From ecc4046e3ed736e5e7d37578d562fbc3bdc8531f Mon Sep 17 00:00:00 2001 From: Ruoxi Ning Date: Sun, 5 Jan 2025 01:53:42 -0500 Subject: [PATCH] Deployed fdd6573 with MkDocs version: 1.4.3 --- index.html | 12 ++++++------ search/search_index.json | 2 +- sitemap.xml.gz | Bin 827 -> 827 bytes 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/index.html b/index.html index 3bca2c82..6339b9dd 100644 --- a/index.html +++ b/index.html @@ -363,14 +363,14 @@
  • - ๅ‹้“พ + ๐Ÿง‘โ€๐Ÿคโ€๐Ÿง‘ ๅ‹้“พ
  • - ่”็ณปไฝœ่€… + โ˜Ž๏ธ ่”็ณปไฝœ่€…
    • @@ -1955,14 +1955,14 @@
  • - ๅ‹้“พ + ๐Ÿง‘โ€๐Ÿคโ€๐Ÿง‘ ๅ‹้“พ
  • - ่”็ณปไฝœ่€… + โ˜Ž๏ธ ่”็ณปไฝœ่€…
    • @@ -2102,7 +2102,7 @@

    โฐ ๆ›ดๆ–ฐ่ฎฐๅฝ•

    -

    ๅ‹้“พ

    +

    ๐Ÿง‘โ€๐Ÿคโ€๐Ÿง‘ ๅ‹้“พ

    @@ -2129,7 +2129,7 @@

    ๅ‹้“พ

    -

    ่”็ณปไฝœ่€…

    +

    โ˜Ž๏ธ ่”็ณปไฝœ่€…

    ๐Ÿ“ซ ้‚ฎ็ฎฑ | ๐Ÿง‘โ€๐Ÿ’ป ไธป้กต

    diff --git a/search/search_index.json b/search/search_index.json index 1201d2bd..d04f37b7 100644 --- a/search/search_index.json +++ b/search/search_index.json @@ -1 +1 @@ -{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"\ud83c\udfdb\ufe0f Mini Babel Library","text":"

    :material-circle-edit-outline: \u7ea6 231 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    La biblioteca de Babel

    \u300c\u5b87\u5b99\uff08\u522b\u4eba\u7ba1\u5b83\u53eb\u56fe\u4e66\u9986\uff09\u7531\u8bb8\u591a\u516d\u89d2\u5f62\u7684\u56de\u5eca\u7ec4\u6210\uff0c\u6570\u76ee\u4e0d\u80fd\u786e\u5b9a\uff0c\u4e5f\u8bb8\u662f\u65e0\u9650\u7684\u300d \u2014\u2014 Jorge Luis Borges (1939)

    \u8fd9\u662f\u6211\u4e3b\u8981\u7528\u4e2d\u6587\u5199\u7684 BLOG\uff0c\u5927\u90e8\u5206\u5185\u5bb9\u662f\u5b66\u4e60\u7b14\u8bb0\u3002\u6211\u7684\u7b14\u8bb0\u4e0d\u591a\uff01\u4ee5\u540e\u4e5f\u4e0d\u4f1a\u591a\u7684(\u4fdd\u8d28\u4e0d\u4fdd\u91cf) \u6b22\u8fce\u6765\u770b\u6211\u7684\u7b14\u8bb0\uff01

    "},{"location":"#content-shortcut","title":"\ud83d\uded7 Content Shortcut\u23f0 \u66f4\u65b0\u8bb0\u5f55","text":"

    \ud83d\udcbb Computer Science

    Selection

    \ud83c\udf33 Linguistics

    Selection

    \ud83c\udf93 Deep Learning

    Selection

    \ud83d\udcad Opinions

    Selection

    \ud83c\udfb9 Life

    Selection

    2025-01-04\u00b6

    Music Theory \u4e50\u7406

    French Tense \u6cd5\u8bed\u65f6\u6001

    2025-01-01\u00b6

    2024 Summary

    2024-12-14\u00b6

    Main Page

    \u8bb0\u5f55\u751f\u6210\u5de5\u5177\uff1aTonyCrane/mkdocs-changelog-plugin"},{"location":"#_1","title":"\u53cb\u94fe","text":"\u7ad9 \u5b9a\u4f4d\u662f \u672c\u7ad9\uff1a# \u63ba\u6742\u81ea\u5df1\u89c2\u70b9\u7684\u7b14\u8bb0 + \u5fc3\u5f97 \u4ed3\u5e93\uff1a\ud83d\udd17ZJUCourse \u5ba2\u89c2\u901a\u7528\u7684\u4e00\u4e2aZJU\u8bfe\u7a0b\u8d44\u6599\u5de5\u5177\u7bb1 \ud83d\udd17mem \u7684\u5c0f\u7ad9 \u5185\u5bb9\u4e3b\u8981\u662f\u7b97\u6cd5\u7b14\u8bb0 + ZJU \u8bfe\u7a0b\u7b14\u8bb0\u3002\u8c22\u8c22\u7b2c\u4e00\u4f4d\u627e\u6211\u6362\u53cb\u94fe\u7684\u5c0f\u670b\u53cb\uff01\u662f\u5f88\u5389\u5bb3\u7684 OIer \ud83d\udd17\u79d1\u5b66\u7a7a\u95f4 \u82cf\u5251\u6797\u82cf\u795e\u7684 blog\uff0c\u66f4\u65b0\u4e86\u5341\u51e0\u5e74\u4e86\uff0c\u4ef0\u6155"},{"location":"#_2","title":"\u8054\u7cfb\u4f5c\u8005","text":"

    \ud83d\udceb \u90ae\u7bb1 | \ud83e\uddd1\u200d\ud83d\udcbb \u4e3b\u9875

    "},{"location":"docs/1-cs/","title":"Computer Science Notes","text":"

    :material-circle-edit-outline: \u7ea6 460 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    This section mainly consists of my selected notes on the course/project/assignment of the computer science courses from Zhejiang University. \u672c\u7ae0\u8282\u5185\u5bb9\u4e3b\u8981\u4e3a\u6d59\u6c5f\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662\u8bfe\u7a0b\u7684\u8bfe\u7a0b/\u9879\u76ee/\u4f5c\u4e1a\u7b14\u8bb0\u3002

    I respect the honest code of computer science school of Zhejiang University and do not publish any content against this code (e.g., solutions of the assignments or source codes of the projects). Please contact me if you find anything that has the risk to violate the code.

    "},{"location":"docs/1-cs/#compass","title":"\ud83e\udded Compass","text":"

    \u5728\u7f51\u4e0a\u627e\u7b14\u8bb0/\u8d44\u6e90\u7684\u65f6\u5019\uff0c\u6211\u7684\u6700\u5927\u611f\u53d7\u4e4b\u4e00\u662f\u867d\u7136\u8d44\u6e90\u5f88\u591a\u5f88\u591a\uff0c\u4f46\u662f\u5e38\u5e38\u4e0d\u77e5\u9053\u67d0\u4e2a\u8d44\u6e90\u6709\u591a\u91cd\u8981\uff0c\u65e0\u6cd5\u8bc4\u4f30\u91cc\u9762\u6db5\u76d6\u4e86\u591a\u5c11\u4e1c\u897f\u4ece\u800c\u4e0d\u77e5\u9053\u8981\u4e0d\u8981\u70b9\u5f00\uff0c\u6216\u8005\u65e0\u6cd5\u4f30\u8ba1\u5728\u671f\u672b\u6709\u9650\u7684\u65f6\u95f4\u91cc\u5e94\u8be5\u82b1\u591a\u5c11\u65f6\u95f4\u590d\u4e60\u67d0\u4e2a\u8d44\u6e90\u3002\u6211\u6b63\u5728\u52aa\u529b\u5728\u8fd9\u91cc\u5efa\u4e00\u4e2a\u5c1a\u80fd\u8bfb\u7684\u8d44\u6e90\u7684 pagetable\uff0c\u4ee5\u9632\u4e0d\u5e78\u7684\u6e38\u5ba2\u4ece\u4fa7\u8fb9\u680f\u6e38\u8d70\u8fdb\u672c\u56fe\u4e66\u9986\u7684\u5783\u573e\u5806\u6f29\u6da1\ud83c\udf00\u3002\u5982\u679c\u6211\u76ee\u524d\u7684\u7b14\u8bb0\u5728\u8fd9\u4e2a\u7ef4\u5ea6\u4e0a\u505a\u5f97\u4e0d\u597d\uff0c\u8bf7\u8054\u7cfb\u6211\u6216\u8005\u5411\u6211\u63d0 issue \u50ac\u6211\u6539 \u8c22\u8c22\uff01

    \u56fe\u4f8b

    \ufe0f\ud83d\udcd8 \ufe0f\ud83d\udcd6 \ud83e\uddea \ud83d\udd17 \u5b8c\u6210\u5ea6\u4e0d\u9ad8\uff0c\u5f03\u5751\u6216\u5728\u5199\uff0c\u4e0d\u63a8\u8350\u9605\u8bfb \uff08\u7279\u6307\u7406\u8bba\uff09\u5b8c\u6210\u5ea6\u8db3\u591f\u9ad8\uff0c\u53ef\u4ee5\u9605\u8bfb\uff01 \u4ec5\u5b9e\u9a8c\u8d44\u6e90\uff0c\u672a\u5199\u7406\u8bba\u90e8\u5206 \u540c\u7c7b\u4f18\u8d28\u6216\u66f4\u4f18\u8d44\u6e90\u63a8\u8350 \u7c7b\u522b \u8bfe.. \u7f16\u7a0b\u8bed\u8a00 \ud83d\udcd8C\u5c16 \ud83d\udcd8C++ \ud83d\udd17\u8bb2\u4e49@\u6684 \ud83d\udcd8Verilog \ud83d\udd17\u5b9e\u9a8c@\u74dc \ud83d\udd17playground@HDLB \ud83d\udcd8Python \ud83d\udcd6x86\u6c47\u7f16 \u8ba1\u7b97\u673a\u79d1\u5b66 \ud83d\udcd8\u79bb\u6563\u6570\u5b66 \ud83d\udd17\u8bb2\u4e49@Kaleo \ud83d\udcd8FDS \ud83d\udcd8ADS \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8\u8ba1\u7b97\u7406\u8bba \ud83d\udd17\u8bb2\u4e49@\u6684 \ufe0f\ud83d\udcd8\u7f16\u8bd1\u539f\u7406 \ud83d\udd17\u8bb2\u4e49@\u6684 \u8f6f\u4ef6 \ud83e\uddeaOS \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8DBMS \ud83d\udcd8\u8ba1\u7f51 \ud83d\udcd8\u8f6f\u5de5 \u786c\u4ef6 \ud83d\udcd8\u6570\u903b \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8\u8ba1\u6982 \ud83d\udcd8\u8ba1\u7ec4 \ud83d\udd17\u8bb2\u4e49@\u6684&\u4fee \ud83d\udcd6\u4f53\u7cfb"},{"location":"docs/1-cs/#contents","title":"\ud83d\udcdd Contents","text":""},{"location":"docs/1-cs/assembly-x86/","title":"x86\u6c47\u7f16","text":"

    :material-circle-edit-outline: \u7ea6 5487 \u4e2a\u5b57 :fontawesome-solid-code: 47 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f

    "},{"location":"docs/1-cs/assembly-x86/#lab","title":"Lab\u8bb0\u5f55","text":"

    Failure

    Lab\u5df2\u7ecf\u5168\u90e8\u6362\u6389\uff0c\u8fd9\u90e8\u5206\u4f5c\u4e1a\u4ecb\u7ecd\u65e0\u6cd5\u53c2\u8003\u4e86\u3002

    "},{"location":"docs/1-cs/assembly-x86/#6","title":"6\u79cd\u5bfb\u5740\u65b9\u5f0f\u4e0e\u5176\u4f5c\u7528","text":"\u8bf4\u660e \u793a\u4f8b \u4f5c\u7528 \u7acb\u5373\u5bfb\u5740 mov eax,56H \u901a\u5e38\u7528\u4e8e\u8d4b\u503c \u76f4\u63a5\u5bfb\u5740 mov eax,[1255887H] \u901a\u5e38\u7528\u4e8e\u5904\u7406\u53d8\u91cf \u5bc4\u5b58\u5668\u5bfb\u5740 mov eax,[edi] \u5730\u5740\u5728\u5bc4\u5b58\u5668\u4e2d \u5bc4\u5b58\u5668\u76f8\u5bf9\u5bfb\u5740 mov eax,[edi+20H] \u5e38\u7528\u4e8e\u8bbf\u95ee\u6570\u7ec4\u548c\u7ed3\u6784 \u57fa\u5740\u52a0\u53d8\u5740\u5bfb\u5740 mov eax,[EBP+ESI] \u5e38\u7528\u4e8e\u8bbf\u95ee\u6570\u7ec4 \u76f8\u5bf9\u57fa\u5740\u52a0\u53d8\u5740\u5bfb\u5740 mov eax,[EBX+EDI-10H] \u5e38\u7528\u4e8e\u8bbf\u95ee\u7ed3\u6784"},{"location":"docs/1-cs/assembly-x86/#obj-dump","title":"obj dump","text":"

    \u6e90\u4ee3\u7801\u6587\u4ef6\u540dmytest.c

    gcc -c -g -o mytest mytest.c\nobjdump -s -d main.o > main.o.txt\n

    \u76ee\u6807\u6587\u4ef6\u53cd\u6c47\u7f16\uff0c\u540c\u65f6\u663e\u793a\u6e90\u4ee3\u7801

    gcc -g -c -o main.o main.c\nobjdump -S -d main.o > main.o.txt\n

    \u663e\u793a\u6e90\u4ee3\u7801\u7684\u540c\u65f6\u663e\u793a\u884c\u53f7

    objdump -j .text -ld -C -S main.o > main.o.txt\n

    \u53ef\u6267\u884c\u6587\u4ef6\u53cd\u6c47\u7f16

    gcc -o main main.c\nobjdump -s -d main > main.txt\n

    \u540c\u65f6\u663e\u793a\u6e90\u4ee3\u7801

    gcc -g -o main main.c\nobjdump -S -d main > main.txt\n
    "},{"location":"docs/1-cs/assembly-x86/#_1","title":"\u671f\u672b\u8003\u8bd5","text":"
    1. \u662f\u975e\u9898(10\u4e2a\uff0c\u6bcf\u98981\u5206\uff0c\u517110\u5206)
    2. \u586b\u7a7a(15\u4e2a\uff0c\u6bcf\u7a7a2\u5206\uff0c\u517130\u5206)\uff1a

    3. \u7a0b\u5e8f\u586b\u7a7a\u9898(3\u9898\uff0c\u6bcf\u989810\u5206\uff0c\u517130\u5206)

      \u4e00\u822c\u90fd\u4f1a\u7528stack\u538b\u5165\u53c2\u6570 \u4f1a\u7ed9\u51fac\u8bed\u8a00\u7684\u539f\u578b\uff08\uff1f\uff0c\u53c2\u6570\u7684\u538b\u5165\u987a\u5e8f\u4ece\u53f3\u5230\u5de6\uff0ccaller\u6e05\u7406 pascal\uff0c\u4ece\u5de6\u5230\u53f3\uff0ccallee\u6e05\u7406 stdcall\uff0c\u4ece\u53f3\u5230\u5de6\uff0ccaller\u6e05\u7406 \u90fd\u7528ax\u8fd4\u56de\u53c2\u6570 \u4e00\u822c\u4e24\u4e2a\u7a7a\u4e0d\u53ef\u4ee5\u4ea4\u6362\u3002\u3002\u3002 \u5148\u81ea\u5df1\u5199\u4e00\u904d\u518d\u586b \uff08\u4e00\u822c20\u51e0\u884c\u7684\u7a0b\u5e8f\uff09

    4. \u7a0b\u5e8f\u9605\u8bfb(2\u9898\uff0c\u6bcf\u98985\u5206\uff0c\u517110\u5206) \u4f1a\u95ee\u8fd0\u884c\u7ed3\u679c\u548c\u4e2d\u95f4\u7ed3\u679c\uff08#\uff09\uff08\u5982\u679c\u6709\u5faa\u73af\uff0c\u6bcf\u6b21\u5faa\u73af\u5230\u90fd\u8981\u5199\uff0c\u4f46\u662f\u4e0d\u4f1a\u592a\u591a\uff09

    \u4e0d\u4f1a\u6709\u76f4\u63a5\u624b\u5199\u4e00\u6574\u4e2a\u7a0b\u5e8f\u7684\u9898

    \u91cd\u70b9\uff1a \u51fd\u6570\u53c2\u6570\u4f20\u9012\uff0c\u5982\u4f55\u6784\u9020\u4e00\u4e2a\u5806\u6808\u6846\u67b6\uff0cebp\u3002\u3002 \u9700\u8981\u770b\u61c2\u662f\u4e0d\u662f\u9012\u5f52\uff0c \u6709\u4e00\u4e2a\u7a0b\u5e8f\u586b\u7a7a\u4f1a\u51fa\u5355\u6b65\u8c03\u8bd5\uff0c\u8fb9\u89e3\u5bc6\u8fb9\u52a0\u5bc6\u90a3\u4e2a\u3002\u3002 \u4e0d\u4f1a\u8003\u4fdd\u62a4\u6a21\u5f0f\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_2","title":"\u590d\u4e60","text":""},{"location":"docs/1-cs/assembly-x86/#intel-808680386-cpu","title":"Intel 8086/80386 CPU \u529f\u80fd\u7ed3\u6784","text":""},{"location":"docs/1-cs/assembly-x86/#_3","title":"\u5de5\u4f5c\u65b9\u5f0f","text":"
    1. \u4ece\u5b58\u50a8\u5668\u4e2d\u53d6\u4e00\u6761\u6307\u4ee4
    2. \u5206\u6790\u6307\u4ee4\u7684\u64cd\u4f5c\u7801
    3. \u4ece\u5b58\u50a8\u5668\u4e2d\u8bfb\u53d6\u64cd\u4f5c\u6570
    4. \u6267\u884c\u6307\u4ee4
    5. \u5199\u5165\u7ed3\u679c\u96c6
    6. \u56de\u52301

    \u8fd0\u7b97\u5668\u8fdb\u884c\u4fe1\u606f\u5904\u7406\uff0c\u5bc4\u5b58\u5668\u8fdb\u884c\u4fe1\u606f\u5b58\u50a8\uff0c\u63a7\u5236\u5668\u63a7\u5236\u5404\u79cd\u5668\u4ef6\u5de5\u4f5c\uff0c\u603b\u7ebf\u8fde\u63a5\u5404\u79cd\u5668\u4ef6\u3002

    "},{"location":"docs/1-cs/assembly-x86/#163280x86-view","title":"16\u4f4d\u548c32\u4f4d\u768480x86\u7684\u533a\u522b - \u64cd\u4f5c\u7cfb\u7edfview","text":""},{"location":"docs/1-cs/assembly-x86/#_4","title":"\u903b\u8f91\u5730\u5740\u4e0e\u7269\u7406\u5730\u5740\u8f6c\u6362\uff1a","text":"

    1234h:0058h \u8f6c\u5316\u6210\u7269\u7406\u5730\u5740=12340h+0058h=12398h \u8865\u7801

    "},{"location":"docs/1-cs/assembly-x86/#_5","title":"\u6807\u5fd7\u4f4d","text":"

    \u72b6\u6001\u6807\u5fd7\uff1aCF ZF SF OF AF PF \u63a7\u5236\u6807\u5fd7\uff1aDF(direction flags) TF(trace/trap flag) IF(interrupt flag)

    "},{"location":"docs/1-cs/assembly-x86/#_6","title":"\u6570\u636e\u5728\u5185\u5b58\u4e2d\u7684\u5b58\u653e\u89c4\u5f8b\uff1a","text":"

    \u5c0f\u7aef\u683c\u5f0f\u3002\u4f4e\u5b57\u8282\u5728\u524d\uff0c\u9ad8\u5b57\u8282\u5728\u540e\u3002 \u8bbeds=1000h, bx=2000h, ax=1234h Mov ds:[bx], ax \u6267\u884c\u540e1000:2001\u6307\u5411\u7684\u5b57\u8282=12h

    "},{"location":"docs/1-cs/assembly-x86/#_7","title":"\u5bc4\u5b58\u5668","text":"

    \u603b\u7ed3

    \u5bc4\u5b58\u5668 \u7c7b\u522b \u7528\u9014 AX \u6570\u636e\u5bc4\u5b58\u5668 \u7b97\u672f\u8fd0\u7b97\u4e2d\u7684\u4e3b\u8981\u5bc4\u5b58\u5668\uff0c\u5728\u4e58\u9664\u8fd0\u7b97\u4e2d\u7528\u6765\u5236\u5b9a\u88ab\u9664\u6570\uff0c\u4e5f\u662f\u4e58\u9664\u8fd0\u7b97\u540e\u7ed3\u679c\u7684\u9ed8\u8ba4\u5b58\u50a8\u5355\u5143\u3002\u53e6\u5916I/O\u6307\u4ee4\u5747\u4f7f\u7528\u8be5\u5bc4\u5b58\u5668\u4e0eI/O\u8bbe\u5907\u4f20\u9001\u4fe1\u606f\u3002 BX \u6570\u636e\u5bc4\u5b58\u5668 \u6307\u4ee4\u5bfb\u5740\u65f6\u5e38\u7528\u505a\u57fa\u5740\u5bc4\u5b58\u5668\uff0c\u5b58\u5165\u504f\u79fb\u91cf\u6216\u504f\u79fb\u91cf\u7684\u6784\u6210\u6210\u5206 CX \u6570\u636e\u5bc4\u5b58\u5668 \u5728\u5faa\u73af\u6307\u4ee4\u64cd\u4f5c\u6216\u4e32\u5904\u7406\u6307\u4ee4\u4e2d\u9690\u542b\u8ba1\u6570 DX \u6570\u636e\u5bc4\u5b58\u5668 \u5728\u53cc\u5b57\u8282\u957f\u8fd0\u7b97\u4e2d\u4e0eAX\u6784\u621032\u4f4d\u64cd\u4f5c\u6570\uff0cDX\u4e3a\u9ad816\u4f4d\u3002\u5728\u67d0\u4e9bI/O\u6307\u4ee4\u4e2d\uff0cDX\u88ab\u7528\u6765\u5b58\u653e\u7aef\u53e3\u5730\u5740 SP \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u59cb\u7ec8\u662f\u6808\u9876\u7684\u4f4d\u7f6e\uff0c\u4e0eSS\u5bc4\u5b58\u5668\u4e00\u8d77\u6784\u6210\u6808\u9876\u6570\u636e\u7684\u7269\u7406\u5730\u5740 BP \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u7cfb\u7edf\u9ed8\u8ba4\u5176\u6307\u5411\u5806\u6808\u4e2d\u67d0\u4e00\u5355\u5143\uff0c\u5373\u63d0\u4f9b\u6808\u4e2d\u8be5\u5355\u5143\u7684\u504f\u79fb\u91cf\u3002\u52a0\u6bb5\u524d\u7f00\u540e\uff0cBP\u53ef\u4f5c\u4e3a\u975e\u5806\u6808\u6bb5\u7684\u5730\u5740\u6307\u9488 SI \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u4e0eDS\u8054\u7528\uff0c\u6307\u793a\u6570\u636e\u6bb5\u4e2d\u67d0\u64cd\u4f5c\u7684\u504f\u79fb\u91cf\u3002\u5728\u505a\u4e32\u5904\u7406\u65f6\uff0cSI\u6307\u793a\u6e90\u64cd\u4f5c\u6570\u5730\u5740\uff0c\u5e76\u6709\u81ea\u52a8\u589e\u91cf\u548c\u81ea\u52a8\u51cf\u91cf\u7684\u529f\u80fd\u3002\u53d8\u5740\u5bfb\u5740\u65f6\uff0cSI\u4e0e\u67d0\u4e00\u4f4d\u79fb\u91cf\u5171\u540c\u6784\u6210\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf DI \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u4e0eDS\u8054\u7528\uff0c\u6307\u793a\u6570\u636e\u6bb5\u4e2d\u67d0\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf\uff0c\u6216\u4e0e\u67d0\u4e00\u4f4d\u79fb\u91cf\u5171\u540c\u6784\u6210\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf\uff0c\u4e32\u5904\u7406\u64cd\u4f5c\u65f6\uff0cDI\u6307\u793a\u9644\u52a0\u6bb5\u4e2d\u76ee\u7684\u5730\u5740\uff0c\u5e76\u6709\u81ea\u52a8\u589e\u91cf\u548c\u51cf\u91cf\u7684\u529f\u80fd\u3002 CS \u6bb5\u5bc4\u5b58\u5668 \u5b58\u653e\u5f53\u524d\u7a0b\u5e8f\u7684\u6307\u793a\u4ee3\u7801 DS \u6bb5\u5bc4\u5b58\u5668 \u5b58\u653e\u7a0b\u5e8f\u6240\u8bbe\u8ba1\u7684\u6e90\u6570\u636e\u6216\u7ed3\u679c SS \u6bb5\u5bc4\u5b58\u5668 \u4ee5\u201c\u5148\u5165\u540e\u51fa\u201d\u4e3a\u539f\u5219\u7684\u6570\u636e\u533a ES \u6bb5\u5bc4\u5b58\u5668 \u8f85\u52a9\u6570\u636e\u533a\uff0c\u5b58\u653e\u4e32\u6216\u5176\u5b83\u6570\u636e IP \u63a7\u5236\u5bc4\u5b58\u5668 \u5b83\u59cb\u7ec8\u6307\u5411\u5f53\u524d\u5c06\u8981\u6267\u884c\u6307\u4ee4\u5728\u4ee3\u7801\u6bb5\u4e2d\u7684\u504f\u79fb\u91cf FR \u63a7\u5236\u5bc4\u5b58\u5668 \u63a7\u5236\u6807\u5fd7\u4f4d

    "},{"location":"docs/1-cs/assembly-x86/#_8","title":"\u901a\u7528\u5bc4\u5b58\u5668","text":"

    IA-32\u67b6\u6784\u4e2d\u4e00\u5171\u67094\u4e2a32\u4f4d\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u4fdd\u5b58\u4e34\u65f6\u6570\u636e\uff0c\u8fd94\u4e2a\u901a\u7528\u5bc4\u5b58\u5668\u53ef\u4ee5\u5f53\u4f5c16\u4f4d\u7528\uff0c\u4e5f\u53ef\u4ee5\u4f5c8\u4f4d\u7528\u3002

    AX BX CX DX\uff1a\u6570\u636e\u5bc4\u5b58\u5668\uff0c\u6bcf\u4e2a\u6570\u636e\u5bc4\u5b58\u5668\u90fd\u53ef\u4ee5\u62c6\u6210\u4e24\u4e2a 8 \u4f4d\u5bc4\u5b58\u5668\u72ec\u7acb\u4f7f\u7528\uff0c\u5982 AX \u53ef\u62c6\u5206\u4e3a AH \u548c AL\uff0cBX \u62c6\u5206\u4e3a BH \u548c BL \u7b49\u3002H \u548c L \u5206\u522b\u8868\u793a\u9ad8 8 \u4f4d\u548c\u4f4e 8 \u4f4d\u3002

    AX(accumulator)\uff1a\u7d2f\u52a0\u5668\u3002\u5728\u4e58\u9664\u6cd5\u8fd0\u7b97\u3001\u4e32\u8fd0\u7b97\u3001 I/O \u6307\u4ee4\u4e2d\u90fd\u4f5c\u4e3a\u4e13\u7528\u5bc4\u5b58\u5668\uff1b BX (base)\uff1a\u57fa\u5740\u5bc4\u5b58\u5668\uff0c\u5e38\u7528\u4e8e\u5b58\u6863\u5185\u5b58\u5730\u5740\u3002

    CX (count)\uff1a\u8ba1\u6570\u5bc4\u5b58\u5668\u3002\u5e38\u7528\u4e8e\u5b58\u653e\u5faa\u73af\u8bed\u53e5\u7684\u5faa\u73af\u6b21\u6570\uff0c\u5b57\u7b26\u4e32\u64cd\u4f5c\u4e2d\u4e5f\u5e38\u7528\u3002

    DX (data)\uff1a\u6570\u636e\u5bc4\u5b58\u5668\u3002\u5e38\u5e38\u548cEAX\u4e00\u8d77\u4f7f\u7528\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_9","title":"\u53d8\u5740\u5bc4\u5b58\u5668","text":"

    \u5b58\u653e\u5728\u53d8\u52a8\u7684\u5185\u5b58\u5730\u5740

    ESI(source index): \u6e90\u53d8\u5740\u5bc4\u5b58\u5668\uff0c\u901a\u5e38\u5b58\u653e\u8981\u5904\u7406\u7684\u6570\u636e\u7684\u5185\u5b58\u5730\u5740\u3002

    EDI(destination index)\uff1a\u76ee\u7684\u53d8\u5740\u5bc4\u5b58\u5668\uff0c\u901a\u5e38\u5b58\u653e\u5904\u7406\u540e\u7684\u6570\u636e\u7684\u5185\u5b58\u5730\u5740\u3002

    ESI\u548cEDI\u5e38\u7528\u6765\u914d\u5408\u4f7f\u7528\u5b8c\u6210\u6570\u636e\u7684\u8d4b\u503c\u64cd\u4f5c

    rep movs dword ptr[edi], dword ptr[esi];\n

    \u8fd9\u53e5\u7684\u610f\u601d\u662f\u628aESI\u6307\u5411\u7684\u5185\u5b58\u5730\u5740\u4e2d\u7684\u5185\u5bb9\u590d\u5236\u5230EDI\u6240\u6307\u5411\u7684\u5185\u5b58\u4e2d\uff0c\u6570\u636e\u957f\u5ea6\u5728ECX\u4e2d\u6307\u5b9a\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_10","title":"\u6307\u9488\u5bc4\u5b58\u5668","text":"

    ESP\uff08stack pointer\uff09\uff1a\u5806\u6808\u6307\u9488\u5bc4\u5b58\u5668\u3002SS\uff1aSP\u6307\u5411\u5806\u6808\u7684\u6808\u9876\uff0c\u56e0\u6b64\u867d\u7136\u662f\u901a\u7528\u5bc4\u5b58\u5668\uff0c\u4f46\u4e0d\u5e94\u968f\u4fbf\u6539\u53d8SP\u7684\u503c\u3002\u4e0d\u53ef\u4ee5\u4f5c\u4e3a\u901a\u7528\u5bc4\u5b58\u5668\u4f7f\u7528\uff0cESP\u5b58\u653e\u5f53\u524d\u5806\u6808\u6808\u9876\u7684\u5730\u5740\uff0c\u4e00\u822c\u60c5\u51b5\u4e0b\uff0cESP\u548cEBP\u8054\u5408\u4f7f\u7528\u6765\u8bbf\u95ee\u51fd\u6570\u4e2d\u7684\u53c2\u6570\u548c\u5c40\u90e8\u53d8\u91cf\u3002 EBP\uff08base pointer\uff09\uff1a\u57fa\u5740\u6307\u9488\u5bc4\u5b58\u5668\u3002\u53ef\u4ee5\u4f5c\u4e3a\u901a\u7528\u5bc4\u5b58\u5668\u7528\u4e8e\u5b58\u653e\u64cd\u4f5c\u6570\uff0c\u5e38\u7528\u6765\u4ee3\u66ff\u5806\u6808\u6307\u9488\u8bbf\u95ee\u5806\u6808\u7684\u6570\u636e\u3002 EIP\uff1a\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668\uff0c\u603b\u662f\u6307\u5411\u4e0b\u4e00\u6761\u8981\u6267\u884c\u7684\u6307\u4ee4\u7684\u5730\u5740\u3002 \u5e38\u89c1\u7684\u8bbf\u95ee\u5806\u6808\u6307\u4ee4\uff1a

    push ebp\nmov ebp, esp\nsub esp, 78\npush esi\npush edi\ncmp dword ptr [ebp+8], 0\n

    ss\u6808\u6bb5\u5bc4\u5b58\u5668 sp\u6808\u9876\u6307\u9488\u5bc4\u5b58\u5668 bp\u9ed8\u8ba4\u7684\u6808\u5bfb\u5740\u5bc4\u5b58\u5668

    "},{"location":"docs/1-cs/assembly-x86/#_11","title":"\u6807\u5fd7\u5bc4\u5b58\u5668","text":"

    \u6807\u5fd7\u5bc4\u5b58\u5668EFLAGS\u4e00\u5171\u670932\u4f4d\uff0c\u5728\u8fd932\u4f4d\u4e2d\u5927\u90e8\u5206\u662f\u4fdd\u7559\u7ed9\u7f16\u5199\u64cd\u4f5c\u7cfb\u7edf\u7684\u4eba\u7528\u7684\u3002

    IP (instruction pointer)\uff1a\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668\u3002\u4ee3\u7801\u6bb5\u5bc4\u5b58\u5668 CS \u548c\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668 IP \u662f 8086CPU \u4e2d\u6700\u5173\u952e\u7684\u4e24\u4e2a\u5bc4\u5b58\u5668\u3002\u5b83\u4eec\u5206\u522b\u7528\u6765\u63d0\u4f9b\u5f53\u524d\u6307\u4ee4\u7684\u6bb5\u5730\u5740\u548c\u504f\u79fb\u5730\u5740\u3002\u5373\u4efb\u610f\u65f6\u523b\uff0c8086CPU \u5c06 CS:IP \u6307\u5411\u7684\u5185\u5bb9\u5f53\u505a\u547d\u4ee4\u6267\u884c\u3002\u6bcf\u6761\u6307\u4ee4\u8fdb\u5165\u6307\u4ee4\u7f13\u51b2\u5668\u540e\u3001\u6267\u884c\u524d\uff0cIP += \u6240\u8bfb\u53d6\u6307\u4ee4\u7684\u957f\u5ea6\uff0c\u4ece\u800c\u6307\u5411\u4e0b\u4e00\u6761\u6307\u4ee4\u3002\u7528\u6237\u4e0d\u80fd\u76f4\u63a5\u8bbf\u95ee IP \u5bc4\u5b58\u5668\u3002

    FL (flags)\uff1a\u6807\u5fd7\u5bc4\u5b58\u5668\u3002\u4e0e\u5176\u4ed6\u5bc4\u5b58\u5668\u4e00\u6837\uff0c\u6807\u5fd7\u5bc4\u5b58\u5668\u4e5f\u6709 16 \u4f4d\uff0c\u4f46\u662f\u6807\u5fd7\u5bc4\u5b58\u5668\u53ea\u7528\u5230\u5176\u4e2d\u7684 9 \u4f4d\u3002\u8fd9 9 \u4f4d\u5305\u62ec 6 \u4e2a\u72b6\u6001\u6807\u5fd7\u548c 3 \u4e2a\u63a7\u5236\u6807\u5fd7\uff0c\u53c2\u89c1\u4e0b\u9762\u7684\u201c\u6807\u5fd7\u4f4d\u201d\u3002

    OF\uff08Overflow Flag\uff09:\u6ea2\u51fa\u6807\u5fd7\uff0c\u6ea2\u51fa\u65f6\u4e3a1\uff0c\u5426\u5219\u7f6e0\u3002\u4e24\u4e2a\u6b63\u6570\u76f8\u52a0\u53d8\u8d1f\uff0c\u6216\u4e24\u4e2a\u8d1f\u6570\u76f8\u52a0\u53d8\u6b63\u4f1a\u6ea2\u51fa\u3002#

    DF \uff08Direction Flag\uff09:\u65b9\u5411\u6807\u5fd7\uff0c\u5728\u4e32\u5904\u7406\u6307\u4ee4\u4e2d\u63a7\u5236\u4fe1\u606f\u7684\u65b9\u5411\u30020:\u6b63\u65b9\u5411\uff0c1\uff1a\u53cd\u65b9\u5411\u3002cld\uff0cstd\u3002#

    IF (Interrupt Flag) :\u4e2d\u65ad\u6807\u5fd7\u3002\u7981\u6b62\u4e2d\u65ad0\uff0c\u5141\u8bb8\u4e2d\u65ad1\u3002cli\uff0csti\u3002#

    AF (Auxiliary carry Flag) :\u8f85\u52a9\u8fdb\u4f4d\u6807\u5fd7\uff0c\u6709\u8fdb\u4f4d\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    ZF (Zero Flag) :\u96f6\u6807\u5fd7\uff0c\u8fd0\u7b97\u7ed3\u6784\u4e3a0\u65f6ZF\u4f4d\u4f4d\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    SF (Sign Flag):\u7b26\u53f7\u6807\u5fd7\uff0c\u7ed3\u679c\u4e3a\u8d1f\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002#

    CF (Carry Flag): \u8fdb\u4f4d\u6807\u5fd7\uff0c\u8fdb\u4f4d\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002\u914d\u5957\u7684clc\uff0cstc\u4e24\u6761\u8bbe\u7f6e\u6307\u4ee4\uff1a\u6e05\u9664\u548c\u7f6e1\u3002#

    PF (Parity Flag): \u5947\u5076\u6807\u5fd7\u3002\u7ed3\u679c\u64cd\u4f5c\u6570\u4e2d1\u7684\u4e2a\u6570\u4e3a\u5076\u6570\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    TF\uff1a\u5355\u6b65\u8c03\u8bd5\u8981\u7528\u3002#

    EFLAGS\u662f\u5b9e\u73b0\u6761\u4ef6\u5224\u65ad\u548c\u903b\u8f91\u5224\u65ad\u7684\u4e00\u79cd\u673a\u5236\uff0c\u5728\u6c47\u7f16\u8bed\u8a00\u4e2d\u4e00\u822c\u4e0d\u76f4\u63a5\u8bbf\u95eeEFLAGS\u5bc4\u5b58\u5668\uff0c\u800c\u662f\u901a\u8fc7\u6307\u4ee4\u7684\u64cd\u4f5c\u9690\u542b\u8bbf\u95eeEFLAGS\u5bc4\u5b58\u5668\u3002

    cmp dword ptr [ebp+8], 0. // \u5f71\u54cd\u6807\u5fd7\u4f4dCF\uff0cZF\uff0cSF\uff0cOF\uff0cAF\u548cPF\nJz 99495898 //\u5982\u679cZF\u7b49\u4e8e1\uff0c\u5219\u8df3\u8f6c\u523000405898
    "},{"location":"docs/1-cs/assembly-x86/#_12","title":"\u6307\u4ee4","text":"

    \u603b\u7ed3

    \u6307\u4ee4 \u4f5c\u7528 \u53c2\u6570 \u6539\u53d8\u6807\u5fd7\u4f4d mov \u8d4b\u503c \u88ab\u8d4b\u503c\u5bc4\u5b58\u5668\uff0c\u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\uff0c\u503c\u3011 no xchg \u6570\u636e\u4ea4\u6362 \u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\u3011\uff0c\u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\u3011 no push \u8fdb\u6808 \u6e90\u64cd\u4f5c\u6570\u3010\u5bc4\u5b58\u5668\u3011 pop \u51fa\u6808 \u76ee\u7684\u64cd\u4f5c\u6570\u3010\u5bc4\u5b58\u5668\u3011 pushf \u6807\u5fd7\u4f4d\u8fdb\u6808 \u65e0 popf \u6807\u5fd7\u4f4d\u51fa\u6808 \u65e0 lea Load effect address\uff0c\u5bfb\u5740\uff0c\u53d6\u504f\u79fb\u5730\u5740 lds \u5f53\u6307\u4ee4\u6307\u5b9a\u7684\u662f16\u4f4d\u5bc4\u5b58\u5668\u65f6\uff0c\u628a\u6e90\u64cd\u4f5c\u6570\u5b58\u50a8\u5355\u5143\u4e2d\u5b58\u653e\u7684\u5341\u516d\u4f4d\u504f\u79fb\u5730\u5740\u53d6\u51fa\u5b58\u653e\u5728\u5bc4\u5b58\u5668\u4e2d\uff0c\u7136\u540e\u628a\u6e90\u64cd\u4f5c\u6570+2\u7684\u5341\u516d\u4f4d\u6570\u88c5\u5165\u6307\u4ee4\u6307\u5b9a\u7684\u6bb5\u5bc4\u5b58\u5668\u3002\u5f53\u6307\u4ee4\u6307\u5b9a\u7684\u662f32\u4f4d\u5bc4\u5b58\u5668\u65f6 \u628a\u6e90\u64cd\u4f5c\u6570\u5b58\u50a8\u5355\u5143\u4e2d\u5b58\u653e\u768432\u4f4d\u504f\u79fb\u5730\u5740\u88c5\u5165\u5bc4\u5b58\u5668 \u7136\u540e\u628a \u6e90\u64cd\u4f5c\u6570+4 \u768416\u4f4d\u6570\u88c5\u5165\u6bb5\u5bc4\u5b58\u5668\u3002mem\u6307\u5411\u7684\u5730\u5740,\u9ad8\u4f4d\u5b58\u653e\u5728DS\u4e2d,\u4f4e\u4f4d\u5b58\u653e\u5728reg\u4e2d. LDS reg,mem les \u628a\u5185\u5b58\u4e2d\u6307\u5b9a\u4f4d\u7f6e\u7684\u53cc\u5b57\u64cd\u4f5c\u6570\u7684\u4f4e\u4f4d\u5b57\u88c5\u5165\u6307\u4ee4\u4e2d\u6307\u5b9a\u7684\u5bc4\u5b58\u5668\u3001\u9ad8\u4f4d\u5b57\u88c5\u5165ES\u5bc4\u5b58\u5668\u3002 cbw 8\u4f4d\u6570\u6269\u5c55\u4e3a16\u4f4d\u6570\uff0c\u6709\u7b26\u53f7\u6269\u5145 no cwd \u5b57(16\u4f4d)\u6269\u5c55\u4e3a\u53cc\u5b57(32\u4f4d)\uff0c\u6709\u7b26\u53f7\uff1f no add \u52a0 OPRDS\uff0cOPRDD adc \u5e26\u8fdb\u4f4d\u52a0\uff08\u7ed3\u679c\u542b\u6807\u5fd7\u4f4dCF\u7684\u503c\uff0c=OPRDS\uff0bOPRDD\uff0bCF\uff09 OPRDS\uff0cOPRDD sub \u51cf OPRDD\uff0cOPRDS sbb \u5e26\u8fdb\u4f4d\u51cf\uff08\u7ed3\u679c\u542b\u6807\u5fd7\u4f4dCF\u7684\u503c\uff0c=OPRDD\uff0dOPRDS\uff0dCF\uff09 OPRDD\uff0cOPRDS inc \u81ea\u589e1 \u5bc4\u5b58\u5668 dec \u81ea\u51cf1 \u5bc4\u5b58\u5668 mul 32\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aEAX\uff0c\u90a3\u4e48\u4e58\u79ef\u5c06\u5b58\u653e\u5728EDX\uff1aEAX\u4e2d 32\u4f4d\u4e58\u6570 16\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aAX\u90a3\u4e48\u4e58\u79ef\u5c06\u653e\u5728DX\uff1aAX\u4e2di 16\u4f4d\u4e58\u6570 8\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aAL\uff0c\u90a3\u4e48\u4e58\u79ef\u5c06\u653e\u5728AX 8\u4f4d\u4e58\u6570 div 32\u4f4d\uff1a\u88ab\u9664\u6570\u5c06\u662fEDX\uff1aEAX\uff0c \u6700\u7ec8\u7684\u5546\u5c06\u5b58\u653e\u5728EAX\uff0c \u4f59\u6570\u5c06\u5b58\u653e\u5728EDX\u4e2d 32\u4f4d\u4e58\u6570 16\u4f4d\uff1a\u88ab\u9664\u6570\u4e3aEAX\uff0c\u6700\u7ec8\u5f97\u5230\u7684\u5546\u653e\u5728AX\uff0c\u4f59\u6570\u653e\u5728EAX\u7684\u9ad816\u4f4d 16\u4f4d\u4e58\u6570 8\u4f4d\uff1a\u88ab\u9664\u6570\u662f16\u4f4d\uff0c\u6700\u7ec8\u5f97\u5230\u7684\u5546\u5c06\u653e\u5728AL\u4e2d\uff0c\u4f59\u6570\u653e\u5728AH\u4e2d 8\u4f4d\u4e58\u6570 imul \u65e0\u7b26\u53f7\u4e58 idiv \u65e0\u7b26\u53f7\u9664 xlat \u6362\u7801\u6307\u4ee4\uff0c\u4ee5bx\u4e3a\u9996\u5730\u5740\u7684\uff0c\u504f\u79fb\u5730\u5740\u4e3aal\u7684\u5185\u5bb9\u9001\u7ed9al\u3002 in \u7aef\u53e3\u8bfb\u5199\u6307\u4ee4 IN AL,21H\uff1b\u8868\u793a\u4ece21H\u7aef\u53e3\u8bfb\u53d6\u4e00\u5b57\u8282\u6570\u636e\u5230AL out \u7aef\u53e3\u8bfb\u5199\u6307\u4ee4 and \u6309\u4f4d\u4e0e or \u6309\u4f4d\u6216 xor \u6309\u4f4d\u5f02\u6216 not \u64cd\u4f5c\u6570\u6309\u4f4d\u53d6\u53cd neg \u64cd\u4f5c\u6570\u6309\u4f4d\u53d6\u53cd\u52a0\u4e00 test \u5bf9\u4e24\u4e2a\u64cd\u4f5c\u6570\u8fdb\u884c\u6309\u4f4d\u4e0e\u64cd\u4f5c\u3002\u4e0eand\u4e0d\u540c\uff0c\u4e0d\u5f71\u54cd\u76ee\u6807\u64cd\u4f5c\u6570\u7684\u503c\u3002 shl \u903b\u8f91\u5de6\u79fb\uff0c\u5c06\u4e00\u4e2a\u5bc4\u5b58\u5668\u4e2d\u7684\u503c\u6216\u5355\u5143\u4e2d\u7684\u6570\u636e\u5411\u5de6\u79fb\u4f4d\uff0c\u5c06\u6700\u540e\u79fb\u51fa\u7684\u4e00\u4f4d\u5199\u5165cf\u4e2d\u3002\u6700\u4f4e\u4f4d\u75280\u8865\u5145\u3002 shr \u903b\u8f91\u53f3\u79fb\uff0c\u5c06\u4e00\u4e2a\u5bc4\u5b58\u5668\u4e2d\u7684\u503c\u6216\u5355\u5143\u4e2d\u7684\u6570\u636e\u5411\u5de6\u79fb\u4f4d\uff0c\u5c06\u6700\u540e\u79fb\u51fa\u7684\u4e00\u4f4d\u5199\u5165cf\u4e2d\u3002\u6700\u9ad8\u4f4d\u75280\u8865\u5145\u3002 sal \u7b97\u672f\u5de6\u79fb\uff0c\u4e0eshl\u4e00\u6837\uff0c\u88650 sar \u7b97\u672f\u53f3\u79fb\uff0c\u4e0eshr\u4e0d\u4e00\u6837\uff0c\u7b97\u672f\u53f3\u79fb\u8865\u6700\u9ad8\u4f4d rol \u5faa\u73af\u5de6\u79fb ror \u5faa\u73af\u53f3\u79fb rcl \u5e26\u8fdb\u4f4d\u5faa\u73af\u5de6\u79fb\uff0c\u5de6\u79fb\u7684\u65f6\u5019\u79fb\u51fa\u53bb\u7684\u4f1a\u653e\u5728cf\uff1f rcr \u5e26\u8fdb\u4f4d\u5faa\u73af\u53f3\u79fb cmp \u6bd4\u8f83 ja jump if above jb Jump if below jae Jump if above or equal jbe Jump if below or equal jg jump if greater\uff0c\u6709\u7b26\u53f7\u5927\u4e8e\u8df3\u8f6c jl jump less\uff0c\u6709\u7b26\u53f7\u5c0f\u4e8e\u8df3\u8f6c jge jump if greater or equal jle Jump if less or equal jc jump if with carry, CF = 1 jnc jump if not with carry, CF = 0 je = jz jump if equal, ZF = 1 jne = jnz jump if not equal, ZF = 0 jz jump if zero, ZF = 1 jnz jump if not zero, ZF = 0 jcxz jump if cx equals zero js SF = 1 jns SF = 0 jo Jump if overflow, OF = 1 jno jump if not overflow, OF = 0 loop \u5faa\u73af \u4ee3\u7801\u6bb5\uff08\uff1f\uff09\u540d clc clear carry flag\uff0c\u5c06cf\u4f4d\u6e05\u96f6 stc set carry flag\uff0cCF\u7f6e1 cli clear interrupt endable flag\uff0cIF\u6e05\u96f6\uff0c\u5173\u95ed\u4e2d\u65ad sti set interrupt endable flag\uff0cIF\u7f6e\u4f4d1\uff0c\u6253\u5f00\u4e2d\u65ad CMC complement carry flag\uff0cCF\u53d6\u53cd CLD clear direction flag\uff0cDF\u6e05\u96f6 STD set interrupt endable flag\uff0cDF\u7f6e1 call \u8fd1\u8c03\u7528 ret \u8fd1\u8fd4\u56de call far ptr \u8fdc\u8c03\u7528\u3002\u4e09\u4e2apush\u4e00\u4e2ajmp\u3002push f\uff0cpush cs\uff0cpush ip\uff0cjump retf \u8fdc\u8fd4\u56de\u3002\u4e09\u4e2apop\u3002\u6307\u4ee4\u2f64\u6808\u4e2d\u7684\u6570\u636e\uff0c\u4fee\u6539CS\u548cIP\u7684\u5185\u5bb9\uff0c\u4ece\u2f7d\u5b9e\u73b0\u8fdc\u8f6c\u79fb int \u4e2d\u65ad\u6307\u4ee4 iret \u4e2d\u65ad\u8fd4\u56de jmp short \u6bb5\u5185\u77ed\u8f6c\u79fb\uff0c\u77ed\u662f\u6307\u8981\u8df3\u2f84\u7684\u2f6c\u6807\u5730\u5740\u4e0e\u5f53\u524d\u5730\u5740\u524d\u540e\u76f8\u5dee\u4e0d\u8d85\u8fc7128\u5b57\u8282 jmp near ptr \u6bb5\u5185\u8fd1\u8f6c\u79fb\u3002\u8fd1\u662f\u6307\u8df3\u8f6c\u7684\u2f6c\u6807\u5730\u5740\u4e0e\u5f53\u524d\u5730\u5740\u5728\u2f64\u2f00\u4e2a\u6bb5\u5185\uff0c\u5373CS\u7684\u503c\u4e0d\u53d8\uff0c\u53ea\u6539\u53d8EIP\u7684\u503c jmp far ptr \u6bb5\u95f4\u8f6c\u79fb\uff0c\u8fdc\u6307\u8df3\u5230\u53e6\u2f00\u4e2a\u4ee3\u7801\u6bb5\u53bb\u6267\u2f8f\uff0cCS/EIP\u90fd\u8981\u6539\u53d8 Jmp dword ptr \u6bb5\u95f4\u8f6c\u79fb\uff0c\u4ee5\u5185\u5b58\u5730\u5740\u5355\u5143\u5904\u7684\u53cc\u5b57\u6765\u4fee\u6539\u6307\u4ee4\uff0c\u2fbc\u5730\u5740\u5185\u5bb9\u4fee\u6539CS\uff0c\u4f4e\u5730\u5740\u5185\u5bb9 \u4fee\u6539IP\uff0c\u5185\u5b58\u5730\u5740\u53ef\u4ee5\u4ee5\u4efb\u4f55\u5408\u6cd5\u7684\u2f45\u5f0f\u7ed9\u51fa repe/renpe scasb \u5b57\u7b26\u4e32\u626b\u63cf\u6307\u4ee4\u3002cmp al, es:[di] di++; \u5f53DF=1\u65f6\uff0c\u4e3adi-- repne:\u5f53ECX!=0\u5e76\u4e14ZF==0\u65f6 \u91cd\u590d repe: cx != 0\u4e14zf != 0\u91cd\u590d repe/renpe cmpsb \u5b57\u7b26\u4e32\u6bd4\u8f83\u6307\u4ee4\u3002\u2f50\u8f83byte ptr ds:[si]\u4e0ebyte ptr es:[di] \u5f53DF=0\u65f6\uff0cSI++\uff0cDI++ \u5f53DF=1\u65f6\uff0cSI--\uff0cDI-- repne:\u5f53ECX!=0\u5e76\u4e14ZF==0\u65f6 \u91cd\u590d repe: cx != 0\u4e14zf != 0\u91cd\u590d rep movsb \u5b57\u7b26\u4e32\u79fb\u52a8\u6307\u4ee4\u3002\u5176\u4e2drep\u8868\u793arepeat\uff0cs\u8868\u793astring\uff0cb\u8868\u793abyte \u5728\u6267\u2f8f\u6b64\u6307\u4ee4\u524d\u8981\u505a\u4ee5\u4e0b\u51c6\u5907\u2f2f\u4f5c\uff1a \u2460ds:si lodsb \u5757\u88c5\u5165\u6307\u4ee4\uff0c\u628aSI\u6307\u5411\u7684\u5b58\u50a8\u5355\u5143\u8bfb\u5165\u7d2f\u52a0\u5668\uff0clodsb\u5c31\u8bfb\u5165ax\uff0clodsw\u5c31\u8bfb\u5165ax\uff0c\u7136\u540esi\u81ea\u52a8\u589e\u52a0\u6216\u51cf\u5c0f1\u62162 stosb/stosw/stosd SI\u6307\u5411\u7684\ud83d\udd17,\u5176\u4e2dLODSB\u662f\u8bfb\u5165AL, LODSW\u662f\u8bfb\u5165AX\u4e2d, \u7136\u540eSI\u81ea\u52a8\u589e\u52a0\u6216\u51cf\u5c0f1\u62162\u4f4d.\u5f53\u65b9\u5411\u6807\u5fd7\u4f4dDF=0\u65f6\uff0c\u5219SI\u81ea\u52a8\u589e\u52a0\uff1bDF=1\u65f6\uff0cSI\u81ea\u52a8\u51cf\u5c0f\u3002 rep stosb lodsb"},{"location":"docs/1-cs/assembly-x86/#_13","title":"\u6570\u636e\u4f20\u9001\u6307\u4ee4","text":"

    \u6570\u636e\u4f20\u9001\u6307\u4ee4\u662f\u4e3a\u4e86\u5b9e\u73b0CPU\u548c\u5185\u5b58\uff0c\u8f93\u5165\u548c\u8f93\u51fa\u7aef\u53e3\u4e4b\u95f4\u7684\u6570\u636e\u4f20\u9001\u3002

    mov

    mov eax, 56 // \u5c0656H\u4f20\u9001\u5230eax\u5bc4\u5b58\u5668\nmov esi, dword ptr [eax * 2 + 1]  // \u5c06\u5185\u5b58\u5730\u5740\u4e3aeax*2+1\u76844\u5b57\u8282\u6570\u636e\u4f20\u9001\u5230esi\u5bc4\u5b58\u5668\nmov ah, byte ptr [esi * 2 + eax]  // \u5c06\u5185\u5b58\u5730\u5740\u4e3aesi*+eax\u5904\u76848\u4f4d\u6570\u636e\u4f20\u9001\u5230AH\u5bc4\u5b58\u5668\n

    xchg

    \u5bc4\u5b58\u5668\u548c\u5185\u5b58\u7684\u6570\u636e\u4ea4\u6362\uff0c\u4ea4\u6362\u7684\u6570\u636e\u53ef\u4ee5\u662f8\u5b57\u8282\u300116\u5b57\u8282\u621632\u5b57\u8282\uff0c\u5fc5\u987b\u683c\u5f0f\u76f8\u540c

    xchg eax, edx; // \u5c06edx\u5bc4\u5b58\u5668\u7684\u503c\u548ceax\u5bc4\u5b58\u5668\u7684\u503c\u4ea4\u6362\nxchg [esp-55], edi; // \u5c06edi\u5bc4\u5b58\u5668\u7684\u503c\u548c\u5806\u6808\u5730\u5740\u4e3a[esp-55]\u5904\u7684\u503c\u4ea4\u6362\n

    push pop

    push\u548cpop\uff1a\u79f0\u4e3a\u538b\u5165\u5806\u6808\u6307\u4ee4\u548c\u5f39\u51fa\u5806\u6808\u6307\u4ee4\uff0c\u683c\u5f0f\u662fpush src(\u6e90\u64cd\u4f5c\u6570)\u548cpop dst(\u76ee\u7684\u64cd\u4f5c\u6570)\uff0cpush\u6307\u4ee4\u548cpop\u6307\u4ee4\u9700\u8981\u5339\u914d\u51fa\u73b0\uff0c\u5426\u5219\u5806\u6808\u4f1a\u4e0d\u5e73\u8861\u3002push\u6307\u4ee4\u5c06\u539f\u64cd\u4f5c\u6570src\u538b\u5165\u5806\u6808\uff0c\u540c\u65f6esp-4\uff08\u6808\u9876\u6307\u9488\u51cf\u4e00\u4e2a4\u4f4d\uff09\uff0c\u800cpop\u53cd\u4e4b\uff0c\u4ece\u5806\u6808\u7684\u9876\u90e8\u5f39\u51fa4\u5b57\u8282\u7684\u6570\u503c\u7136\u540e\u653e\u5165dst\u3002\u572832\u4f4d\u7684\u64cd\u4f5c\u7cfb\u7edf\u4e0a\uff0cpush\u548cpop\u7684\u64cd\u4f5c\u662f\u4ee54\u5b57\u8282\u4e3a\u5355\u4f4d\u7684\uff0cpush\u548cpop\u6307\u4ee4\u5e38\u7528\u4e8e\u5411\u51fd\u6570\u4f20\u53c2\u3002

    push eax // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u4ee54\u5b57\u8282\u538b\u5165\u5806\u6808\uff0c\u540c\u65f6esp-4\npush dword ptr [12FF8589] // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230\u5185\u5b58\u5730\u5740\u4e3a12FF8589\u6240\u6307\u5730\u65b9\uff0c\u540c\u65f6esp+4\n-----------------------------------------------------------------------------\npop dword ptr [12FF8589] // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230\u5185\u5b58\u5730\u5740\u4e3a12FF8589\u6240\u6307\u7684\u5730\u65b9\uff0c\u540c\u65f6esp+4\npop eax // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230eax\u5bc4\u5b58\u5668\uff0c\u540c\u65f6esp+4\n
    "},{"location":"docs/1-cs/assembly-x86/#_14","title":"\u5730\u5740\u4f20\u9001\u6307\u4ee4","text":"

    x86\u67093\u6761\u5730\u5740\u4f20\u9001\u6307\u4ee4\uff0c\u5206\u522b\u662fLEA\uff0cLDS\u548cLES\u3002\u5176\u5b9eLDS\u548cLES\u6307\u4ee4\u548c\u6bb5\u5bc4\u5b58\u5668\u6709\u5173\uff0c\u572832\u4f4d\u7684windows\u64cd\u4f5c\u7cfb\u7edf\u4e0a\uff0c\u4e00\u822c\u7684\u7a0b\u5e8f\u5458\u90fd\u4e0d\u9700\u8981\u7ba1\u7406\u6bb5\u5bc4\u5b58\u5668\uff0c\u6240\u4ee5\u76f8\u5bf9\u800c\u8a00\uff0cLDS\u548cLES\u5bc4\u5b58\u5668\u4f7f\u7528\u5f97\u6bd4\u8f83\u5c11\uff0c\u4e00\u822c\u60c5\u51b5\u4e0b\u5e38\u89c1\u7684\u53ea\u6709LEA\u6307\u4ee4\u3002

    LEA

    \u79f0\u4e3a\u5730\u5740\u4f20\u9001\u6307\u4ee4\uff0c\u683c\u5f0f\u662f\u201cLEA DST, ADDR\u201d\u3002LEA\u5c06ADDR\u5730\u5740\u52a0\u8f7d\u5230DST\uff0c\u5176\u4e2dADDR\u53ef\u4ee5\u662f\u5185\u5b58\uff0c\u4e5f\u53ef\u4ee5\u662f\u5bc4\u5b58\u5668\uff0c\u800cDST\u5fc5\u987b\u662f\u4e00\u4e2a\u901a\u7528\u5bc4\u5b58\u5668\u3002

    lea eax, [12345678]; // \u6307\u4ee4\u6267\u884c\u540eeax\u5bc4\u5b58\u5668\u7684\u503c\u4e3a12345678H\nmov eax, [12345678]; // \u800cmov eax, [12345678] \u6307\u4ee4\u6267\u884c\u540eeax\u5bc4\u5b58\u5668\u7684\u503c\u4e3a\u5185\u5b58\u5730\u574012345678\u6307\u5411\u7684\u90a3\u4e2a\u6570\u503c\n// LEA\u6307\u4ee4\u53ef\u7528\u4e8e\u7b97\u6cd5\u8fd0\u7b97\nlea ecx, [ecx + eax*4];  // ecx = ecx + eax * 4\n// \u76f8\u5f53\u4e8e\u8ba1\u7b97\u51faecx+eax*4\u7684\u6570\u503c\uff0c\u5728[]\u91cc\u662f\u4e00\u4e2a\u5730\u5740\uff0clea\u53d6\u5730\u5740\u540e\u5c31\u53d6\u5230\u4e86\u8fd9\u4e2a\u6570\u503c\n
    "},{"location":"docs/1-cs/assembly-x86/#_15","title":"\u7b97\u6570\u8fd0\u7b97\u6307\u4ee4","text":"

    80x86\u63d0\u4f9b\u4e868\u6761\u52a0\u51cf\u6cd5\u6307\u4ee4\uff0c4\u6761\u4e58\u9664\u6cd5\u6307\u4ee4\u3002

    ADD\uff1a\u52a0\u6cd5\u6307\u4ee4

    add eax, esi; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u52a0\u4e0aesi\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u7684\u5bc4\u5b58\u5668\u4e2d\nadd ebx, dword ptr[12345678] // \u5c06ebx\u5bc4\u5b58\u5668\u7684\u503c\u52a0\u4e0a\u5185\u5b58\u5730\u5740\u4e3a12345678\u6240\u5728\u76844\u5b57\u8282\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728ebx\u5bc4\u5b58\u5668\u4e2d\n// \u4e0d\u540c\u7684\u5e73\u53f0\u548c\u7f16\u8bd1\u5668\u4e2d\uff0cdword\u5360\u7528\u7684\u5b57\u8282\u6570\u4e0d\u540c\uff0c\u572832\u4f4d\u7684windows\u4e2d\u4e00\u4e2aword\u536016\u5b57\u8282\uff0cdword\u536032\u5b57\u8282\n// 64\u4f4d\u4e2d\u4e00\u4e2aword\u536032\u5b57\u8282\uff0cdword\u536064\u5b57\u8282\n

    sub \u51cf\u6cd5\u6307\u4ee4

    sub ecx, 4H; // \u5c06ecx\u5bc4\u5b58\u5668\u7684\u503c\u51cf\u53bb4H\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\nsub byte ptr[eax], ch; // \u5c06\u5185\u5b58\u5730\u5740\u4e3aeax\u6240\u6307\u5411\u7684\u6570\u636e\u7ed3\u6784\u6309\u5b57\u8282\u4e3a\u5355\u4f4d\u548cch\u5bc4\u5b58\u5668\u76f8\u51cf\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u6309\u5b57\u8282\u4e3a\u5355\u4f4d\u4fdd\u5b58\u5728eax\u6240\u6307\u5411\u7684\u4f4d\u7f6e\n

    inc\u52a01\u6307\u4ee4

    inc eax; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u52a01\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u653e\u5728\u539f\u6765\u7684\u5730\u65b9\n

    dec\u51cf1\u6307\u4ee4

    dec edx; // \u5c06dec\u5bc4\u5b58\u5668\u7684\u503c\u51cf1\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u653e\u5728\u539f\u6765\u7684\u5730\u65b9\n

    cmp\u6bd4\u8f83\u6307\u4ee4

    \u79f0\u6bd4\u8f83\u6307\u4ee4\u683c\u5f0f\u662f\u201dcmp oper1, oper2\u201d

    cmp\u6307\u4ee4\u5c06oper1\u51cf\u53bboper2\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4e0d\u4fdd\u5b58\uff0c\u53ea\u662f\u76f8\u5e94\u5730\u8bbe\u7f6e\u5bc4\u5b58\u5668eflags\u7684cf\uff0cpf\uff0czf\uff0caf\uff0csf\u548cof\u3002\u4e5f\u5c31\u662f\u8bf4\u53ef\u4ee5\u901a\u8fc7\u6d4b\u8bd5\u5bc4\u5b58\u5668eflags\u76f8\u5173\u7684\u6807\u5fd7\u503c\u5f97\u77e5cmp\u6267\u884c\u540e\u7684\u7ed3\u679c

    cmp eax, 56H; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u51cf\u53bb56H\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4e0d\u4fdd\u5b58\uff0c\u5e76\u4e14\u8bbe\u7f6e\u5bc4\u5b58\u5668eflags\u76f8\u5173\u7684\u6807\u5fd7\u4f4d\n

    neg

    neg\uff1a\u53d6\u8865\u6307\u4ee4\uff0c\u683c\u5f0f\u662fneg oper

    neg\u6307\u4ee4\u5c06oper\u64cd\u4f5c\u6570\u53d6\u53cd\uff0c\u7b80\u800c\u8a00\u4e4b\u5c31\u662f\u5c060\u51cf\u53bboper\u64cd\u4f5c\u6570\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u5728oper\u81ea\u8eab\u4e2d\u3002

    neg eax; \n

    mul imul

    \u65e0\u7b26\u53f7\u4e58\u6cd5\u6307\u4ee4\u548c\u6709\u7b26\u53f7\u4e58\u6cd5\u6307\u4ee4\u3002mul\u6307\u4ee4\u9690\u542b\u4e86\u4e00\u4e2a\u53c2\u52a0\u8fd0\u7b97\u7684\u64cd\u4f5c\u6570eax\u5bc4\u5b58\u5668\uff0c\u5c06eax\u5bc4\u5b58\u5668\u91cc\u7684\u503c\u4e58oper\uff0c\u7ed3\u679c\u4fdd\u5b58\u5728eax\u4e2d\u3002\u5982\u679c\u7ed3\u679c\u8d85\u8fc732\u4f4d\u5219\u9ad832\u4f4d\u4f7f\u7528edx\u5bc4\u5b58\u5668\u4fdd\u5b58\uff0ceax\u5bc4\u5b58\u5668\u4fdd\u5b58\u4f4e32\u4f4d\u3002

    mul edx; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u4e58\u4ee5edx\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\n

    div idiv

    \u9664\u6cd5\u6307\u4ee4\u548c\u6709\u7b26\u53f7\u9664\u6cd5\u6307\u4ee4\u3002

    div ecx; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u63094\u5b57\u8282\u4e3a\u5355\u4f4d\u9664\u4ee5ecx\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5546\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\uff0c\u4f59\u6570\u4fdd\u5b58\u5728edx\u5bc4\u5b58\u5668\u4e2d\u3002\ndiv word ptr [esp+36]; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u6309word\u4e3a\u5355\u4f4d\u9664\u4ee5\u5806\u6808\u5730\u5740\u4e3aesp+36\u6240\u6307\u5411\u7684\u6570\u636e\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5546\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\uff0c\u4f59\u6570\u4fdd\u5b58\u5728edx\u5bc4\u5b58\u5668\u4e2d\u3002\n
    "},{"location":"docs/1-cs/assembly-x86/#80386","title":"\u9ad8\u7ea7\u8bed\u8a00\u4e2d\u7684\u6570\u636e\u7ed3\u6784\u4e0e80386\u95f4\u63a5\u5bfb\u5740","text":"

    BX BP SI DI

    BX\uff1a

    BP\uff1a

    SI\uff1a

    DI\uff1a

    \u95f4\u63a5\u5bfb\u5740\uff1abx\uff0cbp\uff0csi\uff0cdi\uff0c\u53ef\u4ee5\u653e\u5728\u65b9\u62ec\u53f7\u5185

    \u7f3a\u7701\u6bb5\u5740\uff1ads\u548css\uff0c\u5982\u679c\u65b9\u62ec\u53f7\u5185\u6709bp\uff0c\u4e00\u5b9a\u662fss\uff0cbx\u4e00\u5b9a\u662fds

    CS (code segment): \u4ee3\u7801\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u4ee3\u7801\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    DS (data segment)\uff1a\u6570\u636e\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u6570\u636e\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    SS (stack segment)\uff1a\u5806\u6808\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u5806\u6808\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    ES (extra segment)\uff1a\u9644\u52a0\u6570\u636e\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u653e\u9644\u52a0\u6bb5\u7684\u6bb5\u5730\u5740\u3002\u6709\u65f6\uff0c\u4e00\u4e2a\u6570\u636e\u6bb5\u4e0d\u591f\u7528\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u58f0\u660e\u4e00\u4e2a\u9644\u52a0\u6bb5\u6765\u5b58\u653e\u66f4\u591a\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u58f0\u660e 2 \u4e2a\u6570\u636e\u6bb5\uff0c\u5206\u522b\u7528 DS \u548c ES \u6307\u5411\u3002

    \u7a0b\u5e8f\u5f00\u59cb\u8fd0\u884c\u65f6\uff0cDOS \u4f1a\u628a ds \u548c es \u8d4b\u503c\u4e3a psp(program segment prefix) \u6bb5\u5730\u5740\u3002psp \u6bb5\u4f4d\u4e8e\u7a0b\u5e8f\u9996\u4e2a\u6bb5\u7684\u524d\u9762\uff0c\u957f\u5ea6\u4e3a 100h \u5b57\u8282\uff0c\u5176\u7528\u9014\u662f\u4fdd\u5b58\u5f53\u524d exe \u76f8\u5173\u7684\u4e00\u4e9b\u4fe1\u606f\uff0c\u5982 psp:80h \u5f00\u59cb\u5b58\u653e\u4e86 exe \u7684\u547d\u4ee4\u884c\u53c2\u6570\u3002

    \u95f4\u63a5\u5bfb\u5740\uff1a \u53ef\u4ee5\u2f64\u4f5c\u95f4\u63a5\u5bfb\u5740\u7684\u5bc4\u5b58\u5668\u53ea\u6709\u56db\u4e2a\uff1abx, bp, si, di [bx], [bp], [si], [di]\u662f\u6700\u7b80\u5355\u7684\u95f4\u63a5\u5bfb\u5740 [bx + si], [bp + si], [bx + di], [bp + di]\u6ce8\u610f\u524d\u2faf\u5fc5\u987b\u662fbx/bp\uff0c\u540e\u2faf\u5fc5\u987b\u662fdi/si [bx+2] [bp-2] [si+1] [di-1] [bx+si+2] [bx+di-2]

    [bp+si+1] [bp+di-1] tips\uff1a\u4e24\u4e2a\u5bc4\u5b58\u5668\u76f8\u52a0\u7684\u95f4\u63a5\u5bfb\u5740\u2f45\u5f0f\u4e2d, bx\u6216bp\u901a\u5e38\u2f64\u6765\u8868\u793a\u6570\u7ec4\u7684\u2fb8\u5730\u5740, \u2f7dsi\u6216di\u5219\u2f64\u6765\u8868\u793a\u4e0b \u6807\u3002

    \u7f3a\u7701\u6bb5\u5740\uff1a\u4e0d\u542bbp\u7684\u6e90\u64cd\u4f5c\u6570\u2f00\u822c\u90fd\u7701\u7565\u7684\u6bb5\u5730\u5740ds\uff0c\u542b\u6709bp\u7684\u6e90\u64cd\u4f5c\u6570\u7701\u7565\u4e86ss\uff0c\u2f7d\u8fd9\u4e2a\u9ed8\u8ba4\u7684\u6bb5\u5730\u5740\u662f \u53ef\u4ee5\u88ab\u6539\u53d8\u7684

    \u7528\u5806\u6808\u4f20\u9012\u53c2\u6570\u65f6\uff0c\u5982\u4f55\u7528[bp+]\u5b9e\u73b0\u5bf9\u53c2\u6570\u7684\u5f15\u7528\uff1f

    bp + \u591a\u5c11\u5c31\u662f\u6808\u91cc\u7684\u591a\u5c11

    \u738b\u723d\u300a\u6c47\u7f16\u8bed\u2f94\u300b\u7b2c\u56db\u7248 \u9644\u5f554:\u2f64\u6808\u4f20\u9012\u53c2\u6570

    difcube:\n    mov bp, sp\n    mov ax, [bp+4]  ;a\u7684\u503c\u9001\u5165ax\u4e2d\n    sub ax, [bp+6]  ;\u51cf\u6808\u4e2db\u7684\u503c\n    mov bp, ax\n    mul bp\n    mul bp\n    pop bp\n    ret 4\n
    "},{"location":"docs/1-cs/assembly-x86/#_16","title":"\u5176\u5b83\u7684\u7b14\u8bb0","text":""},{"location":"docs/1-cs/assembly-x86/#x86_1","title":"x86\uff1a","text":"

    Intel\u4ece16\u4f4d\u5fae\u5904\u7406\u56688086\u5f00\u59cb\u7684\u6574\u4e2aCPU\u82af\u7247\u7cfb\u5217\uff0c\u7cfb\u5217\u4e2d\u7684\u6bcf\u79cd\u578b\u53f7\u90fd\u4fdd\u6301\u4e0e\u4ee5\u524d\u7684\u5404\u79cd\u578b\u53f7\u517c\u5bb9\uff0c\u4e3b\u8981\u67098086\uff0c8088\uff0816\u4f4dCPU\uff09\uff0c80186\uff0c80286\uff08\u8fd9\u4e24\u4e2a\u662f\u8fc7\u6e21\u4ea7\u54c1\uff09\uff0c 80386\uff0c80486\u4ee5\u53ca\u4ee5\u540e\u5404\u79cd\u578b\u53f7\u7684Pentium\u82af\u7247\uff0832\u4f4dCPU\uff09\uff0c\u901a\u5e38\u6240\u8bf4\u7684x86\u90fd\u662f\u630732\u4f4dCPU

    80386: 32\u4f4d\u6c47\u7f16\u3002

    80836\u5bc4\u5b58\u5668

    \u901a\u7528\u5bc4\u5b58\u5668(EAX EBX ECX EDX,ESP,EBP,ESI,EDI)

    \u901a\u7528\u5bc4\u5b58\u5668\u4e0e8086\u7684\u5bc4\u5b58\u5668\u76f8\u6bd4,\u753116\u4f4d\u53d8\u4e3a\u4e8632\u4f4d

    ESP:\u6808\u9876

    EBP:\u6808\u5e95

    EAX\uff0cEBX\uff0cECX\uff0cEDX\u901a\u7528\u5bc4\u5b58\u5668

    EAX\uff1a\u7d2f\u52a0\u5668\uff08\u4e58\u6cd5\u7684\u65f6\u5019\u5b58\u4f4e\u4f4d\uff09

    EBX\uff1a\u57fa\u5740\uff08\uff3bEBX\uff0b100\uff28\uff3d\uff09

    ECX\uff1a\u8ba1\u6570\uff08\u5faa\u73af\u7684\u65f6\u5019\u8ba1\u6570\uff09

    EDX\uff1a\u6570\u636e\uff08\u9ed8\u8ba4EDX\uff0a10H\uff0b\uff0e\uff0e\uff0e\uff1b\u4e58\u6cd5\u7684\u65f6\u5019\u5b58\u9ad8\u4f4d\uff09

    ESI\uff0cEDI\uff1a\u53d8\u5740\u5bc4\u5b58\u5668

    ESI\uff1a\u6e90\u53d8\u5740\u5bc4\u5b58\u5668

    EDI\uff1a\u76ee\u7684\u53d8\u5740\u5bc4\u5b58\u5668\u3000\u4e0eEBX\u57fa\u5740\u642d\u914d\u4f7f\u7528

    "},{"location":"docs/1-cs/assembly-x86/#_17","title":"\u53c2\u8003\u6587\u732e","text":"

    asm_sum.doc

    xxjj\u7684\u300a\u6c47\u7f16\u8bed\u8a00\u8003\u8bd5\u603b\u7ed3\u300b https://www.yuque.com/xianyuxuan/coding/mkte6u

    [80386]80x86\u6c47\u7f16\u6307\u4ee4_CarlosX\u7684\u535a\u5ba2-CSDN\u535a\u5ba2_80386\u6307\u4ee4\u96c6

    80386 \u7b97\u672f\u8fd0\u7b97\u6307\u4ee4\uff0c\u903b\u8f91\u8fd0\u7b97\u6307\u4ee4\uff0c\u79fb\u4f4d\u6307\u4ee4 (\u4e09) _ttzyanswer\u7684\u535a\u5ba2-CSDN\u535a\u5ba2

    "},{"location":"docs/1-cs/c-libgraphics/","title":"C\u5927\u7a0b libgraphics \u6587\u6863 \u4f7f\u7528\u8bb0\u5f55","text":"

    :material-circle-edit-outline: \u7ea6 562 \u4e2a\u5b57 :fontawesome-solid-code: 162 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    \u26a0\ufe0f \u6ca1\u5199\u5b8c TODO

    "},{"location":"docs/1-cs/c-libgraphics/#_1","title":"\u5df2\u77e5\u95ee\u9898","text":""},{"location":"docs/1-cs/c-libgraphics/#devc","title":"DevC++\u56fe\u5f62\u7f16\u7a0b\u8fc7\u7a0b","text":""},{"location":"docs/1-cs/c-libgraphics/#_2","title":"\u51fd\u6570\u5e93","text":"

    graphics.h \u4ec5\u63d0\u4f9b\u4ee5\u4e0b\u5c11\u91cf\u753b\u56fe\u51fd\u6570\u63a5\u53e3

    InitGraphics();\nMovePen(x, y);\nDrawLine(dx, dy);\nDrawArc(r, start, sweep);\nGetWindowWidth();\nGetWindowHeight();\nGetCurrentX();\nGetCurrentY();\n

    \u6211\u4eec\u5c06\u5728\u4e0b\u9762\u4ecb\u7ecd\u8fd9\u4e9b\u63a5\u53e3\u7684\u7528\u6cd5\u3002

    "},{"location":"docs/1-cs/c-libgraphics/#_3","title":"\u521d\u59cb\u5316\u64cd\u4f5c","text":"

    \u5728main.c\u91cc\u9700\u8981\u8fdb\u884c\u5982\u4e0b\u521d\u59cb\u5316

    #include \"graphics.h\"\n#include \"extragraph.h\"\n#include \"imgui.h\"\nvoid Main()        // \u6ce8\u610f\u8fd9\u91cc\u9700\u8981\u4f7f\u7528\u5927\u5199Main\n{\nSet WindowTitle(\"Your Title\");\nInitGraphics();  // \u8c03\u7528\u4e86\u56fe\u5f62\u6a21\u5f0f\n}\n

    InitGraphics(); \u8fd9\u4e2a\u51fd\u6570\u4f1a\u6253\u5f00\u4e00\u4e2a\u7a7a\u7684\u56fe\u5f62\u7a97\u53e3\u3002

    "},{"location":"docs/1-cs/c-libgraphics/#_4","title":"\u7a97\u53e3","text":"

    \u4ee5\u4e0b\u56db\u4e2a\u51fd\u6570\u90fd\u4e0d\u9700\u8981\u4f20\u5165\u53c2\u6570\uff0c\u5206\u522b\u8fd4\u56de\u7a97\u53e3\u5bbd\u3001\u9ad8\uff0c\u5f53\u524dX\u3001Y\u5750\u6807\u3002

    GetWindowWidth();\nGetWindowHeight();\nGetCurrentX();\nGetCurrentY();\n
    "},{"location":"docs/1-cs/c-libgraphics/#_5","title":"\u597d\u7684\u7f16\u5199\u4e60\u60ef","text":"

    \u5e94\u8be5\u5148\u5b9a\u4e49\u4e00\u4e9b\u5e38\u91cf\uff0c\u7ed9\u8fd9\u4e9b\u5e38\u91cf\u53d6\u540d\u5b57

    #define HouseHeight 2.0\n#define HouseWidth 3.0\n#define AtticHeight 0.7\n#define DoorWidth 0.4\n#define DoorKnobRadius 0.03\n#define DoorKnobInset 0.07\n#define PaneHeight 0.25\n#define PaneWidth 0.2\n#define FirstFloorWindows 0.3\n#define SecondFloorWindows 1.25\n
    "},{"location":"docs/1-cs/c-libgraphics/#_6","title":"\u753b\u56fe\u5f62\u7684","text":""},{"location":"docs/1-cs/c-libgraphics/#movepen","title":"MovePen","text":"

    \u5c06\u7b14\u79fb\u52a8\u5230(x, y)\u8be5\u5750\u6807\u3002\u6ce8\u610f\u5f53\u753b\u56fe\u5f62\u65f6\uff0c\u540e\u9762\u51e0\u4e2a\u51fd\u6570\u7684\u76f8\u5bf9\u4f4d\u79fb\uff0c\u90fd\u662f\u76f8\u5bf9\u4e8e\u8fd9\u4e2a\u51fd\u6570\u8bbe\u7f6e\u7684\u7b14\u5750\u6807\u79fb\u52a8\u7684\u3002

    MovePen(double x, double y);\n
    "},{"location":"docs/1-cs/c-libgraphics/#drawline","title":"DrawLine","text":"

    \u5728\u753b\u7ebf\u4e4b\u524d\u4e00\u5b9a\u8981MovePen();

    DrawLine(double dx, double dy);\n

    \u753b\u7ebf\u7684\u65b9\u5411\uff1a

    \u6a2a\u5750\u6807\u6700\u5de6\u8fb9\u662f0\uff0c\u5411\u53f3\u589e\u5927

    \u7eb5\u5750\u6807\u6700\u4e0b\u9762\u662f0\uff0c\u5411\u4e0a\u589e\u5927

    \u53ef\u4ee5\u7406\u89e3\u4e3a\u6211\u4eec\u5728\u7b2c\u4e00\u8c61\u9650

    "},{"location":"docs/1-cs/c-libgraphics/#drawarc","title":"DrawArc","text":"

    \u5728\u753b\u5f27\u4e4b\u524d\u4e00\u5b9a\u8981MovePen();

    DrawArc(double r, double start, double sweep);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_7","title":"\u6211\u4eec\u5e94\u5f53\u628a\u753b\u77e9\u5f62\u5c01\u88c5\u6210\u4e00\u4e2a\u65b0\u7684\u51fd\u6570","text":"
    void DrawBox (double x, double y, double width, double height)\n{\nMovePen(x, y);\nDrawLine(0, height);\nDrawLine(width, 0);\nDrawLine(0, height);\nDrawLine(-width, 0);\n}\n
    void DrawCenteredBox(double x, double y, double width, double height)\n{\nDrawBox(w - width/2, y - height/2, width, height);\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_8","title":"\u753b\u5706\u7684\u51fd\u6570","text":"
    void DrawCenteredCircle(double x, double y, double r)\n{\nMovePen(x + r, y);\nDrawArc(r, 0, 360);\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_9","title":"\u6587\u5b57","text":"

    \u4ece\u5f53\u524d\u4f4d\u7f6e\u5f00\u59cb\u8f93\u51fa\u6587\u672c\u4e32

    DrawTextString(string);\n

    \u8fd9\u4e2a\u51fd\u6570\u7528\u4e8e\u83b7\u53d6\u67d0\u4e2a\u5b57\u7b26\u4e32\u957f\u5ea6

    double stringLen = TextStringWidth(string);
    "},{"location":"docs/1-cs/c-libgraphics/#_10","title":"\u67e5\u770b\u56de\u8c03\u51fd\u6570\u7c7b\u578b","text":"
    typedef void(* KeyboardEventCallback)(int key, int event);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_11","title":"\u5b9a\u65f6\u5668","text":""},{"location":"docs/1-cs/c-libgraphics/#_12","title":"\u65f6\u95f4\u56de\u8c03\u51fd\u6570","text":"
    registerTimerEvent(mytimer);  //\u83b7\u53d6\u7535\u8111\u65f6\u949f\u4fe1\u606f\u8fd4\u56de\u7ed9mytimer\nstartTimer(0, (int)(1000/speed));  // \u8981\u8ba8\u8bba\u4f20\u8fdb\u6765\u7684timer\u662f\u4ec0\u4e48\n
    "},{"location":"docs/1-cs/c-libgraphics/#_13","title":"\u5b9a\u65f6\u5668\u6d88\u606f\u56de\u8c03\u51fd\u6570","text":"
    void TimerEventProcess(int timerID);\n

    \u793a\u4f8b

    typedef enum\n{\nLabelTimer,\nBoxTimer,\n} MyTimer;\n
    void mytimer(int  timerID)\n{\nswitch (timerID)\n{\ncase LabelTimer:\nlabel_x += 0.5;\nif (label_x > 5.0) label_x = 1.0;\ndisplay();\nbreak;\ncase BoxTimer:\nbox_y += 0.5;\nif (box_y > 5.0) box_y = 1.0;\ndisplay();\nbreak;\nbreak;\n}\n}\n
    registerTimerEvent(mytimer);\nstartTimer(LabelTimer, 100);\nstartTimer(BoxTimer, 200);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_14","title":"\u9f20\u6807","text":""},{"location":"docs/1-cs/c-libgraphics/#_15","title":"\u9f20\u6807\u6d88\u606f\u56de\u8c03\u51fd\u6570","text":"
    void MouseEventProcess(int x, int y, int button, int event);\n

    x, y - \u4f4d\u7f6e\u5750\u6807

    button - \u6309\u4e0b\u7684\u662f\u54ea\u4e2a\u952e

    event - \u6309\u4e0b\uff0c\u677e\u5f00\uff0c\u79fb\u52a8\u7b49\u4e8b\u4ef6

    void myMouseEvent (int x, int y, int button, int event)\n{\nmouse_x = ScaleXInches(x);   // \u8fd9\u4e2a\u51fd\u6570\u5728extragraph\u5e93\u91cc\nmouse_y = ScaleYInches(y);\ndisplay();\n}\n

    \u9700\u8981\u5728Main()\u91cc\u6dfb\u52a0\u8fd9\u4e00\u884c

    registerMouseEvent(myMouseEvent);\n

    \u5728display()\u91cc

    void display()\n{\ndouble w = 1.0;\ndouble h = GetFontHeight() * 2;\n// \u6e05\u9664\u5c4f\u5e55\nDisplayClear();\n// draw a square\nSetPenColor(\"Red\");\ndrawLabel(label_x, label_y, \"Lable is Here\");\n//draw a rect/box to trace the mouse\n//drawRectangle(mouse_x, mouse_y, w, h, 0);\nSetPenColor(\"Blue\");\ndrawBox(mouse_x, mouse_y, w, h, 1, \"This box follows the mouse\", 'L', \"Red\");\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#linkedlist","title":"\u4f7f\u7528linkedlist\u5e93","text":"
    #include \"linkedlist.h\"\n

    \u521b\u5efa\u4e00\u4e2a linkedlist \u540d\u53eb g_polylines

    linkedlistADT g_polylines = NULL;\ng_polylines = NewLinkedList();\ndisplay();\n
    void display()\n{\nlinkedlistADT poly = NextNode(g_polylines, g_polylines);\nSetPenColor(\"Blue\");\nif (poly) {\nPoint * p = (Point*) NodeObj(g_polylines, poly);\ndouble lx = p->x;\ndouble ly = p->y;\nMovePen(lx, ly);\nwhile (poly = NextNode(g_polylines, poly))\n{\np = (Point*) NodeObj(g_polylines, poly);\nDrawLine(p->x - lx, p->y - ly);\nlx = p->x;\nly = p->y;\n}\n}\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#button","title":"\u4f7f\u7528button\u548c\u952e\u76d8","text":"

    \u8fd9\u6b21\u9700\u8981\u7528\u5230\u7684\u5e93

    #include <windows.h>\n#include <winuser.h>\n#include \"graphics.h\"\n#include \"extgraph.h\"\n#include \"imgui.h\"\n#include \"linkedlist.h\"\n
    "},{"location":"docs/1-cs/c-libgraphics/#_16","title":"\u5b57\u7b26\u8f93\u5165\u56de\u8c03\u51fd\u6570","text":"
    void charEventProcess(char c);\n

    c - \u8f93\u5165\u5b57\u7b26\u7684ASCII\u7801

    "},{"location":"docs/1-cs/c-libgraphics/#_17","title":"\u952e\u76d8\u56de\u8c03\u51fd\u6570","text":"
    void KeyboardEventProcess(int key, int event);\n

    key - \u54ea\u4e2a\u952e

    event - \u6309\u4e0b\u8fd8\u662f\u677e\u5f00

    \u793a\u4f8b

    \u5728Main()\u4e2d

    \n
    void myKeyboardEvent(int key, int event)\n{\nuiGetKeyboard(key, event); // needed for using simpleGUI\ndisplay();\nswitch (event)\n{\ncase KEY_UP:\nif (key == VK_F1)\ng_add_point = !g_add_point;\nbreak;\ndefault:\nbreak;\n}\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_18","title":"\u989c\u8272\u5e93","text":"

    \u81ea\u5e26\u7684\u989c\u8272\u5217\u8868

    char colorlist[100][100] = {\u201dBlack\u201d, \u201cDark Gray\u201d, \u201cGray\u201d, \u201cLight Gary\u201d, \u201cWhite\u201d, \u201cBrown\u201d, \u201cRed\u201d, \u201cOrange\u201d, \u201cYellow\u201d, \u201cGreen\u201d, \u201cBlue\u201d, \u201cViolet\u201d, \u201cMagenta\u201d, \u201cCyan\u201d};\nconst int colorNumber = 14;\n

    \u81ea\u5b9a\u4e49\u989c\u8272

    \u989c\u8272\u4f1a\u88ab\u52a0\u5165\u989c\u8272\u5e93\uff0cRGB\u7684\u53d6\u503c\u8303\u56f4\u90fd\u662f[0, 1]\u800c\u4e0d\u662f[0, 256)

    DefineColor(\"Color Name\", R, G, B);\n
    "},{"location":"docs/1-cs/c-libgraphics/#libgraphics","title":"libgraphics\u5176\u5b83\u5e38\u7528\u7684\u4e1c\u897f","text":""},{"location":"docs/1-cs/code-style/","title":"Pythons' Code Style Guide","text":"

    :material-circle-edit-outline: \u7ea6 517 \u4e2a\u5b57 :fontawesome-solid-code: 71 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/1-cs/code-style/#pr","title":"PR","text":""},{"location":"docs/1-cs/code-style/#first-prototypes-and-implementations-then","title":"First prototypes, and implementations then","text":""},{"location":"docs/1-cs/code-style/#every-pr-should-be-meaningful-an-integral-element","title":"Every PR should be meaningful (an integral element)","text":""},{"location":"docs/1-cs/code-style/#split-to-the-smallest-elements","title":"Split to the smallest elements","text":"

    \u2705 each PR can be described within one sentence.

    "},{"location":"docs/1-cs/code-style/#git-add-instead-of-git-add","title":"git add , instead of git add .","text":""},{"location":"docs/1-cs/code-style/#require-review-before-each-merging-by-setting-up-protecting-your-branch","title":"require review before each merging, by setting up \u2018protecting your branch\u2019","text":""},{"location":"docs/1-cs/code-style/#prs-title-same-as-git-commit-message","title":"PRs title - same as git commit message

    format [label] name + summary of change

    admitted labels: Git Commit Style Guide

    ","text":""},{"location":"docs/1-cs/code-style/#pr-message-same-as-git-commit-message","title":"PR message - same as git commit message","text":""},{"location":"docs/1-cs/code-style/#file-management","title":"File management","text":""},{"location":"docs/1-cs/code-style/#oop","title":"oop

    Encompass each function (except main) into a related class.

    ","text":""},{"location":"docs/1-cs/code-style/#write-prototypes-first","title":"write prototypes first","text":""},{"location":"docs/1-cs/code-style/#avoid-using-hyphen-or-underscore-in-file-naming-make-files-into-folders-instead","title":"avoid using hyphen or underscore in file naming, make files into folders instead.

    \u2705 Do models/models.py

    \u274c Don't models_main.py

    ","text":""},{"location":"docs/1-cs/code-style/#naming","title":"Naming","text":""},{"location":"docs/1-cs/code-style/#avoid-abbreviations-and-use-full-spellings","title":"avoid abbreviations and use full spellings

    \u2705 Do path_checkpoint.

    \u274c Don't path_ckpt.

    ","text":""},{"location":"docs/1-cs/code-style/#my-own-habit","title":"(my own habit:) ","text":""},{"location":"docs/1-cs/code-style/#classs-private-members-should-start-with-an-underscore-_-to-separate-with-the-input-parameters","title":"Class's private members should start with an underscore _ to separate with the input parameters.

    e.g., the correct private number name should be

    def __init__(self, foo):\n    self._foo = foo     # not recommended\n

    instead of 

    def __init__(self, foo):\n    self.foo = foo      # recommended\n

    And whenever an outer function requires a private member of a class, it is not recommended to directly use the private member from the class like

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\nfoo = Foo()\nfoo._bar                # not recommnded\n

    nor

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\n    @property\n    def get_bar(self):\n        return self._bar\n\nfoo = Foo()\nfoo.get_bar()\n

    instead, using a @property decorator is recommonded.

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\n    @property\n    def bar(self):\n        return self._bar\n\nfoo = Foo()\nfoo.bar\n
    ","text":""},{"location":"docs/1-cs/code-style/#spacing","title":"Spacing","text":"

    From top to down - In every comment: 1 space-line between each section, i.e., - Except the file top, no more than 2 space-line

    "},{"location":"docs/1-cs/code-style/#type-hints","title":"Type Hints","text":""},{"location":"docs/1-cs/code-style/#write-type-hints-no-need-to-write-types-in-the-comment","title":"write type hints, no need to write types in the comment

    \u2705 Do

    def foo(bar: int) -> str:\n    \"\"\"\n    Args:\n        bar: \n    Returns:\n        str: \n    \"\"\"\n    pass\n

    \u274c Don't

    def foo(bar: int) -> str:\n    \"\"\"\n    Args:\n        bar (int): \n    Returns:\n        str (str): \n    \"\"\"\n    pass\n
    ","text":""},{"location":"docs/1-cs/code-style/#try-to-use-the-typing-library","title":"try to use the typing library.

    Usual usage: when you want to indicat the element type of a Dict / a List / etc.

    from typing import Dict\n\ntyping.Dict[str, Union[int, float]]\n

    Supported types: - Dict[x, y] - Union[x, y, ...] -

    After Python 3.10, this feature is included as an internal feature, with all types written as lower cases.

    dict[str, int | float]\n

    But to preserve the extenability to lower versions, I believe the importing method would be better.

    ","text":""},{"location":"docs/1-cs/code-style/#comments","title":"Comments","text":""},{"location":"docs/1-cs/code-style/#where-should-comments-appear","title":"Where should comments appear? ","text":""},{"location":"docs/1-cs/code-style/#formats","title":"Formats ","text":""},{"location":"docs/1-cs/code-style/#file-docstring","title":"file docstring

    No space between the docstring and the imports.

    ","text":""},{"location":"docs/1-cs/code-style/#be-sure-to-make-every-doc-a-sentence","title":"Be sure to make every doc a sentence

    \u2705 Do # a comment.

    \u274c Don't # a comment..

    ","text":""},{"location":"docs/1-cs/code-style/#can-omit-the-but-keep-congruent","title":"Can omit 'the' but keep congruent

    \u2705 Do 

    # comment 1.\n# comment 2.\n# comment 3.\n

    \u274c Don't

    # comment 1.\n# the comment 2.\n# comment 3.\n
    ","text":""},{"location":"docs/1-cs/code-style/#imports","title":"Imports","text":""},{"location":"docs/1-cs/code-style/#order","title":"Order
    1. import all Python default libs, in alphabetical order (of the package name instead of the folder name), and add an empty line.
    2. import all 3rd party libs in alphabetical order, and add an empty line.
    3. import all libs defined in this project.

    One way to automatically sort the imports in VSCode (Don't sing an alphabet song every time you add an import): 1. Open the setting.json. 2. Add or change the following setting

    ```json\n\"editor.codeActionsOnSave\": {\n    \"source.organizeImports\": true,\n},\n```\n
    ","text":""},{"location":"docs/1-cs/code-style/#importing-names","title":"Importing Names

    \u2705 Do use import x, x.y to avoid the conflict of namespace, e.g.,

    import torch\nimport transformers\n\ntorch.nn.Module\ntransformers.Trainer\n

    \u274c Don't use from x import y.

    The only examptions are those well-established ones, e.g., from typing import Dict, List, Optional, Sequence, Union.

    ","text":""},{"location":"docs/1-cs/code-style/#references","title":"References","text":"

    This code style guide is an examplanation of the Google's Python Style Guide.

    "},{"location":"docs/1-cs/architecture/","title":"\u7d22\u5f15","text":"

    :material-circle-edit-outline: \u7ea6 318 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u6253\u7b97\u7a0d\u5fae\u5199\u4e00\u70b9\u662f\u56e0\u4e3a\u81ea\u5df1\u5b66\u4f53\u7cfb\u7684\u65f6\u5019\u6ca1\u627e\u5230\u7279\u522b\u5b8c\u6574\u7b14\u8bb0\u8d44\u6599 + \u6ca1\u4e0a\u8ba1\u7ec4\uff0c\u81ea\u5df1\u5b8c\u5168\u6ca1\u7406\u89e3\uff0c\u5355\u7eaf\u786c\u80cc\u901f\u6210\u7684\uff0c\u8bb0\u4e00\u4e0b\u81ea\u5df1\u901f\u6210\u770b\u4e86\u54ea\u4e9b\u4e1c\u897f

    \u5f53\u7136\u9996\u5148\u82b1\u4e86\u4e24\u4e2a\u4e0b\u5348\u8fc7\u4e86\u4e00\u904d\u9a6c\u5fb7\u8ba1\u7ec4\u7684\u667a\u4e91 + xyx\u8ba1\u7ec4\u7b14\u8bb0\uff0c\u8fb9\u5b66\u8fb9\u52a8\u7b14

    \u8fd8\u6709\u6284 A4 \u7684\u89c4\u5212\u8bf7\u89c1\u6211 github \u90a3\u4e2a ZJU \u8d44\u6e90\u4ed3\u5e93

    \u53c2\u8003\u8d44\u6599

    "},{"location":"docs/1-cs/architecture/chap2/","title":"chap2: Memory Hierachy Design","text":"

    :material-circle-edit-outline: \u7ea6 3017 \u4e2a\u5b57 :fontawesome-solid-code: 28 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap2/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap2/#cache","title":"cache \u57fa\u7840\u6982\u5ff5","text":"

    \u8fd9\u5757\u5e38\u8003\u5927\u9898\uff0c\u6bd4\u5982\u8ba1\u7b97\u5730\u5740\u957f\u5ea6\uff0c\u8ba1\u7b97 AMAT\uff0c\u8ba1\u7b97 miss \u6b21\u6570\u7b49\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#cache_1","title":"cache \u7684\u5206\u7c7b\u548c\u5730\u5740\u7684\u8ba1\u7b97\u65b9\u6cd5","text":"

    Warning

    \u8fd9\u4e2a\u8868\u8bb0\u4e0d\u6e05\u4e86\u6253\u7b97\u7b49\u4e0a\u8ba1\u7ec4\u518d\u8865\u3002

    \u7c7b\u522b \u89e3\u91ca \u6807\u8bb0\u9879\u7ed3\u6784 \u5730\u5740\u8ba1\u7b97 \u4f18\u70b9 \u7f3a\u70b9 direct-mapping \u76f4\u63a5\u6620\u5c04 fully associative \u5168\u5173\u8054 2^n-set associative 2^n\u8def\u7ec4\u5173\u8054 "},{"location":"docs/1-cs/architecture/chap2/#cache-write","title":"cache write \u7684\u5904\u7406\u65b9\u6cd5","text":"write \u7b56\u7565 \u89e3\u91ca \u7ecf\u5e38\u642d\u914d\u7684 write-miss \u7b56\u7565 \u89e3\u91ca write through \u6bcf\u6b21\u5199\u6570\u636e\u65f6\u65e2\u5199\u5728cache\u4e5f\u5199\u5728main memory\u3002\u597d\u5904\u662fcache\u548cmain memory\u603b\u662f\u4e00\u81f4\u7684\uff0c\u4f46\u662f\u5f88\u6162\u3002\u53ef\u4ee5\u901a\u8fc7\u5f15\u5165\u4e00\u4e2awrite buffer\u6765\u6539\u8fdb\u3002 write around\uff08\u4e5f\u53ebnon-allocate\uff09 \u8003\u8651\u5230\u65e2\u7136\u672c\u6765\u5c31\u8981\u53bb\u4e00\u6b21main memory\uff0c\u4e0d\u5982\u76f4\u63a5\u5199\u5728\u91cc\u9762\uff0c\u4e0d\u518d\u62ff\u5230cache\u91cc\u4e86\u3002 write back \u53ea\u5c06\u4fee\u6539\u540e\u7684\u5185\u5bb9\u653e\u5728cache\u91cc\uff0c\u8be5block\u8981\u88ab\u8986\u76d6\u7684\u65f6\u5019\u518d\u5199\u56de\u5185\u5b58\u3002\u8fd9\u79cd\u60c5\u51b5\u9700\u8981\u4e00\u4e2a\u989d\u5916\u7684dirty bit\u6765\u8bb0\u5f55\u8fd9\u4e2acache\u662f\u5426\u88ab\u66f4\u6539\u8fc7\uff0c\u4ece\u800c\u76f4\u5230\u88ab\u8986\u76d6\u524d\u662f\u5426\u9700\u8981\u88ab\u5199\u56de\u5185\u5b58\u3002 write allocate \u50cfread miss\u4e00\u6837\u5148\u628ablock\u62ff\u5230cache\u91cc\u518d\u5199\u5165"},{"location":"docs/1-cs/architecture/chap2/#cache-miss-3c","title":"cache miss \u7684\u79cd\u7c7b \uff08\u7b80\u79f0\u4e3a3C\uff09","text":"\u79cd\u7c7b \u89e3\u91ca compulsory miss \u51b7\u542f\u52a8\u5931\u914d\uff0c\u521a\u4e0a\u7535cache\u662f\u7a7a\u7684\uff0c\u6240\u4ee5\u4e0d\u8bba\u4ec0\u4e48\u8bbf\u95ee\u90fd\u8981miss\u4e00\u6b21\u3002cache\u8d8a\u5927compulsory miss\u8d8a\u591a\u3002 capacity miss cache\u5757\u7684\u5927\u5c0f\u4e0d\u6ee1\u8db3\u7a0b\u5e8f\u5c40\u90e8\u6027\u65f6\u53d1\u751f\u7684\u5931\u914d\uff0c\u79f0\u4e3a\u5bb9\u91cf\u5931\u914d\u3002cache\u5757\u5927\u5c0f\u589e\u5927\uff0c\u5bb9\u91cf\u5931\u914d\u7387\u51cf\u5c0f\uff0c\u4e0e\u5173\u8054\u5ea6\u65e0\u5173\u3002 conflict miss \u5728\u91c7\u7528\u7ec4\u5173\u8054\u548c\u76f4\u63a5\u6620\u50cf\u65b9\u5f0f\u7684cache\u4e2d\uff0c\u4e3b\u5b58\u7684\u5f88\u591a\u5757\u90fd\u6620\u5c04\u5230cache\u7684\u540c\u4e00\u5757\uff0c\u5982\u679c\u67d0\u5757\u672c\u6765\u5728cache\u4e2d\uff0c\u521a\u88ab\u66ff\u6362\u51fa\u53bb\uff0c\u53c8\u88ab\u8bbf\u95ee\u5230\u3002\u6709\u70b9\u50cf OS \u91cc\u9875\u66ff\u6362\u65f6\u8bb2\u5230\u7684\u201c\u6296\u52a8\u201d\u3002\u5173\u8054\u5ea6\u8d8a\u5927\uff0cConflict\u5931\u914d\u8d8a\u5c0f\u3002"},{"location":"docs/1-cs/architecture/chap2/#cache_2","title":"cache \u4f18\u5316\u65b9\u6cd5","text":"

    \u8fd9\u5757\u5e38\u8003\u9009\u62e9\u3002

    \u603b\u7ed3\u6027\u7684\u56fe

    \u63a5\u4e0b\u6765\u5177\u4f53\u8bb2\u89e3\u6bcf\u4e00\u79cd\u4f18\u5316\u65b9\u6cd5\u3002

    \u9996\u5148\u56db\u5927\u7c7b\u4f18\u5316\u7684\u601d\u8def\u662f\u5982\u4f55\u4ea7\u751f\u7684\uff1f\u6765\u81ea\u4e8e\u8861\u91cf\u5185\u5b58\u6027\u80fd\u7684\u516c\u5f0f\uff1a

    \\[ Average\\space Memory\\_access\\space Time\\space (AMAT) = Hit\\_time + Miss\\_rate \\times Miss\\_penalty \\]

    \u9996\u5148\u8fd9\u4e2a\u516c\u5f0f\u7684\u610f\u601d\u662f\uff0c\u5f53 CPU \u9700\u8981\u5185\u5b58\u8bbf\u95ee\u7684\u65f6\u5019\uff0c\u8bbf\u95ee\u65f6\u95f4\u7684\u8ba1\u7b97\u65b9\u6cd5\u662f\uff1a - \u5982\u679c\u5728 cache \u91cc\u627e\u5230\u4e86\uff0c\u5373\u53d1\u751f cache hit\uff0c\u90a3\u4e48\u9700\u8981\u7684\u65f6\u95f4\u53ea\u6709 cache \u7684\u8bbf\u95ee\u7528\u65f6\u5373hit_time\u3002 - \u5982\u679c\u5728 cache \u91cc\u6ca1\u627e\u5230\uff08\u6b64\u65f6\u5df2\u7ecf\u7528\u4e86\u4e00\u4e2a hit_time\uff0c\u8fd9\u5c31\u662f\u4e3a\u4ec0\u4e48 hit_time \u662f 100% \u8981\u7528\u6389\u7684\uff09\uff0c\u90a3\u4e48\u5c31\u9700\u8981\u53bb\u5185\u5b58\u91cc\u627e\uff0c\u53bb\u5185\u5b58\u91cc\u627e\u7684\u7528\u65f6\u662f\u8fd9\u79cd\u60c5\u51b5\u6240\u5360\u7684\u767e\u5206\u6bd4 miss_rate \u4e58\u4e0a\u53bb\u5185\u5b58\u91cc\u627e\u4e00\u6b21\u7684\u8017\u65f6 miss_penalty\u3002

    Note

    \u5f53\u7136\u9898\u76ee\u91cc\u8fd8\u53ef\u80fd\u4f1a\u8bf4 \"cache \u548c memory \u662f\u540c\u65f6\u8bbf\u95ee\u7684\"\uff0c\u610f\u601d\u5c31\u662f cache \u548c memory \u4e00\u8d77\u627e\uff0c\u5982\u679c cache \u91cc\u627e\u5230\u4e86\uff0c\u5c31\u628a memory \u8bbf\u95ee\u6390\u6389\uff0c\u8fd9\u6837\u5728 miss \u7684\u60c5\u51b5\u4e0b\u662f\u6bd4\u5148\u5728 cache \u91cc\u627e\u5b8c\u518d\u53bb memory \u627e\u66f4\u5feb\u7684\u3002\u8fd9\u6837\u7684\u6761\u4ef6\u4e0b\u8ba1\u7b97 AMAT \u5c31\u9700\u8981\u628a hit_time \u4e58\u4e0a\u4e00\u4e2a hit_rate\uff0c\u4e0d\u518d\u662f 100% \u7528\u6389\u4e86\u3002

    \u603b\u4e4b\uff0cAMAT \u7684\u8868\u8fbe\u5f0f\u7ed9\u6211\u4eec\u63d0\u4f9b\u4e86\u4e09\u79cd\u4f18\u5316\u7684\u5927\u65b9\u5411\uff0c\u5373 (1)\u964d\u4f4e hit_time (2)\u51cf\u5c0f miss_rate (3)\u51cf\u5c0f miss_penalty\u3002\u6b64\u5916\u8fd8\u6709\u4e00\u4e2a\u5927\u65b9\u5411\u53eb (4)\u505a\u5e76\u884c\u7684 cache\uff0c\u5728\u6709\u7684\u8001\u5e08\u7684 PPT \u91cc\u7b2c(4)\u9879\u597d\u50cf\u4f1a\u62c6\u51fa\u4e24\u7c7b\u6765\u8bb2\uff0c\u4e0d\u8fc7\u6211\u4eec\u8fd9\u91cc\u5c31\u6309\u603b\u5171\u56db\u79cd\u5927\u65b9\u5411\u6765\u5199\uff0c\u8ddf\u56fe\u4e00\u81f4\uff0c\u6bd4\u8f83\u8212\u670d\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#miss-penalty","title":"Miss Penalty","text":"

    Multilevel Caches

    \u7ecf\u5178\u7684\u5185\u5b58\u6a21\u578b\u662f

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [cache] - [\u5185\u5b58] - [\u5916\u5b58]\n

    \u8fd9\u4e2a\u65b9\u6cd5\u662f\u628a\u5b83\u53d8\u6210

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [\u5c0fcache] - [\u5927cache] - [\u5185\u5b58] - [\u5916\u5b58]\n
    \u6bd4\u5982\u5c0f cache \u6ca1\u627e\u5230\u7684\u5148\u4ece\u5927 cache \u627e\uff0c\u5927 cache \u6ca1\u627e\u5230\u7684\u518d\u53bb\u5185\u5b58\u627e\u3002\u6b64\u7c7b\u53ef\u80fd\u51fa AMAT \u7684\u8ba1\u7b97\u9898\uff0c\u628a\u5404\u79cd rate \u62ce\u6e05\u4ee5\u540e\u5c31\u50cf\u4f55\u8001\u5e08\u8bf4\u7684\u201c\u5f53\u6210\u521d\u4e2d\u7269\u7406\u9898\u505a\u5c31\u884c\u201d\u3002

    Early Resart & Critical Word 1st

    \u4f17\u6240\u5468\u77e5\uff08\u81f3\u5c11\u4f60\u73b0\u5728\u77e5\u9053\u4e86\uff09cache \u7684\u4e00\u4e2a block \u7ecf\u5e38\u662f\u542b\u6709\u591a\u4e2a word \u7684\uff08\u4f60\u53ef\u80fd\u4f1a\u604d\u7136\u5927\u609f\u6709\u4e9b\u9898\u76ee\u91cc\u8bf4\u7684\u201ccache \u6309 word \u7f16\u5740\u201d\u662f\u4ec0\u4e48\u610f\u601d\uff09\uff0c\u800c block \u5f80\u5f80\u662f\u5927\u4e8e cache \u548c\u5185\u5b58\u4e4b\u95f4\u7684\u6570\u636e\u7ebf\u4f4d\u5bbd\u7684\uff0c\u4e5f\u5c31\u662f\u8bf4\u60f3\u8981\u66ff\u6362\u4e00\u4e2a block\uff0c\u9700\u8981\u5728 cache \u548c\u5185\u5b58\u4e4b\u95f4\u4f20\u9001\u597d\u51e0\u8d9f\u624d\u80fd\u628a\u4e00\u4e2a block \u66ff\u6362\u5b8c\u3002

    \u4f46\u662f miss \u53d1\u751f\u65f6 CPU \u9700\u8981\u7684\u53ef\u80fd\u53ea\u6709\u4e00\u4e2a word\uff0c\u90a3\u4e48\u53ef\u4ee5\u5148\u628a CPU \u9700\u8981\u7684\u8fd9\u4e2a word \u5199\u56de\u6765\uff0c\u8ba9 CPU \u5148\u7ee7\u7eed\u8dd1\u8d77\u6765\uff0c\u5728 CPU \u7ee7\u7eed\u8dd1\u7684\u540c\u65f6\u518d\u628a\u5269\u4e0b\u7684 word \u5199\u8fdb cache\u3002

    Priority to Read Miss

    \u5728\u4f7f\u7528 write buffer \u7684\u60c5\u51b5\u4e0b\uff0c\u5982\u679c write \u7684\u6570\u636e\u5f88\u5feb\u5c31\u8981 read\uff0c\u53ef\u4ee5\u5148\u4e0d\u5c06 buffer \u7684\u6570\u636e\u5199\u8fdb\u5185\u5b58\uff0c\u800c\u662f\u7b49\u5230read\u7684\u65f6\u5019\u76f4\u63a5\u4ecebuffer\u91cc\u8bfb\uff0c\u8bfb\u591a\u6b21\u4e4b\u540e\u518d\u4e00\u6b21\u4ecebuffer\u91cc\u5199\u5185\u5b58\u3002

    \u5176\u4e2d\uff0cwrite buffer \u662f\u4e00\u4e2a\u53ef\u4ee5\u8bbe\u5728 cache \u548c\u5185\u5b58\u4e4b\u95f4\u7684\u7ed3\u6784\uff0c\u610f\u601d\u662f\uff0c\u5047\u8bbe\u5185\u5b58\u53ea\u6709\u4e00\u4e2a\u8bfb\u5199\u7aef\u53e3\uff0c\u5199\u5165\u5185\u5b58\u975e\u5e38\u6162\uff0c\u90a3\u4e48 cache \u53ef\u4ee5\u5c06\u9700\u8981\u5199\u5230\u5185\u5b58\u7684\u4e1c\u897f\u5148\u642c\u5230 write buffer \u91cc\uff0c\u7136\u540e cache \u5148\u8dd1\u7740\uff0c\u5185\u5b58\u53bb\u6162\u6162\u5199\u5165\u3002

    Merging Write Buffer

    \u540c\u6837\u662f\u4f7f\u7528 write buffer \u7684\u60c5\u51b5\u3002merging write buffer \u5c31\u662f\u5c06\u5728\u591a\u884c\u53ef\u4ee5\u4e00\u6b21\u5199\u56de\u7684\u5185\u5bb9\u5408\u5e76\u5230\u4e00\u884c\uff0c\u4ee5\u53ef\u4ee5\u4e00\u6b21\u5199\u56de\u3002write buffer \u7684\u5185\u5bb9\u662f\u6309 byte \u7f16\u5740\u7684\uff0c\u4f46\u5185\u5b58\u6570\u636e\u7ebf\u4f4d\u5bbd\u4e00\u822c\u5927\u4e8e byte\uff0c\u6bd4\u5982\u4e00\u6b21\u53ef\u4ee5\u5199\u56de\u4e00\u6574\u4e2a word\uff0c\u90a3\u4e48\u5047\u5982 write buffer \u91cc\u73b0\u5728\u6709\u56db\u884c mem[200], mem[400], mem[208], mem[408]\uff0c\u5199\u56de\u5185\u5b58\u5c31\u9700\u8981\u56db\u6b21\u3002\u4f46\u662f\u5982\u679c\u6211\u4eec\u628a\u5728\u540c\u4e00\u4e2a word \u91cc\u7684 byte \u5408\u5e76\u4e00\u4e0b\uff0c\u53d8\u6210 mem[200] mem[208] \u548c mem[400] mem[408] \u4e24\u884c\uff0c\u4e24\u6b21\u5199\u56de\uff0c\u5c31\u4f1a\u53d8\u5feb\u3002

    Victim Caches

    \u662f\u4e00\u79cd\u51cf\u5c11 conflict miss \u7684\u65b9\u6cd5\uff0c\u5373\u66ff\u6362\u51fa\u53bb\u7684\u9875\u5148\u653e\u8fdb\u8fd9\u4e2a victim cache \u7ed3\u6784\u3002victim cache \u4e0e cache \u662f\u5168\u76f8\u5173\u7684\uff0c\u6709\u70b9\u50cf\u4e00\u4e2a\u4e8c\u7ea7 cache\uff0c\u662f\u4e00\u4e2a\u6bd4\u4e00\u7ea7 cache \u6162\u7684 cache\u3002\u8fd9\u6837\u5982\u679c\u53d1\u751f conflict miss\uff0c\u4ece\u8fd9\u4e2a victim cache \u91cc\u53d6\u6570\u636e\u6bd4\u4ece\u5185\u5b58\u91cc\u53d6\u66f4\u5feb\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#miss-rate","title":"Miss Rate","text":"

    \u8fd9\u4e00\u680f\u7684\u524d\u4e09\u4e2a\u65b9\u6cd5\u90fd\u4e0d\u662f\u5f88\u806a\u660e\uff0c\u672c\u8d28\u4e0a\u662f\u5728 cache \u7684\u4e09\u79cd\u8bbe\u8ba1\u65b9\u6cd5\u4e2d\u53bb\u6743\u8861\uff0c\u800c\u6211\u4eec\u77e5\u9053 cache \u7684\u4e09\u79cd miss \u8fd8\u662f\u6b64\u6d88\u5f7c\u957f\u7684\uff0c\u54ea\u4e00\u79cd\u8bbe\u8ba1\u65b9\u6cd5\u90fd\u4e0d\u80fd\u5b8c\u7f8e\u89e3\u51b3\u3002\u4e0d\u8fc7\u6574\u4f53\u800c\u8a00\uff0cfrom \u738b\u9053\u8ba1\u7ec4\uff0c\u4f7f\u7528\u5408\u9002\u7684 2^n \u8def\u7ec4\u5173\u8054\u65f6\uff0c\u6700\u597d\u7684\u60c5\u51b5\u80fd\u591f\u51e0\u4e4e\u517c\u5177\u76f4\u63a5\u6620\u5c04\u7684\u6548\u7387\u548c\u5168\u5173\u8054\u7684\u547d\u4e2d\u7387\u3002

    Larger Block Size

    \u628a cache \u7684\u6bcf\u4e2a\u5757\u8bbe\u8ba1\u5f97\u66f4\u5927\uff0c\u8fd9\u6837\u6bcf\u4e2a\u5757\u5b58\u5f97\u4e1c\u897f\u591a\u4e86\uff0c\u5f53\u7136 miss_rate \u5c31\u4e0b\u964d\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0cmiss_penalty \u4e0a\u5347\u4e86\uff0c\u56e0\u4e3a\u5199\u8d77\u6765\u53d8\u6162\u4e86\u3002

    Larger Cache Size

    \u628a cache \u7684\u5757\u6570\u589e\u591a\uff0c\u8fd9\u6837\u5b58\u5f97\u4e1c\u897f\u4e5f\u591a\u4e86\uff0cmiss_rate \u5c31\u4e5f\u4e0b\u964d\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0c\u51b7\u542f\u52a8 compulsory miss \u4e0a\u5347\u4e86\uff1b\u5982\u679c\u4e0d\u662f\u76f4\u63a5\u6620\u5c04\uff0c\u67e5\u627e\u65f6\u95f4\u4e5f\u4e0a\u5347\u4e86\u3002

    Higher Associativity

    \u63d0\u5347\u7ec4\u5173\u8054\u6570\uff0c\u8fd9\u6837\u51cf\u5c11 cache \u91cc\u9762\u7684\u4e1c\u897f\u88ab\u66ff\u6362\u51fa\u53bb\u7684\u6982\u7387\uff0c\u51cf\u5c11 conflict miss\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0c\u67e5\u627e\u65f6\u95f4\u589e\u52a0\u3002

    Way-predicting Cache

    \u5728\u7ec4\u5173\u8054\u8bbe\u8ba1\u4e2d\uff0c\u4f7f cache \u5177\u6709\u9884\u6d4b\u9700\u8981\u67e5\u627e\u7684 tag \u7684\u80fd\u529b\u3002\u56e0\u4e3a\u53bb\u67e5\u9700\u8981\u7684\u6570\u636e\u5728\u7ec4\u91cc\u54ea\u4e2a tag \u6bd4\u8f83\u6162\uff0c\u6240\u4ee5\u5148\u731c\u4e00\u4e2a tag \u5728 cache \u91cc\u627e\u7740\uff0c\u7b49 tag \u51c6\u5907\u597d\u540e\u5982\u679c\u731c\u5bf9\u4e86\uff0c\u90a3\u4e48\u8282\u7ea6\u4e86\u65f6\u95f4\uff0c\u5c31\u53ef\u4ee5\u76f4\u63a5 hit\u3002

    Pseudo-associative Caches

    \u65e2\u662f\u76f4\u63a5\u6620\u5c04\u53c8\u662f\u7ec4\u5173\u8054\u6620\u5c04\u7684 cache\u3002\u9996\u5148\u628a cache \u5f53\u4f5c\u4e00\u4e2a\u76f4\u63a5\u6620\u5c04 cache\uff0c\u7b2c\u4e00\u6b21\u67e5\u7684\u65f6\u5019\u5c31\u8fd9\u4e48\u67e5\uff0c\u6700\u5feb\u3002\u4f46\u662f\u8fd9\u79cd cache \u53c8\u540c\u65f6\u662f\u4e00\u4e2a\u7ec4\u5173\u8054\u6620\u5c04\uff0c\u5728 cache \u5757\u4e2d\u653e\u4e00\u4e2a\u989d\u5916\u7684\u6807\u5fd7\u8868\u793a\u4e0e\u4e4b\u5173\u8054\u7684\u5176\u5b83\u5757\uff0c\u5982\u679c miss \u4e86\u518d\u53bb\u67e5\u8fd9\u4e9b\u5757\u3002\u8fd9\u6837\u6709\u4e00\u4e2a\u5c0f\u7684 hit_time \u548c2^n - 1\u4e2a\u5927\u7684 pseudo_hit_time\uff0c\u4f46\u662f\u5e73\u5747\u6765\u8bf4 miss_rate \u6bd4\u76f4\u63a5\u6620\u5c04\u5c0f\uff0chit_time \u6bd4\u7ec4\u5173\u8054\u6620\u5c04\u5c0f\u3002

    Compiler Techniques Reduce Cache Misses

    \u7528\u8f6f\u4ef6\u65b9\u6cd5\uff0c\u4f18\u5316\u4ee3\u7801\u3002\u8fd9\u91cc\u6709\u56db\u4e2a\u4f8b\u7a0b\uff0c\u5206\u522b\u53eb Merging Arrays, Loop Interchange, Blocking, \u548c Loop Merging\u3002\u7b80\u5355\u7684\u76f4\u63a5\u7528\u6587\u5b57\u63cf\u8ff0\u4e86\u3002

    Merging Arrays

    \u6bd4\u5982\u6211\u4eec\u9700\u8981\u8bbf\u95ee\u7684\u662fa[100], b[100], \u5728\u540c\u4e00\u4e2a\u5faa\u73af\u91cc\u8fde\u7eed\u8bbf\u95eea[i] b[i]\u5373\u4e0b\u6807\u76f8\u540c\u7684\u9879\uff0ccache\u5982\u679c\u4e00\u6b21\u6027\u653e\u4e0d\u4e0b\u4e24\u4e2a\u6570\u7ec4\uff0c\u5c31\u4f1a\u4e24\u4e2a\u6570\u7ec4\u4ea4\u66ff\u4ece\u5185\u5b58\u91cc\u53d6\u51fa\u6765\u653e\u5230cache\u91cc\u3002\u8fd9\u65f6\u5019\u53ef\u4ee5\u8bbe\u8ba1\u6210\u4e00\u4e2a\u7ed3\u6784\u4f53\u6570\u7ec4struct ab { a[100], b[100] }\uff0c\u8fd9\u6837 cache \u53ef\u4ee5\u628a a \u548c b \u76f8\u90bb\u5730\u62ff\u8fdb\u6765\u3002\u51cf\u5c11miss\u3002

    Loop Interchange

    e.g.

    /* Before: \u5916\u884c\u5185\u5217\uff0c\u4e00\u884c\u53ef\u4ee5\u4e00\u6b21\u88ab\u653e\u8fdb\u5185\u5b58 */\nfor (k = 0; k < 100; k = k+1)\nfor (j = 0; j < 100; j = j+1)\nfor (i = 0; i < 5000; i = i+1)\nM[i][j] = 2 * M[i][j];\n/* After: \u5916\u5217\u5185\u884c */\nfor (k = 0; k < 100; k = k+1)\nfor (i = 0; i < 5000; i = i+1)\nfor (j = 0; j < 100; j = j+1)\nM[i][j] = 2 * M[i][j];\n

    \u4fee\u6539\u540e\u7684cache\u547d\u4e2d\u7387\u53d8\u9ad8\u4e86\uff0c\u56e0\u4e3a\u4ea4\u6362\u540e\u5bf9\u5185\u5b58\u7684\u8bbf\u95ee\u662f\u8fde\u7eed\u7684\u3002\u4e00\u822c\u662f\u884c\u5bf9\u9f50\u7684\uff0c\u6700\u4f4e\u7ef4\u662f\u76f8\u90bb\u7684\u3002

    Blocking

    \u9002\u5f53\u62c6\u5206\u8fd0\u7b97\uff0c\u4ee5\u914d\u5408cache\u5927\u5c0f\u3002e.g. \u77e9\u9635\u76f8\u4e58\u4f8b\u5b50\u3002

    /* Before */\nfor (i = 0; i < N: i += 1)\nfor (j = 0; j < N; j += 1) {\nr = 0;      for (k = 0; k < N; k +=1 )\nr = r + y[i][k] * z[k][j];  }\n/* After */\nfor (jj = 0 ; jj < N; jj = jj+B)\nfor (kk = 0; kk < N; kk = kk +B) {\n// ...\u8bb0\u4e0d\u6e05\u4e86\nfor (ii = 0; ii < B; ii ++) {\n// \u603b\u4e4b\u8fd9\u4e2a\u5185\u5c42\u5faa\u73af\u53ea\u5904\u7406\u4e00\u4e2a B * B \u7684 block\uff0c\u5176\u4e2d block \u662f cache \u80fd\u653e\u4e0b\u7684\u5927\u5c0f\n}\n}\n
    \u90a3\u4e48\u4f18\u5316\u524d cache \u9700\u8981\u66ff\u6362\u66f4\u591a\u6b21\uff0c\u56e0\u4e3a\u4e0d\u8bba\u662f\u884c\u5faa\u73af\u8fd8\u662f\u5217\u5faa\u73af\uff0c\u8d85\u8fc7 B \u4e4b\u540e cache \u90fd\u8981\u91cd\u65b0\u5199\u4e00\u904d\u3002\u7136\u540e\u4e0b\u6b21\u5199\u5230\u8fd9\u4e2a block \u65f6\u518d\u6362\u8fdb\u6765\u4e00\u6b21\u3002

    \u4f18\u5316\u540e\u6bcf\u6b21\u5bf9\u6bcf\u4e00\u4e2a block \u4e00\u6b21\u6027\u5b8c\u6210\u64cd\u4f5c\u3002

    Loop Merging

    \u6bd4\u5982\u6709\u4e24\u4e2a\u5faa\u73af\u7684\u5faa\u73af\u8d77\u6b62\u6761\u4ef6\u4e00\u6837\uff0c\u90a3\u4e48\u5c31\u4e0d\u8981\u5f00\u4e24\u4e2a\u5faa\u73af\u4e86\uff0c\u5408\u5e76\u5230\u4e00\u4e2a\u5faa\u73af\u91cc\u5b8c\u6210\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#parallelism","title":"Parallelism","text":"

    Non-blocking Caches

    cache miss\u65f6, \u7b49\u5f85\u5185\u5b58\u5199\u56de\u65f6\u7ee7\u7eed\u505a\u522b\u7684\u6ca1\u6709\u51b2\u7a81\u7684\u4e8b\u60c5\uff0c\u4e0d\u5fc5\u8981\u8ba9\u6240\u6709\u7684\u8d44\u6e90\u90fd\u7b49\u5f85\u5185\u5b58\u3002\u53ef\u4ee5\u8ba9\u522b\u7684\u5757\u5148\u5b8c\u6210\u522b\u7684\u6307\u4ee4\u7684\u9700\u6c42\u3002\u6bd4\u5982\u5728\u5904\u7406write miss\u7684\u65f6\u5019\uff0c\u5141\u8bb8\u5904\u7406read hit\u3002

    \u4e3b\u8981\u7528\u4e8eout of order\uff08\u4e71\u5e8f\uff09\u7684\u5904\u7406\u5668\u4e0a\u3002

    ppt \u7ed9\u7684\u5b9a\u4e49\u662f\uff1aallows cache to continues to supply hits while processing read misses (hit under miss, hit under multiple miss)

    Hardware Prefetching of Instr/Data

    \u53ef\u4ee5\u7531\u786c\u4ef6\u63a7\u5236\u6570\u636e\u9884\u53d6\uff0c\u4e00\u79cd\u7c7b\u4f3c branch-prediction \u7684\u505a\u6cd5\u3002\u9884\u6d4b\u5e76\u63d0\u524d\u53d6\u51fa\u53ef\u80fd\u9700\u8981\u7528\u5230\u7684\u6570\u636e\u653e\u5230cache\u91cc\u3002

    \u4f7f\u7528prefetching\u7684\u524d\u63d0\u662f\u6307\u4ee4\u662f\u5e76\u884c\u7684\uff0ccache \u4e5f\u662f non-blocking \u7684\u3002

    Compiler Controlled Prefetching

    \u4e0a\u9762\u4e00\u6761\u9884\u53d6\u65b9\u6cd5\uff0c\u4e5f\u53ef\u4ee5\u7531\u7a0b\u5e8f\u5458\u548c\u7f16\u8bd1\u5668\u624b\u52a8\u6307\u5b9a\u54ea\u4e9b\u5185\u5bb9\u5e94\u8be5\u88ab\u653e\u5230cache\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#hit-time","title":"Hit Time","text":"

    Small & Simple Caches

    \u6bd4\u5982\u5c31\u9488\u5bf9 cache \u672c\u8eab\uff0c\u51cf\u5c0f cache \u7684\u590d\u6742\u5ea6\u4ee5\u51cf\u5c0f\u7ec4\u5408\u903b\u8f91\u7684\u5ef6\u8fdf\u3002\u5f53\u7136\u7531\u4e8e\u6211\u4eec\u4e4b\u524d\u8ba8\u8bba\u8fc7\u7684 cache \u4e09\u4e2a\u6307\u6807\u7684\u76f8\u4e92\u5236\u7ea6\uff0c\u662f\u53ef\u80fd\u4f1a\u5bfc\u81f4\u5176\u5b83\u4e24\u4e2a\u6307\u6807\u53d8\u4e0d\u597d\u7684\u3002

    Avoiding Address Translation

    \u8fd9\u91cc\u9700\u8981\u5206\u522b\u56de\u5fc6\u4e00\u4e0b cache \u6807\u8bb0\u4f4d\u7684\u7ed3\u6784\u548c OS \u91cc\u7684\u9875\u8868\u9879\u3002\u4e00\u822c\u672c\u8bfe\u7a0b\u4e2d\u4f7f\u7528\u7684 cache \u8bbe\u8ba1\u89c4\u5219\u90fd\u662f \"physically tagged, virtually indexed\"(PTVI)\uff0c\u610f\u601d\u662f\uff0c\u7528\u4e8e\u67e5\u627e cache block \u7684 tag \u6574\u4e2a\u5168\u90fd\u5728 page offset \u91cc\uff0c\u8fd9\u5757 offset \u5b57\u6bb5\u5bf9\u4e8e\u865a\u62df\u5730\u5740\u548c\u7269\u7406\u5730\u5740\u6765\u8bf4\u662f\u5b8c\u5168\u4e00\u6837\u7684\uff0c\u53ea\u6709 page number \u9700\u8981\u9001\u8fdb tlb \u53bb\u5bfb\u627e\u7269\u7406\u5e27\u53f7\u3002\u5982\u56fe\u3002

    \u5982\u679c\u4e4b\u524d\u7684\u505a\u6cd5\u662f cache \u7b49\u5230\u7269\u7406\u5e27\u53f7\u627e\u51fa\u6765\u3001\u5730\u5740\u7ffb\u8bd1\u5b8c\u518d\u53bb\u67e5\u627e\uff0c\u5c31\u592a\u6162\u4e86\u3002\u65e2\u7136 tag \u4e0d\u7528\u7b49\u5230\u5730\u5740\u7ffb\u8bd1\u5c31\u80fd\u62ff\u5230\uff0c\u53ef\u4ee5\u4f7f\u5730\u5740\u7ffb\u8bd1\u548c cache \u67e5\u627e\u540c\u65f6\u8fdb\u884c\u3002

    Pipelined Cache Access

    \u56e0\u4e3a cache management unit \u7684\u64cd\u4f5c\u5206\u4e3a\u597d\u591a\u6b65\uff0c\u53ef\u4ee5\u628a\u6bcf\u6b65\u53bb\u50cf\u6d41\u6c34\u7ebf\u4e00\u6837\u5e76\u884c\u3002\u7f3a\u70b9\u662f\u4f1a\u589e\u52a0\u7cfb\u7edf\u5f00\u9500\uff0c\u5bfc\u81f4 hit_time \u589e\u52a0\uff0c\u4f46\u662f\u597d\u5904\u662f\u524d\u9762\u7684\u6307\u4ee4 miss \u65f6\uff0c\u4e0b\u4e00\u6761\u6307\u4ee4\u53ef\u4ee5\u5e76\u884c\u3002

    Multi-banked Cache

    \u5c06\u591a\u8def\u7ec4\u5173\u8054\u7684\u6bcf\u4e00\u8def\u7684\u67e5\u627e\u5e76\u884c\u3002

    ppt \u7ed9\u7684\u5b9a\u4e49\u662f\uff1acache is divided into independent banks that can support simultateous accesses like interleaved memory banks.

    Trace Cache

    \u6838\u5fc3\u903b\u8f91\u662f\u7f13\u5b58\u903b\u8f91\u4e0a\u7684\u6307\u4ee4\u6d41\uff0c\u800c\u4e0d\u662f\u7f13\u5b58\u7269\u7406\u5730\u5740\u7684\u6307\u4ee4\u6d41\uff0c\u4ece\u800c\u52a0\u5feb\u6307\u4ee4\u7684\u9884\u53d6\u3002\u6bd4\u5982\u5206\u652f\u6307\u4ee4\u4e2d\u4e0d\u53bb\u9884\u6d4b\u91cc cache \u4e0d\u4f1a\u547d\u4e2d\u7684\u5206\u652f\uff0c\u8fd9\u6837\u8282\u7701\u4e86 cache \u7a7a\u95f4\uff0c\u4e5f\u8ba9\u76f8\u90bb\u7684\u6307\u4ee4\u5728 cache \u4e2d\u4e5f\u76f8\u90bb\u3002\u6211\u7684\u7406\u89e3\u5b83\u7684\u610f\u601d\u662f\u628a prediction \u7684\u529f\u80fd\u9001\u7ed9\u4e86 cache\uff0c\u5982\u679c\u5206\u652f\u9884\u6d4b\u9884\u6d4b\u5230\u4e86\u67d0\u4e2a\u8df3\u8f6c\u6307\u4ee4\u4f1a\u53d1\u751f\uff0c\u90a3\u4e48 cache \u5c31\u53bb\u9884\u53d6\u53d1\u751f\u7684\u5206\u652f\u540e\u9762\u7684\u6570\u636e\u3002

    "},{"location":"docs/1-cs/architecture/chap3/","title":"chap3: Instruction-level Parallelism (ILP)","text":"

    :material-circle-edit-outline: \u7ea6 1058 \u4e2a\u5b57 :fontawesome-solid-code: 9 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap3/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap3/#ilp","title":"ILP \u57fa\u7840\u6982\u5ff5","text":"

    Note

    \u662f\u5199\u5f97\u7b80\u5355\u70b9\u4e86\u54c8\u3002\u5199\u4e0d\u52a8\u4e86\u3002\u8981\u4e0d\u5927\u5bb6\u770b\u8ba1\u7ec4\u738b\u9053\u597d\u4e86\u3002

    \u4e09\u79cd\u7ade\u4e89

    \u6d41\u6c34\u7ebf\u7c7b\u578b

    \u770b\u7684\u65f6\u5019\u6ce8\u610f\u603b\u7ed3\u4e00\u4e0b\u6bcf\u4e00\u79cd\u7684 CPI \u662f\u5927\u4e8e\u7b49\u4e8e\u8fd8\u662f\u5c0f\u4e8e 1\u3002\u6211\u603b\u7ed3\u4e0d\u51fa\u6765\u4e86\u3002

    "},{"location":"docs/1-cs/architecture/chap3/#ilp_1","title":"ILP \u5728\u4f53\u7cfb\u91cc\u5b66\u7684\u4e09\u79cd\u7b97\u6cd5","text":"

    Note

    \u672c\u6765\u8fd9\u5757\u8be5\u5199\u7684\u4f46\u662f\u6211\u5199\u4e0d\u52a8\u4e86

    \u76f4\u63a5\u53bb bing \u641c\u7d22 (1)Scoreboard, (2)Tomasulo, (3)Tomasulo w speculation, \u53bb\u627e\u4e00\u4e2a\u5357\u5927\u540c\u5b66\u5199\u7684\u77e5\u4e4e\u5e16\u5b50\uff0c\u6211\u662f\u770b\u8fd9\u5957\u5e16\u5b50\u770b\u61c2\u7684\u3002\u8fd8\u6709 lab \u91cc\u8fd9\u5757\u7684\u5b9e\u9a8c\u4e5f\u80fd\u5e2e\u52a9\u7406\u89e3\u3002

    \u8bf7\u518d\u7ed3\u5408\u8fd9\u5f20\u56fe\u8bb0\u5fc6\u4e00\u4e0b\uff1a

    \u8fd8\u6709\u4e00\u4e2a\u4e0a\u8ff0\u8d44\u6599\u4f3c\u4e4e\u6ca1\u8bb2\u5230\u7684\u70b9\uff0c\u5173\u4e8e ISSUE \u65f6\u673a\uff0c\u6211\u8bb0\u5f97\u662f - Scoreboard: \u9700\u8981\u7684 Function Unit \u4e3a\u7a7a\uff0c\u4e14\u9700\u8981\u5199\u7684 Reg State \u6ca1\u6709\u522b\u7684\u6307\u4ee4\u8fd8\u51c6\u5907\u5199\uff08\u907f\u514d WAW\uff09\u65f6\u3002 - Tomasulo: Reservation Station \u6709\u7a7a\u65f6\u3002 - Tomasulo w ROB (\u5373 w speculation): Reservation Station \u548c ROB \u90fd\u7a7a\u65f6\u3002

    Warning

    \u4f46\u662f\u4e0a\u8ff0 Tomasulo w ROB \u4f3c\u4e4e\u8ddf\u6211\u8003\u7684\u4e00\u4e2a\u671f\u672b\u9898\u4e0d\u517c\u5bb9\uff0c\u4e0d\u77e5\u9053\uff0c\u7b49\u540e\u4eba\u6765\u4e3a\u6211\u6307\u51fa

    "},{"location":"docs/1-cs/architecture/chap3/#branch-prediction","title":"Branch prediction","text":"

    \u56de\u5fc6 control hazard\uff0c\u6d41\u6c34\u7ebf CPU \u9047\u5230\u8df3\u8f6c\u8bed\u53e5\u5982\u679c\u5224\u65ad\u6761\u4ef6\u8fd8\u6ca1\u5c31\u7eea\uff0c\u5c31\u9700\u8981\u7b49\u64cd\u4f5c\u6570\u624d\u80fd\u7ee7\u7eed\u5f80\u4e0b\u8d70\u3002\u6211\u4eec\u60f3\u8ba9 CPU \u968f\u4fbf\u5148\u731c\u4e00\u4e2a\u5f80\u4e0b\u8d70\u7740\uff0c\u5982\u679c\u7b49\u64cd\u4f5c\u6570\u51c6\u5907\u597d\u53d1\u73b0\u731c\u9519\u4e86\uff0c\u5927\u4e0d\u4e86\u518d\u6390\u6389\uff0c\u731c\u5bf9\u4e86\u90a3\u5c31\u8282\u7ea6\u65f6\u95f4\u4e86\u3002

    \u731c\u7684\u6839\u636e\u6709\u4ec0\u4e48\u5462\uff0c\u786e\u5b9e\u6709\u6839\u636e\uff0c\u7edf\u8ba1\u8868\u660e\u5927\u90e8\u5206\u7a0b\u5e8f\u91cc\u53d1\u751f\u8df3\u8f6c\uff08branch taken\uff09\u548c\u4e0d\u53d1\u751f\u8df3\u8f6c\uff08branch not taken\uff09\u7684\u6570\u76ee\u662f\u4e25\u91cd\u4e0d\u6210\u6bd4\u4f8b\u7684\uff0c\u7ecf\u5e38\u5176\u4e2d\u4e00\u4e2a\u53ef\u80fd\u80fd\u5360\u5230 90% \u591a\u7684\u60c5\u51b5\u3002\u90a3\u4e48\uff0c\u5047\u8bbe\u5982\u679c\u77e5\u9053\u4e4b\u524d\u5f88\u591a\u8df3\u8f6c\u8bed\u53e5\u90fd\u8df3\u4e86\uff0c\u63a5\u4e0b\u6765\u53d1\u751f\u7684\u8df3\u8f6c\u8bed\u53e5\u4e5f\u5927\u6982\u7387\u4f1a\u8df3\u3002

    \u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u8bbe\u8ba1\u4e00\u4e2a\u72b6\u6001\u673a\uff0c\u6709\u56db\u79cd\u7f16\u7801 00(\u5f88\u53ef\u80fd\u8df3) 01(\u5e94\u8be5\u8df3\u5427) 10(\u5e94\u8be5\u4e0d\u8df3\u5427) 11(\u5f88\u53ef\u80fd\u4e0d\u8df3)\uff0c\u5982\u679c\u72b6\u6001\u673a\u5728 00 \u548c 01 \u72b6\u6001\u5c31\u9884\u6d4b\u4e0b\u4e00\u6b21\u4e5f\u8df3\u8f6c\uff0c\u5982\u679c\u72b6\u6001\u673a\u5728 10 \u548c 11 \u5c31\u9884\u6d4b\u4e0b\u4e00\u6b21\u4e0d\u8df3\u8f6c\u3002

    \u800c\u72b6\u6001\u8f6c\u79fb\u662f\u8fd9\u6837\u53d1\u751f\u7684\uff1a

    Note

    \u6211\u77e5\u9053 mkdocs \u5e94\u8be5\u6e32\u4e0d\u4e86 mermaid\uff0c\u4f46\u662f\u6211\u61d2\uff0c\u8bf7\u5927\u5bb6\u8111\u6e32\u4e00\u4e0b\u3002\u3002\u6216\u8005\u770b\u81ea\u5df1\u8001\u5e08 ppt\u3002\u3002\u662f\u4e00\u4e2a\u6709\u56db\u4e2a\u72b6\u6001\u7684\u7ea2\u7ea2\u84dd\u84dd\u7684\u72b6\u6001\u673a

    graph LR\n00 --(\u672c\u6b21\u8df3\u4e86)--> 00\n00 --(\u672c\u6b21\u6ca1\u8df3)--> 01\n01 --(\u672c\u6b21\u8df3\u4e86)--> 00\n01 --(\u672c\u6b21\u6ca1\u8df3)--> 10\n10 --(\u672c\u6b21\u8df3\u4e86)--> 01\n10 --(\u672c\u6b21\u6ca1\u8df3)--> 11\n11 --(\u672c\u6b21\u8df3\u4e86)--> 10\n11 --(\u672c\u6b21\u6ca1\u8df3)--> 11\n

    \u8ba1\u7b97\u9898\u4f1a\u8003\u4f7f\u7528\u8fd9\u6837\u7684 branch prediction\uff0c\u9884\u6d4b\u5931\u8bef\u7684\u6982\u7387\u662f\u591a\u5c11\u3002

    "},{"location":"docs/1-cs/architecture/chap5/","title":"chap5: Thread-level Parallelism","text":"

    :material-circle-edit-outline: \u7ea6 381 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap5/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap5/#cache","title":"cache \u4e00\u81f4\u6027\u7684\u6982\u5ff5","text":"

    \u4e0d\u77e5\u9053\u600e\u4e48\u63cf\u8ff0\u7684\u4e24\u4e2a\u672f\u8bed

    Note

    \u8ba1\u7ec4\u738b\u9053\u6709\u4e00\u7ae0\u4e13\u95e8\u8bb2\u3002\u5176\u5b83\u8bf7\u901a\u8fc7\u738b\u9053\u5b66\u4e60\uff0c\u8fd8\u6709\u59dc\u8001\u5e08 ppt \u4e5f\u6709\u4e00\u4e2a\u5c0f\u603b\u7ed3\u7684\u8868\u683c\u3002

    \u6982\u5ff5 \u5168\u540d \u7279\u70b9 \u4f18\u70b9 UMA uniform memory access \u6bcf\u4e2a\u8282\u70b9\u5230 memory \u7684\u8bbf\u95ee\u65f6\u95f4\u4e00\u81f4 NUMA non-uniform memory access \u6bcf\u4e2a\u8282\u70b9\u5230 memory \u7684\u8bbf\u95ee\u65f6\u95f4\u4e0d\u4e00\u81f4\uff0c\u5230\u81ea\u5df1\u7684\u5feb\uff0c\u5230\u522b\u4eba\u7684\u6162 \u6269\u5c55\u5230\u66f4\u5927\u89c4\u6a21\u4e0a\u7684\u53ef\u6269\u5c55\u6027\u5f3a

    cache \u4e00\u81f4\u6027\u7684\u672f\u8bed

    \u5982\u679c CPU \u6709\u591a\u4e2a\u6838\uff0c\u6216\u8005\u5982\u679c CPU \u662f\u5206\u5e03\u5f0f\u7684\uff0c\u5b83\u4eec\u5171\u7528\u4e00\u4e2a cache\uff0c\u90a3\u4e48\u5c31\u9700\u8981\u4f7f cache \u5bf9\u6240\u6709\u6838/\u8282\u70b9\u7684\u8bfb\u5199\u4fdd\u6301\u4e00\u81f4\u6027\uff0c\u6bd4\u5982\u4e00\u4e2a\u6838/\u8282\u70b9\u5199\u7684\u4e1c\u897f\u5bf9\u5176\u5b83\u6838/\u8282\u70b9\u53ef\u89c1\uff0c\u5176\u5b83\u6838/\u8282\u70b9\u770b\u89c1\u7684\u90fd\u662f\u6700\u65b0\u7684\u3002

    \u672f\u8bed \u4e00\u53e5\u8bdd\u5b9a\u4e49\uff08\u5728 ppt \u4e0a\u53d1\u73b0\u7684\uff0c\u4f46\u662f\u4e2a\u4eba\u611f\u89c9\u4e0d\u592a\u51c6\u786e\uff09 \u5173\u6ce8\u7684\u65b9\u9762\u662f\uff08\u8fd9\u680f from \u8bfe\u672c\u66f4\u51c6\u786e\uff0c\u4f46\u4e0d\u662f\u4e00\u53e5\u8bdd\u5b9a\u4e49\uff09 coherence Memory accesses executed by each processor were kept in order. reads and writes to the same location consistency Memory accesses among different processors were interleaved. reads and writes wrt other memory locations"},{"location":"docs/1-cs/architecture/chap5/#cache_1","title":"\u8fbe\u6210 cache \u4e00\u81f4\u6027\u4e24\u4e2a\u534f\u8bae","text":"

    Note

    \u806a\u660e\u7684\u8bfb\u8005\u5df2\u7ecf\u53d1\u73b0\u6211\u5df2\u7ecf\u4e0d\u60f3\u5199\u4e86

    Snooping\u534f\u8bae

    Note

    \u8bf7\u901a\u8fc7\u81ea\u5df1\u73ed\u8001\u5e08 ppt \u5b66\u4e60\uff1aMOESI \u72b6\u6001\u673a + \u4f8b\u9898\u8868\u683c \u4e24\u4e2a\u56fe

    Directory\u534f\u8bae

    Note

    \u8bf7\u901a\u8fc7\u81ea\u5df1\u73ed\u8001\u5e08 ppt \u5b66\u4e60: \u4f8b\u9898\u8868\u683c \u4e00\u4e2a\u56fe

    "},{"location":"docs/1-cs/compiler/","title":"Compiler","text":"

    :material-circle-edit-outline: \u7ea6 56 \u4e2a\u5b57

    \u662f ZJU \u7f16\u8bd1\u539f\u7406\u7b14\u8bb0\u3002\u4f5c\u4e3a xyx \u4e8b\u65e0\u5de8\u7ec6\u7248\u672c\u7684\u7b14\u8bb0\uff08\u53ef\u5728\u672c\u7ad9\u9996\u9875\u627e\u5230\uff09\u7684\u8865\u5145\uff0c\u6211\u505a\u4e86\u4e00\u4e9b\u6211\u505a\u9898\u65f6\u9700\u901f\u67e5\u7684\u8d44\u6599\u7684\u6574\u7406\u3002

    \u8fdb\u5ea6\uff1a

    "},{"location":"docs/1-cs/compiler/parsing/","title":"Parsing","text":"

    :material-circle-edit-outline: \u7ea6 788 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    \u672c\u9875\u5b8c\u6210\u4e86\u5173\u4e8e LL(1), LR(0), SLR (aka. SLR(1)), LR(1), LALR(1) \u6587\u6cd5\u7684\u4e00\u4e9b\u5e38\u7528\u533a\u522b\u7684\u6574\u7406\u3002\u7531\u4e8e\u4f5c\u8005\u4e5f\u5b66\u5f97\u4e0d\u597d\uff0c\u5982\u679c\u6709\u9519\uff0c\u8bf7\u5411\u6211\u6307\u51fa\uff08\u53ef\u60dc\u8bc4\u8bba\u533a\u6211\u8fd8\u6ca1\u7814\u7a76\u597d\u600e\u6837\u914d\uff0c\u4e00\u5b9a\u5c3d\u5feb\u914d\u4e0a\uff0c\u53ef\u4ee5\u5148\u5176\u5b83\u9014\u5f84\u8054\u7cfb\u6211\uff09\u3002

    \u672c\u9875\u9762\u5199\u4f5c\u65f6\u7684\u7279\u70b9\u662f\u5c3d\u91cf\u7528\u81ea\u7136\u8bed\u8a00\u6765\u63cf\u8ff0\u7279\u70b9\uff0c\u800c\u4e0d\u662f latex \u6570\u5b66\u516c\u5f0f\u548c\u56fe\u50cf\u3002\u539f\u56e0\u662f\u6211\u5728\u5176\u5b83\u8d44\u6599\u641c\u5230\u7684\u8bb2\u89e3\u90fd\u4e8b\u65e0\u5de8\u7ec6\u7528\u5927\u91cf\u516c\u5f0f\u548c\u56fe\u50cf\uff0c\u4f7f\u7406\u89e3\u53d8\u5f97\u5bb9\u6613\uff0c\u4f46\u4e0d\u9002\u5408\u901f\u67e5\u548c\u8bb0\u5fc6\u3002\u76f4\u767d\u4e00\u70b9\u8bf4\u5c31\u662f\u7b14\u8005\u4e0d\u60f3\u770b\u5230\u5b83\u4eec\uff0c\u4e00\u770b\u5c31\u5934\u75bc\u3002\u56e0\u6b64\u4e5f\u9020\u6210\u4e86\u672c\u6587\u6863\u7684\u4e00\u4e2a\u7f3a\u70b9\uff1a\u4e0d\u662f\u4e3a\u521d\u5b66\u8005\u8bbe\u8ba1\u7684\u3002\u521d\u5b66\u8005\u63a8\u8350\u9605\u8bfb xyx \u7684\u7b14\u8bb0\u3002\u505a\u9898\u65f6\u901f\u67e5\u8bb0\u5fc6\u53ef\u4ee5\u770b\u672c\u6587\u6863\u3002

    \u600e\u6837\u5224\u65ad\u6587\u6cd5\u662f...\u4e0d\u662f...

    \u6587\u6cd5 \u5224\u65ad\u662f \u5224\u65ad\u4e0d\u662f LL(1) (\u4e0d\u542b\u5de6\u9012\u5f52 && \u5bf9\u4e8e\u6587\u6cd5\u4e2d\u6bcf\u4e00\u4e2a non-terminal\uff0c\u5b83\u7684\u4ea7\u751f\u5f0f\u7684 SELECT set\uff08\u5373\u5f00\u5934\u7684 terminal \u4e0e\u5f00\u5934\u7684 non-terminal \u7684 FIRST\uff09\u4e24\u4e24\u4e0d\u4ea4\uff0c\u4e14\u4e0d\u80fd\u540c\u65f6\u63a8\u51fa\u7a7a\u4e32) || \u4ea7\u751f\u5f0f lhs \u4e24\u4e24\u4e0d\u76f8\u540c \u542b\u5de6\u9012\u5f52 || \u9047\u5230\u4e0b\u4e00\u4e2a\u8981\u626b\u63cf\u7684 terminal \u8f93\u5165\u65f6\uff0c\u6709\u8d85\u8fc7\u4e00\u79cd derive \u65b9\u6cd5 LR(0) \u6784\u9020\u51fa LR(0) items DFA\uff0c\u5982\u679c\u4e0d\u5b58\u5728 shift-reduce & reduce-reduce conflicts LR(0) items DFA \u5b58\u5728 shift-reduce | reduce-reduce conflicts SLR (aka. SLR(1)) \u6784\u9020\u51fa LR(0) items DFA\uff0c\u9996\u5148\u5176\u4e0d\u5b58\u5728 reduce-reduce \u51b2\u7a81\uff0c\u4e14\u5b58\u5728 shift-reduce \u51b2\u7a81\uff08\u5426\u5219\u5c31\u4e3a LR(0) \u8bed\u6cd5\u4e86\uff09\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u6709 shift-reduce \u51b2\u7a81\u7684\u5730\u65b9\uff0c\u72b6\u6001\u91cc\u9762\u6709\u53ef shift \u89c4\u5219\u4e5f\u6709\u53ef reduce \u89c4\u5219\uff0c\u5982\u679c reduce \u540e\u5f97\u5230\u7684 non-terminal \u7684 FOLLOW set \u4e0e\u53ef shift \u89c4\u5219\u65b0\u7eb3\u5165\u7684 terminal \u90fd\u6ca1\u6709\u4ea4 shift-reduce conflict \u4e2d\u5982\u679c reduce \u540e\u5f97\u5230\u7684 non-terminal \u7684 FOLLOW set \u4e0e\u53ef shift \u89c4\u5219\u65b0\u7eb3\u5165\u7684 terminal \u6709\u4ea4 LR(1) \u6784\u9020\u51fa LR(1) items DFA\uff0c\u5982\u679c\u4e0d\u5b58\u5728 shift-reduce & reduce-reduce conflicts LR(1) items DFA\uff0c\u5982\u679c\u5b58\u5728 shift-reduce | reduce-reduce conflicts LALR(1) \u6784\u9020\u51fa LR(1) items DFA\uff0c\u5982\u679c\u5408\u5e76\u540c\u5fc3\u96c6\u540e\u6ca1\u6709\u4ea7\u751f reduce-reduce conflicts\uff08\u4e00\u5b9a\u4e0d\u4f1a\u4ea7\u751f shift-reduce conflicts\uff0c\u540c\u5fc3\u96c6\u4e0d\u957f\u90a3\u6837\uff09 LR(1) items DFA \u5982\u679c\u5408\u5e76\u540c\u5fc3\u96c6\u540e\u4ea7\u751f\u4e86 reduce-reduce conflicts

    \u5927\u5bb6\u7684 items DFA \u600e\u4e48\u753b...

    \u6587\u6cd5 items DFA LL(1) \u5b83\u6ca1\u6709\u2026 LR(0) \u5148\u753b NFA\uff1a\u6240\u6709 shift \u7684\u60c5\u51b5\u9760\u8bfb\u53d6 non-terminal/terminal \u8f6c\u6362\uff0c\u6240\u6709 reduce \u7684\u60c5\u51b5\u7a7a\u8f6c\u79fb\u3002\u7136\u540e\u753b DFA\uff1a\u628a\u7a7a\u8f6c\u79fb\u5408\u5e76\u3002 SLR (aka. SLR(1)) \u540c\u753b LR(0)\u3002\u53ea\u662f\u591a\u5224\u65ad\u4e00\u4e0b shift-reduce conflict \u7684 FOLLOW \u548c terminal \u91cd\u5408\u60c5\u51b5\uff0c\u4f46\u8fd9\u4e2a\u53ea\u4f53\u73b0\u5728 parse table\uff0c\u4e0d\u5c5e\u4e8e DFA \u5173\u5fc3\u7684\u4e8b\u3002 LR(1) \u5176\u5b83\u6b65\u9aa4\u540c\u753b LR(0)\uff0c\u53ea\u662f\u591a\u4e86\u5728\u6240\u6709 items \u540e\u9762\u7528\u9017\u53f7\u9694\u5f00\u4e00\u4e2a lookahead symbol\u3002lookahead \u7684\u9009\u62e9\u5f88\u50cf\u9009\u62e9\u4e86\u5bf9\u5e94\u4ea7\u751f\u5f0f\uff08\u4e0d\u8bba\u662f lhs/rhs\uff09\u7684 FOLLOW set\uff0c\u5373\u5bf9\u5e94\u4ea7\u751f\u5f0f\u4e4b\u540e\u63a5\u7684 terminal \u662f\u4ec0\u4e48\u3002 LALR(1) \u540c\u753b LR(1)\u3002\u53ea\u662f\u9700\u8981\u5408\u5e76\u6240\u6709\u540c\u5fc3\u96c6\uff0c\u540c\u5fc3\u96c6\u662f\u6307\u4ea7\u751f\u5f0f\u76f8\u540c\u4f46\u662f\u53ea\u6709 lookahead symbol \u4e0d\u540c\u7684\u90a3\u4e9b\u72b6\u6001\u3002

    \u5927\u5bb6\u7684 parse table \u600e\u4e48\u753b...

    \u6587\u6cd5 parse table LL(1) non-terminals, nullable, FIRST, FOLLOW LR(0) states, shift&reduce, goto SLR (aka. SLR(1)) states, shift&reduce, goto LR(1) states, shift&reduce, goto LALR(1) states, shift&reduce, goto"},{"location":"docs/1-cs/database/","title":"DBMS","text":"

    :material-circle-edit-outline: \u7ea6 360 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/database/#whats-this","title":"what's this","text":"

    \u8fd9\u91cc\u662f\u6570\u636e\u5e93\u7cfb\u7edf\u7684\u7406\u8bba\u8bfe\u3002

    content table:

    "},{"location":"docs/1-cs/database/#brief-intro-to-dbms-course","title":"Brief intro to DBMS course","text":"

    \u4e00\u4e9b\u4e0e\u8003\u8bd5\u6709\u5173\u7684\u504f\u95e8\u4e1c\u897f\u3002

    \u4e00\u4e2a\u671f\u672b\u8003\u70b9\uff1a\u6570\u636e\u5e93\u5b66\u79d1\u7684\u56db\u4e2a\u56fe\u7075\u5956

    \u4eba\u7269 \u5e74\u4efd \u8d21\u732e Charles William Bachman 1973 \u6570\u636e\u5e93\u7ba1\u7406\u7cfb\u7edf DBMS \u7684\u5f00\u53d1\u3002\u4f7f\u7528\u5de5\u7a0b\u65b9\u6cd5\u6765\u8bbe\u8ba1\u548c\u5b9e\u73b0\u6570\u636e\u5e93\u7ba1\u7406\u3002 Edgar Frank \"Ted\" Codd 1981 \u5173\u7cfb\u6570\u636e\u5e93\u7406\u8bba\uff0c\u63d0\u51fa\u4e86\u5173\u7cfb\u6a21\u578b\u7684\u6982\u5ff5\uff0c\u8bbe\u8ba1\u4e86\u5173\u7cfb\u6570\u636e\u5e93\u7684\u6570\u5b66\u57fa\u7840\uff0c\u5e76\u53d1\u660e\u4e86SQL\u3002 Raj Reddy 1994 \u5206\u5e03\u5f0f\u6570\u636e\u5e93\u7cfb\u7edf\u3002\u63d0\u51fa\u4e86\u4e00\u79cd\u540d\u4e3aDAI\uff08distributed artificial intelligence\uff09\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u6a21\u578b\u3002\u4f7f\u6570\u636e\u53ef\u4ee5\u5728\u591a\u53f0\u8ba1\u7b97\u673a\u4e4b\u95f4\u5171\u4eab\u548c\u5206\u5e03 Mike Ralph Stonebraker 2014 \u9762\u5411\u5bf9\u8c61\u6570\u636e\u5e93\u7cfb\u7edf\u3002\u63d0\u51fa\u4e86\u4e00\u79cd\u540d\u4e3a O-ODBS (object-oriented database system) \u7684\u65b0\u578b\u6570\u636e\u5e93\u7cfb\u7edf\u67b6\u6784\uff0c\u5c06\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\u548c\u6570\u636e\u5e93\u7cfb\u7edf\u76f8\u7ed3\u5408\u3002\u4f7f\u6570\u636e\u5e93\u7cfb\u7edf\u53ef\u4ee5\u66f4\u597d\u652f\u6301\u590d\u6742\u5e94\u7528\u548c\u66f4\u5927\u89c4\u6a21\u6570\u636e\u3002"},{"location":"docs/1-cs/database/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"

    \u5b8c\u6574\u8d44\u6599

    \u4e13\u9898\u5e16\u5b50

    "},{"location":"docs/1-cs/database/ERmodel/","title":"E-R model","text":"

    :material-circle-edit-outline: \u7ea6 2 \u4e2a\u5b57

    "},{"location":"docs/1-cs/database/SQL/","title":"SQL Grammar","text":"

    :material-circle-edit-outline: \u7ea6 172 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/database/SQL/#_1","title":"\u5173\u7cfb\u4ee3\u6570","text":"

    5 \u79cd\u57fa\u672c\u64cd\u4f5c

    \u6269\u5c55\u64cd\u4f5c

    "},{"location":"docs/1-cs/database/SQL/#sql","title":"SQL \u8bed\u6cd5","text":"

    select

    select distinct

    where

    and / or

    order by

    insert to

    update delete

    JOIN \u8bed\u53e5

    \u8fde\u63a5\uff1a\u7528\u4e8e\u628a\u591a\u4e2a\u8868\u7684\u884c\u7ed3\u5408\u8d77\u6765\u3002

    SQL \u4e2d\u51e0\u79cd join \u7684\u7c7b\u578b

    "},{"location":"docs/1-cs/database/design/","title":"Database Design \u6570\u636e\u5e93\u8bbe\u8ba1","text":"

    :material-circle-edit-outline: \u7ea6 3119 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    \u8fd9\u7ae0\u5173\u6ce8\u5982\u4f55\u5728\u78c1\u76d8 disk \u4e0a\u5b9e\u73b0\u4e00\u4e2a database\u3002

    "},{"location":"docs/1-cs/database/design/#storage-structure","title":"Storage Structure \u5b58\u50a8\u7ed3\u6784","text":"

    \u9996\u5148\u9700\u8981\u4ecb\u7ecd storage hierarchy\u3002\u4e00\u4e2a\u4ece\u9876\uff08\u5bb9\u91cf\u6700\u5c0f\u6700\u5feb\u7684\uff09\u5411\u4e0b\uff08\u5bb9\u91cf\u6700\u5927\u6700\u6162\u7684\uff09\u7684\u56fe\u793a\u5982\u4e0b\uff0c

        /\\   Primary storage \u4e3b\u5b58\u50a8\u5668: CPU register \u5bc4\u5b58\u5668, cache \u7f13\u5b58, main memory \u4e3b\u5b58\n   /--\\  Secondary storage \u4e8c\u7ea7\u5b58\u50a8\u5668: flash memory \u95ea\u5b58, magnetic disk \u78c1\u76d8\n  /----\\ Teriary storage \u4e09\u7ea7\u5b58\u50a8\u5668: optical disk \u5149\u76d8, magnetic tape \u78c1\u5e26\n --------\n
    \u5176\u4e2d\u6700\u9876\u5c42 primary storage \u662f volatile\uff08\u6613\u5931\u7684\uff09\uff0c\u610f\u601d\u662f\u5982\u679c\u8ba1\u7b97\u673a\u65ad\u7535\u91cd\u542f\uff0c\u5c31\u4f1a\u4e22\u5931\uff1b\u4e0b\u9762\u4e24\u5c42\u90fd\u662f non-volatile\uff08\u4e0d\u6613\u5931\u7684\uff09\uff0c\u610f\u601d\u662f\u5373\u4f7f\u8ba1\u7b97\u673a\u65ad\u7535\uff0c\u4e5f\u4e0d\u4f1a\u4e22\u5931\u3002

    \u4e0b\u9762\u4f9d\u6b21\u7b80\u5355\u4ecb\u7ecd\u6bcf\u4e2a\u5b58\u50a8\u5668\uff1a

    "},{"location":"docs/1-cs/database/design/#performance-measures-of-disk","title":"Performance Measures of Disk \u78c1\u76d8\u6027\u80fd\u8ba1\u7b97","text":"

    \u6d4b\u91cf\u78c1\u76d8\u7684\u6027\u80fd\u9700\u8981\u4e00\u4e9b\u91cf\u5316\u6307\u6807\uff0c\u901a\u5e38\u6211\u4eec\u8003\u8651\u6570\u636e\u6570\u636e\u8bbf\u95ee\u7684\u7528\u65f6\u548c\u3002

    "},{"location":"docs/1-cs/database/design/#_1","title":"\u78c1\u76d8\u6027\u80fd\u4f18\u5316","text":""},{"location":"docs/1-cs/database/design/#raid","title":"RAID","text":"

    !!! (\u8fd9\u5757\u5728 db \u548c os \u91cc\u90fd\u4e0d\u8003\uff0c\u4f46\u662f\u90fd\u4f1a\u7ecf\u5e38\u63d0\u5230\uff0c\u5f88\u795e\u79d8\uff0c\u6240\u4ee5\u987a\u4fbf\u505a\u4e00\u4e0b\u7b14\u8bb0)

    RAID \u5168\u79f0\u662f redundant arrays of independent disk \u72ec\u7acb\u78c1\u76d8\u5197\u4f59\u9635\u5217\u3002\u5b83\u7684\u6765\u5386\u662f\u56e0\u4e3a\uff0c\u8fc7\u53bb\u7684\u7cfb\u7edf\u8bbe\u8ba1\u8005\u4eec\u8ba4\u4e3a\u4f7f\u7528\u591a\u4e2a\u5c0f\u578b\u3001\u5ec9\u4ef7\u78c1\u76d8\u7ec4\u6210\u7684\u5b58\u50a8\u7cfb\u7edf\u662f\u4e00\u4e2a\u66f4\u7ecf\u6d4e\u9ad8\u6548\u7684\u9009\u9879\uff0c\u6240\u4ee5\u539f\u6765 RAID \u4e2d\u7684 I \u662f inexpensive \u7684\u610f\u601d\u3002\u4f46\u73b0\u5728\u6240\u6709\u78c1\u76d8\u5728\u7269\u7406\u5c3a\u5bf8\u4e0a\u90fd\u5f88\u5c0f\uff0c\u5bb9\u91cf\u66f4\u5927\u7684\u78c1\u76d8\u5b9e\u9645\u4e0a\u5177\u6709\u66f4\u4f4e\u7684\u6bcf\u5146\u5b57\u8282\u6210\u672c\u3002\u5f00\u53d1\u8005\u4f7f\u7528 RAID \u7cfb\u7edf\u73b0\u5728\u4e3b\u8981\u56e0\u5176\u66f4\u9ad8\u7684\u53ef\u9760\u6027\u548c\u6027\u80fd\uff0c\u548c\u7ba1\u7406\u64cd\u4f5c\u7b80\u4fbf\u3002

    !!! TODO

    \u901a\u8fc7\u5e76\u884c\u6765\u52a0\u901f

    "},{"location":"docs/1-cs/database/design/#file-system","title":"File System \u6587\u4ef6\u7cfb\u7edf","text":"

    \u6570\u636e\u5e93\u662f\u5b58\u50a8\u5728\u4e00\u7cfb\u5217\u7684\u6587\u4ef6\u4e2d\u7684\uff0c\u6587\u4ef6\u5185\u90e8\uff0c\u6bcf\u4e2a\u6587\u4ef6\u4e2d\u6709\u4e00\u7cfb\u5217\u7684 records \u8bb0\u5f55\uff0c\u6bcf\u4e2a record \u542b\u6709\u4e00\u7cfb\u5217\u7684 fields \u57df\u3002

    \u5728\u8bbe\u8ba1\u65f6\uff0c\u4e00\u822c\u6709\u4e00\u4e9b\u5047\u8bbe\uff1a\uff081\uff09\u5047\u8bbe\u8bb0\u5f55\u7684\u957f\u5ea6\u662f\u56fa\u5b9a\u7684\uff0c\uff082\uff09\u5047\u8bbe\u6bcf\u4e2a\u6587\u4ef6\u91cc\u53ea\u6709\u4e00\u79cd\u8bb0\u5f55\uff0c\uff083\uff09\u5047\u8bbe\u4e0d\u540c\u7684\u6587\u4ef6\u88ab\u7528\u4e8e\u4e0d\u540c\u7684\u5173\u7cfb\u3002

    "},{"location":"docs/1-cs/database/design/#_2","title":"\u8bb0\u5f55\u7684\u7c7b\u578b","text":"

    \u8bb0\u5f55\u5206\u4e3a

    "},{"location":"docs/1-cs/database/design/#_3","title":"\u8bb0\u5f55\u7684\u6392\u5e03","text":"

    \u4e00\u4e2a\u65b0\u7684\u8bb0\u5f55\u8981\u63d2\u5165\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u6709\u51e0\u79cd\u7b97\u6cd5\u6765\u51b3\u5b9a\u63d2\u5165\u5230\u6587\u4ef6\u7684\u54ea\u4e2a\u4f4d\u7f6e\uff1a

    \u6bcf\u4e2a\u6587\u4ef6\u88ab\u5212\u5206\u4e3a\u56fa\u5b9a\u957f\u5ea6\u7684 blocks\u3002block \u662f\u6570\u636e\u5b58\u53d6\u548c\u7a7a\u95f4\u5206\u914d\u7684\u57fa\u672c\u5355\u4f4d\u3002

    \u4e00\u4e2a block \u5305\u542b\u591a\u6761\u8bb0\u5f55\u3002\u5728\u4f20\u7edf\u7684\u6570\u636e\u5e93\u4e2d\uff0c\u8bb0\u5f55\u7684\u957f\u5ea6\u4e0d\u80fd\u8d85\u8fc7 block\uff0c\u6bcf\u6761\u8bb0\u5f55\u4e00\u5b9a\u90fd\u662f\u5b8c\u6574\u7684\u3002\u8bb0\u5f55\u4e4b\u95f4\u7528\u94fe\u8868\u6765\u8fde\u63a5\u3002

    \u8bb0\u5f55\u5206\u4e3a\u5b9a\u957f\u8bb0\u5f55\u548c\u53d8\u957f\u8bb0\u5f55\u4e24\u79cd\u3002

    slotted page structure \u5206\u69fd\u9875

    \u5178\u578b\u7684\u53d8\u957f\u8bb0\u5f55\u6709\u5982\u4e0b\u7279\u70b9\uff1a

    \u5b58\u50a8\u7f13\u51b2\u533a\u7684\u7ba1\u7406

    "},{"location":"docs/1-cs/database/design/#index","title":"Index \u7d22\u5f15","text":"

    \u6570\u636e\u5e93\u4e2d\u5f15\u5165\u7d22\u5f15\u6982\u5ff5\uff0c\u662f\u4e3a\u4e86\u52a0\u5feb\u67e5\u627e\u901f\u5ea6\u3002

    \u5728\u5f15\u5165\u7d22\u5f15\u7684\u65f6\u5019\uff0c\u9700\u8981\u5173\u6ce8\u7684\u56e0\u7d20\u90fd\u6709\u5982\u4e0b\u51e0\u79cd

    \u4e00\u822c\u6765\u8bf4\uff0c\u952e\u7684\u6392\u5217\u65b9\u5f0f\u5206\u4e3a ordered index \u987a\u5e8f\u7d22\u5f15\u548c hased index \u4e24\u79cd\u3002

    \u800c\u7d22\u5f15\u6307\u5411\u6570\u636e\u7684\u65b9\u5f0f\u53c8\u5206\u4e3a\uff1a

    "},{"location":"docs/1-cs/database/design/#b","title":"B+ \u6811","text":"

    \u4ecb\u7ecd\u5e38\u7528\u7684 B+ \u6811\u6570\u636e\u7ed3\u6784\u3002\u4e0e fds \u4e2d\u5b9a\u4e49\u76f8\u540c\uff0c\u4f46\u662f\u518d\u4ecb\u7ecd\u4e00\u6b21\u3002

    B+ \u6811\u662f\u4e00\u79cd\u5e73\u8861\u7684\uff08\u6bcf\u5c42\u90fd\u662f\u6ee1\u7684\uff09\u591a\u5206\u6811\uff08\u4e0d\u6b62\u4e24\u4e2a\u8282\u70b9\uff09\u3002\u4e00\u4e2a m \u9636\u7684 B+ \u6811\u6ee1\u8db3\u5982\u4e0b\u6761\u4ef6\uff1a

    \u5728\u5b9e\u73b0\u4e2d\uff0cB+ \u6811\u7684\u4e00\u4e2a\u8282\u70b9\u7684\u5927\u5c0f\u548c\u4e00\u4e2a\u78c1\u76d8\u533a\u5757\u4e00\u6837\u5927\uff08\u901a\u5e38\u662f 4 KB\uff09\uff0c\u800c\u7d22\u5f15\u7684\u89c4\u6a21\u4e00\u822c\u5728 100 \u5de6\u53f3\u3002

    B+ Tree Visualization \u662f\u4e00\u4e2a B+ \u6811\u53ef\u89c6\u5316\u7684\u5de5\u5177\u3002

    \u4ecb\u7ecd\u67e5\u8be2\u3001\u63d2\u5165\u548c\u5220\u9664\u64cd\u4f5c\u3002

    \u5f53 B+ \u6811\u4e2d\u7684\u8282\u70b9 TODO \u5177\u4f53\u7684\u6761\u4ef6\u662f\u4ec0\u4e48\uff0c\u6211\u4eec\u8fd9\u91cc\u8bb0\u4f5c\u7834\u574f\u4e86 B+ \u6811\u3001\u5143\u7d20\u8fc7\u591a\u6216\u5143\u7d20\u8fc7\u5c11\uff0c\u5c31\u9700\u8981\u8003\u8651\u66f4\u65b0\u7d22\u5f15\u3002

    \u5206\u522b\u5206\u6790\u51e0\u79cd\u6570\u636e\u64cd\u4f5c\u4e0b\uff0cB+ \u6811\u7684\u6027\u80fd\uff1a

    B+ \u6811\u7684\u76f8\u5173\u8ba1\u7b97

    \u9ad8\u5ea6\u7684\u4f30\u8ba1\uff1a\u53ef\u4ee5\u5206\u6790\u9ad8\u5ea6\u7684\u4e0a\u4e0b\u754c

    size \u5927\u5c0f\u7684\u4f30\u8ba1\uff1a\u4e5f\u662f\u5206\u6790\u9ad8\u5ea6\u7684\u4e0a\u4e0b\u754c

    "},{"location":"docs/1-cs/database/design/#hash","title":"Hash \u7d22\u5f15","text":""},{"location":"docs/1-cs/database/normalforms/","title":"\u6570\u636e\u5e93\u5173\u7cfb\u6a21\u5f0f","text":"

    :material-circle-edit-outline: \u7ea6 1976 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f

    \u4e3a\u4ec0\u4e48\u6211\u4eec\u9700\u8981\u5173\u7cfb\u6a21\u5f0f\uff1f

    \u5728\u8bbe\u8ba1\u6570\u636e\u5e93\u7684\u65f6\u5019\uff0c\u6211\u4eec\u753b\u5b8c E-R \u56fe\uff0c\u8981\u628a\u56fe\u8f6c\u5316\u6210\u8868\u7684\u5f62\u5f0f\u5316\u5b9a\u4e49\uff08\u6bd4\u5982 Student(sid, course, department) \u8fd9\u79cd\u683c\u5f0f\uff09\u3002\u8fd9\u5c31\u9700\u8981\u6211\u4eec\u5bf9\u4e00\u4e9b\u5c5e\u6027\u8fdb\u884c\u8fdb\u4e00\u6b65\u7ea6\u675f\uff0c\u6bd4\u5982\u8981\u5173\u6ce8\u8fd9\u4e9b\u95ee\u9898\uff1a\uff081\uff09\u5728\u4e24\u4e2a\u8868\u91cc\u7684\u952e\u8c01\u51b3\u5b9a\u8c01\uff1f\u8981\u4fdd\u8bc1\u53ea\u6709 candidate key \u7684\u5c5e\u6027\u624d\u80fd\u51b3\u5b9a\u5176\u5b83\u5c5e\u6027\u3002\uff082\uff09\u6709\u4e9b\u8868\u8be5\u5408\u5728\u4e00\u8d77\uff0c\u8fd8\u662f\u62c6\u6210\u591a\u4e2a\u8868\uff1f\u5982\u679c\u8868\u5408\u5f97\u592a\u591a\uff0c\u6709\u4e9b\u4fe1\u606f\u53ef\u80fd\u51fa\u73b0\u592a\u591a\u6b21\uff0c\u4ea7\u751f\u4fe1\u606f\u5197\u4f59\u3001\u63d2\u5165\u5f02\u5e38\u3001\u66f4\u65b0\u56f0\u96be\u3002\uff083\uff09\u6709\u4e9b\u5c5e\u6027\u867d\u7136\u4e0d\u662f\u4e3b\u952e\uff0c\u4f46\u53c8\u51b3\u5b9a\u5176\u5b83\u5173\u7cfb\u7684\u503c\uff0c\u8fd9\u79cd\u60c5\u51b5\u53eb\u505a\u6709\u51fd\u6570\u4f9d\u8d56\u3002

    \u6240\u4ee5\u6211\u4eec\u5f15\u5165\u5173\u7cfb\u4ee3\u6570\uff0c\u6765\u6307\u5bfc\u6211\u4eec\u4ece E-R \u56fe\u5230\u5efa\u7acb\u5f62\u5f0f\u5316\u5b9a\u4e49\u7684\u8fd9\u4e00\u6b65\u9aa4\u3002\u5176\u5b9e\u4e3b\u8981\u7275\u626f\u5230\u7684\u6b65\u9aa4\u5c31\u662f\u5173\u7cfb\u5206\u89e3\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5148\u4ecb\u7ecd\u5206\u89e3\uff0c\u7136\u540e\u4ecb\u7ecd\u5176\u4f9d\u8d56\u7684\u7406\u8bba\u51fd\u6570\u4f9d\u8d56\u7684\u5b9a\u4e49\uff1b\u7136\u540e\u4ecb\u7ecd 6 \u79cd\u6307\u5bfc\u5173\u7cfb\u6a21\u5f0f\u7684\u8303\u5f0f\uff0c\u8fd9\u4e9b\u6bcf\u79cd\u8303\u5f0f\u5c42\u5c42\u9012\u8fdb\uff0c\u662f\u4e00\u4e9b\u5bf9\u6570\u636e\u5e93\u5173\u7cfb\u8d8a\u6765\u8d8a\u4e25\u683c\u7684\u7ea6\u675f\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_2","title":"\u5206\u89e3","text":"

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u662f\u4e0d\u597d\u7684\uff0c\u6211\u4eec\u5e0c\u671b\u628a\u5b83\u5206\u89e3\u6210\u597d\u7684\u5173\u7cfb\u3002

    \u4ecb\u7ecd\u4e00\u4e0b decomposition \u5206\u89e3\u5206\u4e3a\u4e24\u7c7b

    \u8fd9\u4e2a\u5206\u89e3\u7684\u7406\u8bba\uff0c\u662f\u57fa\u4e8e (1) functional dependencies \u51fd\u6570\u4f9d\u8d56 (2) multivalued dependencies \u591a\u503c\u4f9d\u8d56 \u4e24\u4e2a\u7406\u8bba\u7684\u3002

    \u6839\u636e\u5206\u89e3\u7406\u8bba\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u518d\u4e0b\u4e00\u6b65\u8981\u4ecb\u7ecd\u7684\u516d\u4e2a\u8303\u5f0f\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_3","title":"\u51fd\u6570\u4f9d\u8d56","text":"

    \u6982\u5ff5\u533a\u522b

    \u51fd\u6570\u4f9d\u8d56\uff1a

    \u90e8\u5206\u51fd\u6570\u4f9d\u8d56\uff1a\u8bbe X, Y \u662f\u5173\u7cfb R \u7684\u4e24\u4e2a\u5c5e\u6027\u96c6\u5408\uff0c\u5b58\u5728 X->Y, \u82e5 X' \u662f X \u7684\u771f\u5b50\u96c6\uff0c\u5b58\u5728 X\u2018->Y\uff0c\u5219\u79f0 Y \u90e8\u5206\u4f9d\u8d56\u4e8e\u51fd\u6570 X\u3002

    \u4f20\u9012\u51fd\u6570\u4f9d\u8d56\uff1a\u8bbe X, Y, Z \u662f\u5173\u7cfb R \u4e2d\u4e92\u4e0d\u76f8\u540c\u7684\u5c5e\u6027\u96c6\u5408\uff0c

    \u5b8c\u5168\u51fd\u6570\u4f9d\u8d56\uff1a

    \u6211\u770b\u4e0d\u61c2\u3002\u3002\u3002\u3002\u3002\u3002

    \u51fd\u6570\u4f9d\u8d56\u662f\u6765\u81ea\u4e8e\u5e94\u7528\u5c42\u9762\u7684\u89c4\u5b9a\uff08Functional dependencies are constraints on the set of legal relations\uff09\uff0c\u5148\u6709\u51fd\u6570\u4f9d\u8d56\uff0c\u518d\u6709\u6570\u636e\u5e93\u4e2d\u7684\u503c\u3002\u51fd\u6570\u4f9d\u8d56\u8981\u6c42\u4e24\u4e2a\u503c

    \u901a\u8fc7

    \u51fd\u6570\u4f9d\u8d56\u53ef\u4ee5\u88ab\u8bc1\u4f2a\uff08\u5bf9\u4e8e\u5355\u4e2a\uff09\uff0c\u4e0d\u80fd\u88ab\u8bc1\u5b9e\uff08\u5bf9\u4e8e\u6240\u6709\uff09\u3002

    !!! \u672c\u8282\u4ee5\u4e0b latex \u9e1f\u8bed\u5168\u90fd\u4e0d\u8003

    \u5f62\u5f0f\u5316\u7684\u5b9a\u4e49\u91cc\u51fd\u6570\u4f9d\u8d56\u662f\u6307\uff0c\u5728\u4e00\u4e2a\u5173\u7cfb R \u4e2d\uff0c\u5982\u679c\u5c5e\u6027\uff08\u7ec4\uff09Y \u7684\u503c\u662f\u7531\u5c5e\u6027\uff08\u7ec4\uff09X \u7684\u503c\u51b3\u5b9a\u7684\uff0c\u5c31\u79f0 Y \u5bf9 X \u6709\u51fd\u6570\u4f9d\u8d56\u3002\u8003\u8651\u5230\u672c\u8eab\u51fd\u6570\u7684\u5b9a\u4e49\u662f X \u4e2d\u7684\u5143\u7d20\u5728 Y \u4e2d\u6709\u552f\u4e00\u786e\u5b9a\u7684\u503c\uff0c\u90a3\u4e48\u8fd9\u91cc\u7684\u4f9d\u8d56\u5c31\u662f\u6307\uff0c\u4e24\u4e2a\u5143\u7d20\u5982\u679c\u5728 X \u4e2d\u7684\u503c\u4e00\u6837\uff0c\u90a3\u4e48\u5728 Y \u4e2d\u7684\u503c\u4e5f\u4e00\u6837\u3002

    \u5f62\u5f0f\u5316\u5b9a\u4e49\uff1a\u8bbe \\(R(U)\\) \u662f\u5c5e\u6027\u96c6\u5408 \\(U={A_1, A_2, ..., A_n}\\) \u4e0a\u7684\u4e00\u4e2a\u5173\u7cfb\u6a21\u5f0f\uff0cX, Y \u662f U \u4e0a\u7684\u4e24\u4e2a\u5b50\u96c6\uff0c\u82e5\u5bf9 \\(R(U)\\) \u7684\u4efb\u4e00\u4e2a\u53ef\u80fd\u7684\u5173\u7cfb \\(r\\)\uff0c\\(r\\) \u4e2d\u4e0d\u5b58\u5728\u4e24\u4e2a\u5728 X \u4e2d\u5c5e\u6027\u503c\u76f8\u7b49\uff0c\u5728 Y \u4e2d\u5c5e\u6027\u503c\u4e0d\u7b49\u7684\u5143\u7ec4\u3002\u5373\u79f0\u4e3a\u201cX \u51fd\u6570\u51b3\u5b9a Y\u201d\u6216\u201cY \u51fd\u6570\u4f9d\u8d56 X\u201d\uff0c\u8ba1\u4f5c X -> Y\u3002

    Armstrong \u516c\u7406\u7cfb\u7edf\u662f\u63cf\u8ff0\u6570\u636e\u5e93\u4e2d\u7684\u6240\u6709\u51fd\u6570\u4f9d\u8d56\u5173\u7cfb\u7684\u4e00\u7cfb\u5217 references\uff08\u63a8\u7406\u89c4\u5219\uff09\uff0c\u5728 1974 \u5e74\u7531 William W. Armstrong \u8bbe\u8ba1\u3002

    Armstrong \u516c\u7406\u7cfb\u7edf\u6709\u4e09\u5927\u516c\u7406\uff08\u81ea\u53cd\u5f8b\uff0c\u589e\u5e7f\u5f8b\uff0c\u4f20\u9012\u5f8b\uff09\uff0c\u548c\u4e00\u4e9b\u5f15\u7406\u3002

    \u516c\u7406

    !!! \u5bf9\u4e0d\u8d77\uff0c\u6211\u662f\u61d2\u72d7\uff0c\u6211\u4e0d\u60f3\u6572 latex \u5199\u5f62\u5f0f\u5316\u5b9a\u4e49\u4e86\uff0c\u7528\u4eba\u8bdd\u7ed9\u5927\u5bb6\u8bb2\u5427\u3002

    \u8bbe F \u4e3a R(U) \u7684\u4e00\u7ec4\u51fd\u6570\u4f9d\u8d56\uff0c\u8bb0\u4e3a R(U, F)\u3002

    \u5f15\u7406

    !!! \u5b66\u4e0d\u52a8\u4e86\u5149\u62a5\u4e2a\u83dc\u540d\u5427

    \u6b63\u5219\u8986\u76d6

    "},{"location":"docs/1-cs/database/normalforms/#normal-form-6","title":"Normal Form \u8303\u5f0f\uff1a6 \u4e2a\u8303\u5f0f","text":"

    \u63a5\u4e0b\u6765\u6211\u4eec\u4ecb\u7ecd\u6570\u636e\u5e93\u8bbe\u8ba1\u7684\u516d\u5927\u8303\u5f0f\u3002\u5982\u524d\u6587\u6240\u8ff0\uff0c\u516d\u4e2a\u8303\u5f0f\u662f\u5bf9\u6570\u636e\u5e93\u5173\u7cfb\u5c5e\u6027\u5c42\u5c42\u9012\u8fdb\u3001\u8d8a\u6765\u8d8a\u4e25\u683c\u7684\u7ea6\u675f\u3002

    \u7cbe\u7b80\u7248\u5982\u4e0b\uff08\u7528\u4e8e\u8003\u524d\u7a81\u51fb\uff09\uff1a

    \u540d\u79f0 \u4ecb\u7ecd \u8303\u4f8b \u8303\u56f4 \u7b2c\u4e00\u8303\u5f0f 1NF \u5927\uff0c\u9010\u4e2a\u5305\u542b\u4e0b\u65b9\u7684 \u7b2c\u4e8c\u8303\u5f0f 2NF \u7b2c\u4e00\u8303\u5f0f 3NF Buckus-Codd NF \u7b2c\u4e94\u8303\u5f0f 5NF \u7b2c\u516d\u8303\u5f0f 6NF \u5c0f\uff0c\u9010\u4e2a\u88ab\u4e0a\u65b9\u7684\u5305\u542b

    \u63a5\u4e0b\u6765\u662f\u8be6\u7ec6\u4ecb\u7ecd\u3002

    First Normal Form \u7b2c\u4e00\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u6ca1\u6709\u91cd\u590d\u7684\u5217\u3002

    \u7b2c\u4e00\u8303\u5f0f\u7684\u542b\u4e49\uff1aatomicity \u539f\u5b50\u6027\u3002\u5373\u4e0d\u80fd\u518d\u7ee7\u7eed\u62c6\u5206\uff0c\u5c5e\u6027\u4e0d\u80fd\u518d\u5411\u4e0b\u62c6\u5206\u3002\u5f53\u4e00\u4e2a\u5173\u7cfb\u6a21\u5f0f R \u7684\u6240\u6709\u5c5e\u6027\u90fd\u662f atomic \u7684\uff0c\u8fd9\u4e2a\u5173\u7cfb\u6a21\u578b\u5c31\u662f\u7b2c\u4e00\u8303\u5f0f\u3002

    \u6bd4\u5982\uff0cstring \u5e94\u5f53\u88ab\u5f53\u4f5c\u4e0d\u53ef\u5206\u5272\u7684\u3002\u6bd4\u5982 ZJU \u7684\u5b66\u53f7\u7b2c\u4e00\u4f4d\u770b\u672c\u79d1\u751f\u7814\u7a76\u751f\uff0c\u540e\u9762\u4e24\u4f4d\u770b\u5e74\u7ea7\uff0c\u4f46\u8fd9\u4e24\u4e2a\u4fe1\u606f\u5982\u679c\u9700\u8981\u662f\u5e94\u5f53\u88ab\u663e\u793a\u5730\u4fdd\u5b58\u5728\u6570\u636e\u5e93\u4e2d\uff0c\u800c\u4e0d\u662f\u9700\u8981\u7684\u65f6\u5019\u53bb\u5b66\u53f7\u4e2d\u5206\u6790\u67e5\u627e\u7684\u3002\u5982\u679c\u8fd9\u6837\u505a\uff0c\u76f8\u5f53\u4e8e\u628a\u89e3\u6790\u5b57\u7b26\u4e32\u7684\u5de5\u4f5c\u7ed9\u4e86\u5e94\u7528\u7a0b\u5e8f\uff0c\u800c\u5b57\u7b26\u4e32\u67e5\u627e\u662f\u4e00\u4e2a\u6bd4\u6570\u636e\u5e93\u67e5\u8be2\u6162\u7684\u6b65\u9aa4\uff0c\u8fd9\u6837\u7ed3\u679c\u5f88\u4e0d\u597d\u3002

    \u7b2c\u4e00\u8303\u5f0f\u6ca1\u6709\u6d88\u9664\u5197\u4f59\uff0c\u5b83\u6d88\u9664\u7684\u662f\u5217\u91cc\u91cd\u590d\u7684\u4fe1\u606f\u3002\u5b83\u628a\u8868\u683c\u91cc\u5197\u4f59\u7684\u5217\u62c6\u5206\u6210\u4e86\u591a\u4e2a\u884c\u3002

    Second Normal Form \u7b2c\u4e8c\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u5b9e\u4f53\u7684\u5c5e\u6027\u5b8c\u5168\u4f9d\u8d56\u4e8e\u4e3b\u5173\u952e\u5b57\u3002

    \u7b2c\u4e8c\u8303\u5f0f\u662f\u57fa\u4e8e fully functional dependency \u5b8c\u5168\u51fd\u6570\u4f9d\u8d56\u7684\u3002\u610f\u601d\u662f\uff0c\u7b2c\u4e8c\u8303\u5f0f\u7528\u4e8e\u90a3\u4e9b\u6709\u590d\u5408\u952e\u503c\u7684\u5173\u7cfb\uff0c\u6bd4\u5982\u5f53\u4e00\u4e2a\u5173\u7cfb\u7684\u4e3b\u952e\u662f\u591a\u4e2a\u5217\u7684\u590d\u5408\u65f6\u3002

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u672c\u6765\u5c31\u6ca1\u6709\u590d\u5408\u7684\u5c5e\u6027\uff0c\u90a3\u672c\u6765\u5c31\u662f 2NF \u7684\u3002

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u6709\u590d\u5408\u7684\u5c5e\u6027\uff0c\u6bd4\u5982 AB -> C\uff0c\u90a3\u4e48 2NF \u4f1a\u628a AB \u62c6\u5f00\u3002

    TODO\uff1a\u600e\u4e48\u62c6\u5462

    Third Normal Form \u7b2c\u4e09\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u4e0d\u4f9d\u8d56\u4e8e\u5176\u5b83\u975e\u5c5e\u6027\u3002

    A relation is in the third normal form, if there is no transitive dependency for non-prime attributes as well as it is in the second normal form.

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u5728\u7b2c\u4e09\u8303\u5f0f\u91cc\uff0c\u5b83\u5e94\u5f53\u5bf9\u4e8e\u975e\u4e3b\u952e\u5c5e\u6027\u6ca1\u6709\u4f20\u9012\u4f9d\u8d56\uff0c\u5e76\u4e14\u5728\u7b2c\u4e8c\u8303\u5f0f\u91cc\u3002

    Boyce-Cudd Normal Form BCNF\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u6bcf\u4e2a\u4f9d\u8d56\u5173\u7cfb\u4e2d\uff0c\u88ab\u4f9d\u8d56\u7684\u90fd\u662f\u4e3b\u952e

    A relation is in BCNF if it is already 3NF, and if for any functional dependency say P->Q, P should be a super key.

    \u6bd4\u8f83 3NF \u548c BCNF \u7684\u533a\u522b\uff1a

    3NF BCNF \u4e0d\u5e94\u6709 \u5f31 \u5f3a \u51cf\u5c11\u4e86\u5197\u4f59 \u4fdd\u7559\u4e86\u6240\u6709\u51fd\u6570\u4f9d\u8d56 \u53ef\u80fd\u6709\u7684\u51fd\u6570\u4f9d\u8d56\u6ca1\u6709\u88ab\u4fdd\u5b58

    Fifth Normal Form \u7b2c\u4e94\u8303\u5f0f

    Sixth Normal Form \u7b2c\u516d\u8303\u5f0f

    \u505a\u9898\u7684\u65f6\u5019\u4f3c\u4e4e\u53ea\u4f1a\u8ba9\u5199\uff1a\u7b26\u5408 1NF \u7684\uff0c3NF \u7684\uff0cBCNF \u7684\u4e09\u79cd\u5206\u89e3\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_4","title":"\u51fd\u6570\u4f9d\u8d56","text":""},{"location":"docs/1-cs/database/normalforms/#_5","title":"\u95ed\u5305","text":""},{"location":"docs/1-cs/database/normalforms/#_6","title":"\u6700\u5c0f\u8986\u76d6","text":""},{"location":"docs/1-cs/database/normalforms/#references","title":"References","text":""},{"location":"docs/1-cs/database/query/","title":"Query Process \u67e5\u8be2\u5904\u7406","text":"

    :material-circle-edit-outline: \u7ea6 1202 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    \u67e5\u8be2\u5904\u7406\u7684\u57fa\u672c\u6b65\u9aa4\u662f\uff1a\uff081\uff09Parsing and translation \u89e3\u6790\u548c\u7ffb\u8bd1 \uff082\uff09Optimization \u4f18\u5316 \uff083\uff09Evaluation \u8bc4\u4f30\u3002

    \u6211\u4eec\u6700\u5173\u6ce8\u7684\u5176\u5b9e\u662f\u4f18\u5316\u6b65\u9aa4\u3002\u4f18\u5316\u4e00\u6b65\u662f\u57fa\u4e8e\u4ee5\u4e0b\u5047\u8bbe\uff1a\u4e00\u79cd SQL \u67e5\u8be2\u53ef\u80fd\u5bf9\u5e94\u4e86\u591a\u79cd\u7b49\u4ef7\u7684\u5173\u7cfb\u4ee3\u6570\u8868\u8fbe\u5f0f\u3002\u53ef\u4ee5\u901a\u8fc7\u4f30\u8ba1\u6bcf\u79cd\u4f18\u5316\u65b9\u6cd5\u7684 cost \u6765\u8bc4\u4f30\u65b9\u6cd5\u7684\u597d\u574f\u3002\u67e5\u8be2\u4f18\u5316\u4f1a\u9009\u62e9\u6700\u8282\u7ea6\u7684\u65b9\u5f0f\u8fdb\u884c\u67e5\u8be2\u3002

    \u90a3\u4e48\u95ee\u9898\u5c31\u89c4\u7ea6\u6210\u4e86\u4ece\u6240\u6709\u7b49\u4ef7\u7684\u5173\u7cfb\u4ee3\u6570\u8868\u8fbe\u5f0f\u4e2d\uff0c\u9009\u62e9 cost \u6700\u5c0f\u7684\u4e00\u4e2a\u3002\u90a3\u4e48\u95ee\u9898\u5c31\u53d8\u6210\u4e86\u5982\u4f55\u8ba1\u7b97 cost\uff01

    Cost is generally measured as total elapsed time for answering query. Many factors contribute to the time cost: disk access + CPU + network communication. \u4f46\u662f\u524d\u9762\u8ba8\u8bba\u8fc7\uff0c\u4e00\u4e2a\u67e5\u8be2\u88ab\u6267\u884c\u7684\u65f6\u5019\u9700\u8981\u88ab\u52a0\u8f7d\u5230\u78c1\u76d8\u4e0a\uff0c\u800c\u78c1\u76d8\u8bfb\u5199\u975e\u5e38\u6162\uff1bCPU \u65f6\u95f4\u53ef\u4ee5\u5ffd\u7565\u4e0d\u8ba1\uff1b\u53ea\u8981\u4e0d\u662f\u7f51\u7edc\u5e94\u7528\u5c31\u4e0d\u7528\u7ba1\u7f51\u7edc\u4f20\u8f93\u5f00\u9500\u3002\u6240\u4ee5\u76ee\u524d\u6211\u4eec\u5173\u6ce8\u7684 cost \u6700\u5927\u7684\u6765\u6e90\u5c31\u662f\u78c1\u76d8\u8bbf\u95ee\u65f6\u95f4\uff0c\u5176\u4e2d\u5305\u542b seek, block read, block write \u7684\u7528\u65f6\u3002\u56e0\u6b64\u5b9a\u4e49\u4ee5\u4e0b cost \u8ba1\u7b97\u65b9\u6cd5\uff1a

    \u5728 B \u4e2a block \u4e2d\u67e5\u8be2 S \u6b21\u7684\u65f6\u95f4 = B * \u8f6c\u79fb\u5230\u4e00\u4e2a block \u7684\u65f6\u95f4 + S * \u4e00\u6b21\u67e5\u8be2\u7684\u65f6\u95f4\u3002

    \u800c\u67e5\u8be2\u4e2d\uff0c\u8bfb\u5199\u8017\u65f6\u66f4\u591a\uff0c\u5176\u4e2d\u5199\u6bd4\u8bfb\u66f4\u8017\u65f6\u3002\u6240\u4ee5\u6211\u4eec\u5e0c\u671b\u67e5\u627e\u548c\u67e5\u8be2\u7684\u65f6\u95f4\u90fd\u66f4\u5c11\u3002

    \uff08TODO\uff1a\u8fd9\u91cc\u8ba1\u7b97\u7684\u65f6\u5019\u8981\u57fa\u4e8e\u4e24\u4e2a\u5047\u8bbe\uff0ccost \u4f9d\u8d56\u4e8e\u4e3b\u5b58\u4e2d\u7f13\u51b2\u533a\u7684\u5927\u5c0f\uff0c\u66f4\u591a\u7684\u5185\u5b58\u53ef\u4ee5\u51cf\u5c11 disk access\uff1b\u53e6\u5916\u901a\u5e38\u8003\u8651\u6700\u574f\u7684\u60c5\u51b5\uff0c\u5373\u4e3b\u5b58\u53ea\u63d0\u4f9b\u6700\u5c11\u7684\u5185\u5b58\u6765\u5b8c\u6210\u67e5\u8be2\u5de5\u4f5c\uff09

    \u63a5\u4e0b\u6765\u6765\u4f30\u8ba1\u5173\u7cfb\u4ee3\u6570\u5404\u4e2a\u64cd\u4f5c\u7684 cost

    Select \u9009\u62e9\u7684 cost \u8ba1\u7b97

    \u6709\u4e09\u79cd select \u7684\u7b97\u6cd5

    Sort \u6392\u5e8f\u7684 cost \u4f30\u8ba1

    sort \u64cd\u4f5c\u4e00\u822c\u4f7f\u7528\u5916\u90e8\u5f52\u5e76\u6392\u5e8f\u3002\u5bf9\u4e8e\u4e00\u4e2a\u5927\u5c0f\u4e3a M \u7684\u5185\u5b58\uff0cb_r \u8868\u793a block \u7684\u6570\u91cf\u3002sort \u5206\u4e3a\u4ee5\u4e0b\u4e24\u4e2a\u6b65\u9aa4\uff1a(1) create sorted runs\uff0c\u6570\u636e\u4ece\u78c1\u76d8\u8bfb\u5165\u5185\u5b58\u4e2d\uff0c\u56e0\u4e3a\u5185\u5b58\u5927\u5c0f\u662f M\uff0c\u6bcf\u6b21\u80fd\u5904\u7406 M \u4e2a\u6570\u636e\u9879 (2) merge the runs\u3002

    \u9700\u8981\u7684 merge pass \u7684\u603b\u6570 \\(\\lceil log_{M-1}(b_r/M) \\rceil\\)\u3002

    \u521b\u5efa\u548c\u6bcf\u6b21 run \u7684\u8fc7\u7a0b\u4e2d disk access \u7684\u6570\u91cf 2br\u3002

    \u5916\u90e8\u6392\u5e8f\u4e2d\u603b\u7684 disk access \u6b21\u6570 \\((2\\lceil log_{M-1}(b_r/M) \\rceil+1)b_r\\)

    Join \u8fde\u63a5\u7684 cost \u4f30\u8ba1

    \u4ee5\u4e0b\u6709\u51e0\u79cd\u5b9e\u73b0 join \u7684\u7b97\u6cd5 (1) nested-loop join (2) block nested-loop join (3) indexed nested-loop join (4) merge-join (5) hash-join\u3002

    \u5bf9\u6bd4\uff1a

    Nested-loop Join: Simple but inefficient for large datasets due to \ud835\udc42 ( \u2223 \ud835\udc45 \u2223 \u00d7 \u2223 \ud835\udc46 \u2223 ) O(\u2223R\u2223\u00d7\u2223S\u2223) complexity. Block Nested-loop Join: Optimized version of nested-loop join that processes blocks to reduce I/O operations. Merge Join: Efficient for sorted relations, with complexity dominated by the sort operations. Hash Join: Very efficient for large datasets, especially when one relation can fit into memory, with \ud835\udc42 ( \u2223 \ud835\udc45 \u2223 + \u2223 \ud835\udc46 \u2223 ) O(\u2223R\u2223+\u2223S\u2223) complexity assuming good hashing.

    Duplicated Deletion \u91cd\u590d\u6d88\u9664

    \u6392\u5e8f\u548c\u6295\u5f71\u53ef\u4ee5\u6d88\u9664\u91cd\u590d

    \u8003\u5f97\u4e0d\u591a\u3002

    Aggregation \u805a\u5408

    \u4e5f\u53ef\u4ee5\u7528\u6392\u5e8f\u6216\u6295\u5f71\u6765\u505a\u3002

    "},{"location":"docs/1-cs/database/query/#query-optimization","title":"Query Optimization \u67e5\u8be2\u4f18\u5316","text":"

    \u5bf9\u7ed9\u5b9a\u67e5\u8be2\uff0c\u4f18\u5316\u7684\u65b9\u6cd5\u6709\uff1a

    !!! TODO \u4e0b\u9762\u7684\u51e0\u4e2a\u4e13\u9898\u7a76\u7adf\u662f\u4ec0\u4e48\u903b\u8f91\u6392\u7684

    "},{"location":"docs/1-cs/database/query/#equivalent-expressions","title":"Equivalent expressions","text":""},{"location":"docs/1-cs/database/query/#statistics-for-cost-estimation","title":"Statistics for Cost Estimation","text":""},{"location":"docs/1-cs/database/transaction/","title":"Transaction \u4e8b\u52a1","text":"

    :material-circle-edit-outline: \u7ea6 1318 \u4e2a\u5b57 :fontawesome-solid-code: 7 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/1-cs/database/transaction/#_1","title":"\u7b80\u4ecb","text":"

    \u4e8b\u52a1\u662f\u7a0b\u5e8f\u6267\u884c\u7684\u57fa\u672c\u5355\u4f4d\uff0c\u4f1a\u5f15\u8d77\u4e00\u4e9b\u6570\u636e\u9879\u7684\u66f4\u65b0\u3002\u6211\u4eec\u5b9a\u4e49\u4e8b\u52a1\u6709\u4ee5\u4e0b\u56db\u4e2a\u57fa\u672c\u5c5e\u6027\uff1a

    \u4e3a\u4e86\u4fdd\u8bc1\u4e8b\u52a1\u7684\u8fd9\u4e9b\u5c5e\u6027\uff0c\u4e00\u822c\u4e3b\u8981\u9700\u8981\u8003\u8651\u4e24\u4e2a\u95ee\u9898\uff1a

    \u4e8e\u662f\uff0c\u6211\u4eec\u8003\u8651\u628a\u4e00\u4e2a\u4e8b\u52a1\u5206\u4e3a\u591a\u4e2a\u72b6\u6001\u6765\u5b8c\u6210\u3002\u4e00\u4e2a\u4e8b\u52a1\u6709\u4e94\u79cd\u72b6\u6001\uff1a

    \u4e00\u4e2a\u8f6c\u5316\u7684\u72b6\u6001\u56fe\u5982\u4e0b

    graph LR\n\nA[[active]] --> P[[Partially commited]]\nP --(single step)--> C[[commited]]\nA --> F[[failed]]\nP --> F\nF --(single step)--> B[[aborted]]\n

    \u6211\u4eec\u4e3b\u8981\u9700\u8981\u4fdd\u8bc1 partially commited \u5230 commited\uff0c\u548c failed \u5230 abort\uff0c\u8fd9\u4e24\u6b65\u90fd\u662f\u539f\u5b50\u6027\u7684\u3002

    "},{"location":"docs/1-cs/database/transaction/#_2","title":"\u8c03\u5ea6","text":"

    \u8fd9\u6837\u5c31\u6d89\u53ca\u5230\u8c03\u5ea6\u6982\u5ff5\u3002Schedules \u8c03\u5ea6\u662f\u4e00\u7cfb\u5217\u7528\u4e8e\u6307\u5b9a\u5e76\u53d1\u4e8b\u52a1\u6267\u884c\u987a\u5e8f\u7684\u6307\u4ee4\u3002\u5b83\u9700\u8981\uff081\uff09\u5305\u542b\u4e8b\u52a1\u4e2d\u7684\u6240\u6709\u6307\u4ee4\uff0c\uff082\uff09\u4fdd\u8bc1\u5355\u4e2a\u4e8b\u52a1\u4e2d\u7684\u6307\u4ee4\u7684\u76f8\u5bf9\u987a\u5e8f\u3002

    \u5982\u679c\u4e8b\u52a1\u662f\u826f\u6784\u7684\u4e14\u662f\u4e24\u9636\u6bb5\u7684\uff0c\u90a3\u4e48\u4efb\u4f55\u4e00\u4e2a\u5408\u6cd5\u7684\u8c03\u5ea6\u90fd\u662f\u9694\u79bb\u7684 \u5177\u4f53\u7684\u6570\u5b66\u63a8\u5230\u8fc7\u7a0b\u53ef\u4ee5\u53c2\u7167<<\u4e8b\u52a1\u5904\u7406:\u6982\u5ff5\u4e0e\u6280\u672f>>\u8fd9\u672c\u4e66\u76847.5.8.2\u8282\u6b64\u4e66\u4e43\u662f\u5173\u4e8e\u6570\u636e\u5e93\u4e8b\u52a1\u7684\u5723\u7ecf\uff0c\u65e0\u9700\u89e3\u91ca(\u4e2d\u6587\u7ffb\u8bd1\u867d\u7136\u6666\u6da9\uff0c\u4e5f\u80fd\u575a\u6301\u8bfb\u4e0b\u53bb,\u5f3a\u70c8\u63a8\u8350

    "},{"location":"docs/1-cs/database/transaction/#_3","title":"\u4e32\u884c","text":"

    \u5982\u679c\u4e00\u4e2a\u8c03\u5ea6\u4e0e\u4e00\u4e2a\u4e32\u884c\u8c03\u5ea6\uff08serial\uff09\u7b49\u4ef7\uff0c\u90a3\u4e48\u79f0\u8fd9\u4e2a\u8c03\u5ea6\u662f serializable \u53ef\u4e32\u884c\u5316\u7684\u3002

    \u53ef\u4e32\u884c\u5316\u5efa\u7acb\u5728\u4e00\u4e2a\u5047\u8bbe\u4e0a\uff1a\u4e8b\u52a1\u4e0d\u4f1a\u7834\u574f\u6570\u636e\u5e93\u7684\u4e00\u81f4\u6027\uff0c\u53ea\u8003\u8651\u6709\u8bfb\u5199\u4e24\u79cd\u64cd\u4f5c\u3002

    \u6211\u4eec\u8bf4\u4e00\u4e2a\u8c03\u5ea6\u662f conflict serializable \u51b2\u7a81\u53ef\u4e32\u884c\u5316\u7684\uff0c\u5f53\uff1a

    "},{"location":"docs/1-cs/database/transaction/#-","title":"-","text":""},{"location":"docs/1-cs/database/transaction/#_4","title":"\u5e76\u53d1\u5904\u7406","text":"

    \u540c\u65f6\u6267\u884c\u591a\u4e2a\u4e8b\u52a1\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8fd0\u884c\u7684\u6548\u7387\uff0c\u51cf\u5c11\u5e73\u5747\u6267\u884c\u65f6\u95f4\u3002

    \u5e76\u53d1\u63a7\u5236\u7684\u5904\u7406\u673a\u5236\u662f\uff0c\u8ba9\u5e76\u53d1\u7684\u4e8b\u52a1\u72ec\u7acb\u8fdb\u884c\uff0c\u63a7\u5236\u5e76\u53d1\u7684\u4e8b\u52a1\u4e4b\u95f4\u7684\u4ea4\u6d41\u3002

    "},{"location":"docs/1-cs/database/transaction/#_5","title":"\u6545\u969c\u6062\u590d","text":"

    \u6545\u969c\u7684\u79cd\u7c7b\u6709\uff1a

    checkpoint

    Recovery algorithms are techniques to ensure database consistency and transaction atomicity and durability despite failures. \u6545\u969c\u6062\u590d\u7b97\u6cd5\u5c31\u662f\u4fdd\u969c\u6570\u636e\u5e93 ACD\uff08\u4e0d\u77e5\u9053\u4e3a\u4ec0\u4e48\u6ca1\u6709 I\uff09\u7279\u6027\u7684\u65b9\u6cd5\u3002

    \u6545\u969c\u6062\u590d\u7b97\u6cd5\u6709\u4e24\u4e2a\u90e8\u5206\uff1a

    \u6545\u969c\u6062\u590d\u7b97\u6cd5\u5177\u6709 Idempotent(\u5e42\u7b49\u6027): An recovery algorithm is said to be idempotent if executing it several times gives the same result as executing it once. \u610f\u601d\u662f\u7b97\u6cd5\u6062\u590d\u591a\u6b21\u7684\u6548\u679c\u662f\u4e00\u6837\u7684\uff0c\u56e0\u4e3a\u6062\u590d\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u4e5f\u53d1\u751f crash\u3002

    Log-based Recovery \u57fa\u4e8e\u65e5\u5fd7\u7684\u6062\u590d\u6cd5

    log records \u65e5\u5fd7\u8bb0\u5f55\uff1a

    \u65e5\u5fd7\u8bb0\u5f55\u662f\u8bb0\u5f55\u5728 stable storage\uff08\u7a33\u5b9a\u5b58\u50a8\u5668\uff09\u4e0a\u7684\uff0c\u4e00\u7cfb\u5217\u8bb0\u5f55\u6570\u636e\u5e93\u600e\u6837\u88ab\u6210\u529f\u4fee\u6539\u7684\u4fe1\u606f\u3002log \u7531\u4e00\u4e32 log records \u7ec4\u6210\u3002\u5b83\u6709\u4ee5\u4e0b\u51e0\u79cd\u683c\u5f0f

    checkpoint \u4e4b\u95f4\u7684\u95f4\u9694\u5e94\u5f53\u901a\u8fc7\u65e5\u5fd7\u91cf\u6765\u786e\u5b9a\u3002

    \u4e24\u79cd\u7b56\u7565 - Redo:

    In the redo phase, the system replays updates of all transactions by scaning the log forward from the last checkpoint. The log records that are replayed include log records for transactions that were rolled back befored system crash, and those that had not committed when the system crash occurred. \n\u5728 redo \u9636\u6bb5\u91cc\uff0c\u7cfb\u7edf\u6839\u636e\u91cd\u65b0\u626b\u63cf\u4e0a\u4e00\u6b21 checkpoint \u4e4b\u540e\u7684\u6240\u6709\u8bb0\u5f55\uff0c\u91cd\u65b0\u6267\u884c\u4e0a\u4e00\u6b21 checkpoint \u4e4b\u540e\u7684\u6240\u6709 transaction\u3002\u8fd9\u91cc\u7684 log \u8bb0\u5f55\u5305\u62ec\u5728 crash \u4e4b\u524d\u6b63\u5728\u56de\u6eda\u7684\u90a3\u4e9b\u8bb0\u5f55\uff0c\u4e5f\u5305\u62ec crash \u65f6\u8fd8\u6ca1\u6709\u63d0\u4ea4\u7684\u90a3\u4e9b\u8bb0\u5f55\u3002Redo \u9636\u6bb5\u4e5f\u4f1a\u5224\u65ad\u6240\u6709 transaction \u662f\u5426\u5b8c\u6210\u4e86\uff0c\u662f\u5426\u9700\u8981 roll back\u3002\u6ca1\u5b8c\u6210\u7684 transaction \u4f1a\u88ab\u6807\u8bb0\u4e3a\u6216\u8005 \\<Ti abort\\> \u6216\u8005 \\<Ti commit\\> \u7684\u6807\u8bb0\u3002\u5177\u4f53\u6765\u8bf4\u6267\u884c\u7684\u6b65\u9aa4\u6709\u4e0b\u9762\u51e0\u6761\uff1a\n\n-\n
    "},{"location":"docs/1-cs/database/xml/","title":"XML \u6587\u4ef6","text":"

    :material-circle-edit-outline: \u7ea6 14 \u4e2a\u5b57

    "},{"location":"docs/1-cs/database/xml/#_1","title":"\u5b9a\u4e49\u548c\u57fa\u672c\u7ed3\u6784","text":""},{"location":"docs/1-cs/database/xml/#document-schema","title":"Document Schema","text":""},{"location":"docs/1-cs/database/xml/#_2","title":"\u67e5\u8be2","text":""},{"location":"docs/1-cs/oop/course/","title":"Courses \u542c\u8bfe","text":"

    :material-circle-edit-outline: \u7ea6 1567 \u4e2a\u5b57 :fontawesome-solid-code: 91 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f

    "},{"location":"docs/1-cs/oop/course/#cs106bcs106l","title":"\u5173\u4e8eCS106B\u548cCS106L","text":"

    CS106B\u504f\u7b80\u5355\uff0c\u76f8\u5f53\u4e8eZJU\u7684\u6570\u636e\u7ed3\u6784+C++\u7684STL\u7528\u6cd5\u4e00\u5757\u8bb2\uff0c\u53e6\u5916\u518d\u8bb2\u4e00\u4e9bFDS\u7684\u7b97\u6cd5\u3002 CS106L\u662f\u4e13\u95e8\u8bb2C++\u8fdb\u9636\u7279\u6027\u7684\u3002

    \u56e0\u4e3a\u5728\u542cCS106B\u4e4b\u524d\u5b66\u8fc7FDS\uff0cCS106B\u82b1\u4e00\u5929\u901f\u901a\u4e86\u4e00\u4e0b\uff0c\u91cd\u590d\u5185\u5bb9\u6709\u70b9\u591a\uff0c\u622a\u4e0b\u4e86\u4e00\u5e45\u56fe\u3002

    CS106L\u63d0\u4f9b\u7684C++\u5b66\u4e60\u8def\u7ebf\u56fe

    "},{"location":"docs/1-cs/oop/course/#zju","title":"ZJU\u8bfe\u7a0b","text":""},{"location":"docs/1-cs/oop/course/#_1","title":"\u8bfe\u7a0b\u53c2\u8003\u8d44\u6599","text":"

    CPP Reference Standard C++ CppCon

    "},{"location":"docs/1-cs/oop/course/#_2","title":"\u4e0a\u8bfe\u5fc3\u5f97","text":"

    \u6211\u8ddf\u7684\u662fcx\u8001\u5e08\u7684\u73ed\uff0c\u5e94\u8be5\u662f\u6559\u5f97\u6700\u597d\u7684\u4e00\u6863orz \u4f46\u662f\u4e0a\u8bfe\u5185\u5bb9\u4ecd\u4e0d\u80fd\u8986\u76d6\u4f5c\u4e1a\u548c\u671f\u672b\u7684\u5185\u5bb9\uff0c\u89c9\u5f97\u542c\u8bfe\u5185\u5bb9\u53ea\u80fd\u8d77\u5230\u4e00\u4e2a\u9aa8\u67b6\u4f5c\u7528\uff0c\u8bfe\u540e\u9700\u8981\u82b1\u4e0a\u8bfe2\u81f33\u500d\u7684\u65f6\u95f4\u81ea\u5b66\u81ea\u5df1\u6574\u7406\u7b14\u8bb0\uff0c\u591a\u8bfb\u591a\u5199\u4ee3\u7801\uff0c\u4e0d\u7136\u671f\u672b\u4f1a\u9047\u5230\u6ca1\u89c1\u8fc7\u7684\u7279\u6027\uff0c\u4f1a\u6709\u70b9\u60e8orz\uff08\u50cf\u6211\u4e00\u6837\uff09

    "},{"location":"docs/1-cs/oop/course/#_3","title":"\u9762\u5411\u5bf9\u8c61\u56db\u5927\u7279\u6027","text":""},{"location":"docs/1-cs/oop/course/#_4","title":"\u7c7b\u548c\u5bf9\u8c61/\u6784\u9020\u51fd\u6570\u548c\u6790\u6784\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#class-struct","title":"class \u4e0e struct \u7684\u6bd4\u8f83","text":""},{"location":"docs/1-cs/oop/course/#_5","title":"\u7c7b\u7684\u7ed3\u6784\uff1a\u6570\u636e\u6210\u5458\u548c\u6210\u5458\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#_6","title":"\u7c7b\u7684\u58f0\u660e\u683c\u5f0f","text":"
    class Name\n{\n    public:\n        public_data;\n        public_functions;\n    protected:\n        protected_data;\n        protected_functions;\n    private:\n        private_data;\n        private_functions;\n}\n
    "},{"location":"docs/1-cs/oop/course/#_7","title":"\u4e60\u60ef","text":""},{"location":"docs/1-cs/oop/course/#_8","title":"\u7c7b\u5916\u5b9a\u4e49","text":"

    \u8fd4\u56de\u7c7b\u578b \u7c7b\u540d::\u6210\u5458\u51fd\u6570\u540d\uff08\u53c2\u6570\u8868\uff09 { // \u51fd\u6570\u4f53 }

    "},{"location":"docs/1-cs/oop/course/#_9","title":"\u5185\u8054\u51fd\u6570\u548c\u5916\u8054\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#_10","title":"\u5bf9\u8c61","text":"

    \u53ef\u4ee5\u628a\u76f8\u540c\u6570\u636e\u7ed3\u6784\u548c\u76f8\u540c\u64cd\u4f5c\u96c6\u7684\u5bf9\u8c61\u770b\u4f5c\u5c5e\u4e8e\u540c\u4e00\u7c7b\u3002\u5bf9\u8c61\u662f\u7c7b\u7684\u5b9e\u4f8b\u3002

    "},{"location":"docs/1-cs/oop/course/#_11","title":"\u5bf9\u8c61\u7684\u5b9a\u4e49","text":""},{"location":"docs/1-cs/oop/course/#_12","title":"\u5bf9\u8c61\u4e2d\u6210\u5458\u7684\u8bbf\u95ee","text":"

    \u5bf9\u8c61\u540d.\u6570\u636e\u6210\u5458\u540d\uff08\u662f \u5bf9\u8c61\u540d.\u7c7b\u540d::\u6210\u5458\u540d \u7684\u7f29\u5199\uff09 \u5bf9\u8c61\u540d.\u6210\u5458\u51fd\u6570\u540d\uff08\u53c2\u6570\u8868\uff09 

    class Sample\n{\npublic:\nint k;\nint geti(){return i;}\nint getj(){return j;}\nint getk(){return k;}\nprivate:\nint i;\nprotected:\nint j;\n};\nint main()\n{\nSample a;\na.i;        // \u975e\u6cd5\na.j:        // \u975e\u6cd5\na.k;        // \u5408\u6cd5\n}\n

    "},{"location":"docs/1-cs/oop/course/#_13","title":"\u7c7b\u7684\u4f5c\u7528\u57df","text":""},{"location":"docs/1-cs/oop/course/#_14","title":"\u6784\u9020\u51fd\u6570\u4e0e\u6790\u6784\u51fd\u6570","text":"

    \u7c7b\u7684\u6784\u9020\u51fd\u6570\u662f\u7c7b\u7684\u4e00\u4e2a\u7279\u6b8a\u6210\u5458\u51fd\u6570\uff0c\u6ca1\u6709\u8fd4\u56de\u7c7b\u578b\uff08\u4e0d\u662fvoid\uff09\uff0c\u53ef\u4ee5\u6709\u53c2\u6570\uff0c\u51fd\u6570\u540d\u548c\u7c7b\u540d\u4e00\u6837\u3002\u5f53\u521b\u5efa\u7c7b\u7684\u4e00\u4e2a\u65b0\u5bf9\u8c61\u65f6\uff0c\u81ea\u52a8\u8c03\u7528\u6784\u9020\u51fd\u6570\uff0c\u5b8c\u6210\u521d\u59cb\u5316\u5de5\u4f5c\u3002

    "},{"location":"docs/1-cs/oop/course/#namespace","title":"Namespace","text":""},{"location":"docs/1-cs/oop/course/#namespace_1","title":"\u4ec0\u4e48\u662fnamespace\uff1f","text":"

    \u662f\u5355\u4e00\u7684\u5168\u5c40\u540d\u5b57\u7a7a\u95f4\u3002\u9632\u6b62\u5728\u4e00\u4e2a\u7a7a\u95f4\u4e2d\u76f8\u540c\u7684\u540d\u5b57\u5f15\u8d77\u51b2\u7a81\u3002 \u4f8b\u5b50\uff1a 

    namespace myown1\n{\nstring user_name = \"myown1\";\n}\nnamespace myown2\n{\nstring user_name = \"myown2\";\n}\nint main()\n{\n// using namespace myown1; \ncout << \"\\\\n\" << \"Hello, \"\n<< myown1::user_name\n<< \"...and goodbye!\\\\n\"\ncout << \"\\\\n\" << \"Hello, \"\n<< myown2::user_name\n<< \"...and goodbye!\\\\n\"\nreturn 0;\n}\n

    \u5173\u952e\u8bcdusing\u5c06\u4e00\u4e2a\u540d\u5b57\u7a7a\u95f4\u53d8\u4e3a\u53ef\u89c1\uff0c\u4e0d\u4f1a\u8986\u76d6\u5f53\u524d\u7684namespace\u3002

    "},{"location":"docs/1-cs/oop/course/#_15","title":"\u7ee7\u627f\u4e0e\u6d3e\u751f\u7c7b","text":" \u76ee\u7684 \u4ee3\u7801\u7684\u91cd\u7528\u548c\u4ee3\u7801\u7684\u6269\u5145 \u7ee7\u627f\u79cd\u7c7b \u5355\u7ee7\u627f/\u591a\u7ee7\u627f \u7ee7\u627f\u5185\u5bb9 \u9664\u6784\u9020\u51fd\u6570/\u6790\u6784\u51fd\u6570/\u79c1\u6709\u6210\u5458\u5916\u7684\u6240\u6709\u6210\u5458"},{"location":"docs/1-cs/oop/course/#_16","title":"\u7ee7\u627f\u7684\u8bbf\u95ee\u63a7\u5236","text":"

    \u6d3e\u751f\u7c7b\u7ee7\u627f\u4e86\u57fa\u7c7b\u4e2d\u9664\u6784\u9020\u51fd\u6570\u548c\u6790\u6784\u51fd\u6570\u4e4b\u5916\u7684\u6240\u6709\u6210\u5458\u3002\u6d3e\u751f\u7c7b\u7684\u6210\u5458\u5305\u62ec\uff1a - \u7ee7\u627f\u57fa\u7c7b\u7684\u6210\u5458 - \u6d3e\u751f\u7c7b\u5b9a\u4e49\u65f6\u58f0\u660e\u7684\u6210\u5458

    \u4ece\u5df2\u6709\u7c7b\u6d3e\u751f\u51fa\u65b0\u7c7b\u65f6\uff0c\u53ef\u4ee5\u5728\u6d3e\u751f\u7c7b\u5185\u5b8c\u6210\u4ee5\u4e0b\u51e0\u79cd\u529f\u80fd\uff1a - \u589e\u52a0\u65b0\u7684\u6570\u636e\u6210\u5458 - \u589e\u52a0\u65b0\u7684\u6210\u5458\u51fd\u6570 - \u91cd\u65b0\u5b9a\u4e49\u57fa\u7c7b\u4e2d\u5df2\u6709\u7684\u6210\u5458\u51fd\u6570 - \u53ef\u4ee5\u6539\u53d8\u73b0\u6709\u6210\u5458\u7684\u5c5e\u6027

    \u58f0\u660e\u4e00\u4e2a\u6d3e\u751f\u7c7b\u7684\u4e00\u822c\u683c\u5f0f 

    class \u6d3e\u751f\u7c7b\u540d:\u7ee7\u627f\u65b9\u5f0f \u57fa\u7c7b\u540d\n{\n// \u6d3e\u751f\u7c7b\u65b0\u589e\u7684\u6570\u636e\u6210\u5458\u548c\u6210\u5458\u51fd\u6570\n};\n

    \u4e09\u79cd\u7ee7\u627f\u65b9\u5f0f 

    class employee: public person\n{};\n// default\nclass employee: private person\n{};\nclass employee: protected person\n{};\n

    \u57fa\u7c7b\u6210\u5458\u5728\u6d3e\u751f\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027

    \u5728\u57fa\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027 \u7ee7\u627f\u65b9\u5f0f \u5728\u6d3e\u751f\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027 \u89e3\u91ca private public inaccessible \u57fa\u7c7b\u4e2dprivate\u7684\u5bf9\u8c61\u5728\u7c7b\u5916\u5f53\u7136\u4e0d\u53ef\u8bbf\u95ee private private inaccessible private protected inaccessible public public public \u57fa\u7c7b\u4e0d\u7ba1 public private private public protected protected protected public protected \u6743\u9650\u4f1a\u88ab\u7ee7\u627f\u65b9\u5f0f\u7f29\u5c0f\u800c\u4e0d\u4f1a\u653e\u5927 protected private private protected protected protected

    \u6d3e\u751f\u7c7b\u5bf9\u57fa\u7c7b\u7684\u8bbf\u95ee\u89c4\u5219 - \u5185\u90e8\u8bbf\u95ee\uff1a\u7531\u6d3e\u751f\u7c7b\u4e2d\u65b0\u589e\u6210\u5458\u5bf9\u57fa\u7c7b\u7ee7\u627f\u6765\u7684\u6210\u5458\u7684\u8bbf\u95ee\u3002 - \u5bf9\u8c61\u8bbf\u95ee\uff1a\u5728\u6d3e\u751f\u7c7b\u5916\u90e8\uff0c\u901a\u8fc7\u6d3e\u751f\u7c7b\u7684\u5bf9\u8c61\u5bf9\u4ece\u57fa\u7c7b\u7ee7\u627f\u6765\u7684\u6210\u5458\u7684\u8bbf\u95ee\u3002

    \u57fa\u7c7b\u6210\u5458 private\u6210\u5458 public\u6210\u5458 protected\u6210\u5458 \u5185\u90e8\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u53ef\u8bbf\u95ee \u53ef\u8bbf\u95ee \u5bf9\u8c61\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee

    \u79c1\u6709\u7ee7\u627f\u4e3e\u4f8b 

    class Point\n{\npublic:\nvoid InitP(float x = 0, float y = 0)\n{\nthis->X = x;\nthis->Y = y;\n}\nvoid Move(float offX, float offY)\n{\nX += offX;\nY += offY;\n}\nfloat GetX() const{return X;}\nfloat GetY() const{return Y;}\nprivate:\nfloat X, Y;\n};\nclass Rectangle: private Point // \u6d3e\u751f\u7c7b\u58f0\u660e\n{\npublic: //\u65b0\u589e\u5916\u90e8\u63a5\u53e3\nvoid InitR(float x, float y, float w, float h)\n{\nInitR(x, y);\nW = w;\nH = h;\n} // \nvoid Move(float xOff, float yOff)\n{\nPoint::\n}\n}\n

    "},{"location":"docs/1-cs/oop/final_review/","title":"ZJU \u671f\u672b\u590d\u4e60","text":"

    :material-circle-edit-outline: \u7ea6 1500 \u4e2a\u5b57 :fontawesome-solid-code: 36 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 5 \u5206\u949f

    \u9762\u5411\u671f\u672b\u9898\u7684\u76f8\u4f3c\u77e5\u8bc6\u70b9\u805a\u7c7b

    "},{"location":"docs/1-cs/oop/final_review/#_1","title":"\u6784\u9020\u987a\u5e8f","text":"

    \uff081\uff09main\u51fd\u6570\u4ee5\u5916\u7684\u5bf9\u8c61\uff0c\u5168\u5c40\u7c7b\u5b9a\u4e49\u540e\u76f4\u63a5\u5b9a\u4e49\u7684\u7c7b\u5bf9\u8c61 \uff082\uff09main\u51fd\u6570\u5185\u7684\u5bf9\u8c61 \uff083\uff09\u7236\u7c7b\u6784\u9020 \uff084\uff09\u5b50\u7c7b\u7c7b\u6210\u5458 \uff085\uff09\u5b50\u7c7b\u6784\u9020 \u6790\u6784\u987a\u5e8f\u76f8\u53cd

    "},{"location":"docs/1-cs/oop/final_review/#_2","title":"\u4ec0\u4e48\u65f6\u5019\u751f\u6210\u9ed8\u8ba4\u6784\u9020\u51fd\u6570\uff1f","text":"

    \u5982\u679c\u5df2\u7ecf\u6709\u6784\u9020\u51fd\u6570\uff0c\u7f16\u8bd1\u5668\u4e0d\u4f1a\u751f\u6210\u9ed8\u8ba4\u6784\u9020\u51fd\u6570 \u6ca1\u6709\u7684\u65f6\u5019\u4e5f\u4e0d\u4e00\u5b9a\u4f1a\u751f\u6210 \u9700\u8981\u7528\u624d\u751f\u6210

    "},{"location":"docs/1-cs/oop/final_review/#_3","title":"\u91cd\u8f7d\u89c4\u5219","text":"

    \u4e0d\u80fd\u91cd\u8f7d\u7684\u6709\uff1a - \u4f5c\u7528\u57df\u64cd\u4f5c\u7b26:: - \u6761\u4ef6\u64cd\u4f5c\u7b26?:\uff08\u5e94\u8be5\u662f\u95ee\u53f7\u8868\u8fbe\u5f0f\uff1f\uff09 - \u70b9\u64cd\u4f5c\u7b26\u3001\u7c7b\u6210\u5458\u6307\u9488 - \u9884\u5904\u7406\u7b26\u53f7#

    \u53ea\u80fd\u91cd\u8f7d\u4e3a\u53cb\u5143\u4e0d\u80fd\u6210\u5458\u51fd\u6570\uff1a - <<\u548c>> \u539f\u56e0\u662f\u6210\u5458\u51fd\u6570\u91cd\u8f7d\uff0c\u53ea\u80fd\u5e26\u4e00\u4e2a\u53c2\u6570\uff0clhs\u5fc5\u987b\u662f\u6210\u5458\u81ea\u8eab

    \u4f46\u662f\u6d41\u64cd\u4f5c\u7b26\u5de6\u8fb9\u662fcin\u6216cout\uff0c\u91cd\u8f7d\u4e3a\u53cb\u5143\u51fd\u6570\u65f6\uff0c\u53ef\u4ee5\u6bd4\u6210\u5458\u51fd\u6570\u591a\u8bf4\u660e\u4e00\u4e2a\u5f62\u53c2\u505alhs

    \u91cd\u8f7d\u548c\u91cd\u5199\u90fd\u662f\u591a\u6001\uff1a \u91cd\u8f7d\uff1a\u8fd0\u884c\u65f6\u591a\u6001 \u91cd\u5199\uff1a\u7f16\u8bd1\u65f6\u591a\u6001

    static\u548cvirtual\u53ea\u80fd\u6709\u4e00\u4e2a

    \u6790\u6784\u51fd\u6570\u4e0d\u80fd\u5e26\u53c2\u6570

    "},{"location":"docs/1-cs/oop/final_review/#_4","title":"\u5b50\u7c7b\u548c\u7236\u7c7b\u6307\u9488","text":""},{"location":"docs/1-cs/oop/final_review/#static_castdynamic_cast","title":"static_cast\u548cdynamic_cast","text":""},{"location":"docs/1-cs/oop/final_review/#_5","title":"\u5f15\u7528","text":"

    \u4ec0\u4e48\u65f6\u5019\u5fc5\u987b\u7528\u5e38\u5f15\u7528\uff08const &\uff09\uff1a\u5f15\u7528\u578b\u53c2\u6570\u5e94\u5f53\u5728\u80fd\u5b9a\u4e49\u4e3aconst\u7684\u60c5\u51b5\u4e0b\u5c3d\u91cf\u5b9a\u4e49\u4e3aconst\u3002

    \u4f7f\u7528\u5f15\u7528\u7684\u4e3b\u8981\u539f\u56e0\uff1a \u7a0b\u5e8f\u80fd\u591f\u4fee\u6539\u8c03\u7528\u51fd\u6570\u4e2d\u7684\u6570\u636e\u5bf9\u8c61 \u901a\u8fc7\u4f20\u9012\u5f15\u7528\u800c\u4e0d\u662f\u6574\u4e2a\u6570\u636e\u5bf9\u8c61\uff0c\u53ef\u4ee5\u63d0\u9ad8\u7a0b\u5e8f\u7684\u8fd0\u884c\u901f\u5ea6

    \u53ea\u4f7f\u7528\u4f20\u9012\u8fc7\u6765\u7684\u503c\u800c\u4e0d\u4fee\u6539 \u9700\u8981\u4fee\u6539\u4f20\u9012\u8fc7\u6765\u7684\u503c \u5185\u7f6e\u6570\u636e\u7c7b\u578b\uff08\u5c0f\u578b\u7ed3\u6784\uff09 \u6309\u503c\u4f20\u9012 \u6307\u9488\u4f20\u9012 \u6570\u7ec4 \u6307\u9488\u4f20\u9012 \u6307\u9488\u4f20\u9012 \u8f83\u5927\u7684\u7ed3\u6784\uff09 \u6307\u9488\u6216\u5f15\u7528 \u6307\u9488\u6216\u5f15\u7528 \u7c7b/\u5bf9\u8c61 \u5f15\u7528\u4f20\u9012 \u5f15\u7528\u4f20\u9012

    \u5f15\u7528\u548c\u6307\u9488\u7684\u533a\u522b\uff1a \u53ef\u4ee5\u628a\u5f15\u7528\u7406\u89e3\u6210\u4e00\u4e2a\u5e38\u91cf\u6307\u9488\uff0c\u56e0\u6b64\u5f15\u7528\u58f0\u660e\u65f6\u5c31\u5fc5\u987b\u521d\u59cb\u5316\uff0c\u4e00\u7ecf\u58f0\u660e\u4e0d\u80fd\u518d\u548c\u5176\u5b83\u5bf9\u8c61\u7ed1\u5b9a\u3002

    Copy constructor must pass its first argument by reference

    "},{"location":"docs/1-cs/oop/final_review/#_6","title":"\u7c7b\u5185\u9759\u6001\u6210\u5458\u7684\u521d\u59cb\u5316","text":"

    const static\u53ef\u4ee5\u5728\u7c7b\u5185\u76f4\u63a5\u521d\u59cb\u5316\uff0c\u975econst static\u6210\u5458\u9700\u8981\u5728\u7c7b\u5916\u521d\u59cb\u5316\u3002

    \u53ef\u4ee5\u8c03\u7528\u9ed8\u8ba4\u521d\u59cb\u5316A::n\uff0c\u81ea\u52a8\u521d\u59cb\u5316\u4e3a0\u3002\u6b64\u65f6\u8c03\u7528\u9ed8\u8ba4\u6784\u9020\u4e0d\u80fd\u7528n()\uff0c\u5426\u5219\u8ba4\u4e3a\u662f\u4e2a\u51fd\u6570\u3002\u6216\u8005\u5e26\u521d\u59cb\u503c\u521d\u59cb\u5316A::n(9)

    static\u548cconst - \u6ca1\u6709static\u5c31\u662fconst\u7684\u8bf4\u6cd5

    const\u7684\u51e0\u79cd\u5f62\u5f0f 

    const int& fun(int& a); // \u4fee\u9970\u8fd4\u56de\u503c \nint& fun(const int& a); // \u4fee\u9970\u5f62\u53c2 \nint& fun(int& a) const {} // const\u6210\u5458\u51fd\u6570\n

    const\u8fd4\u56de\u503c\uff1a\u662f\u4fee\u9970\u8fd4\u56de\u503c\u5f15\u7528\u7c7b\u578b\u7684\u65f6\u5019\uff0c\u4e3a\u4e86\u907f\u514d\u8fd4\u56de\u503c\u88ab\u4fee\u6539\u7684\u60c5\u51b5

    \u8fd4\u56de\u503c\u662f\u5f15\u7528\u7684\u51fd\u6570\uff0c\u8fd9\u4e2a\u5f15\u7528\u5fc5\u7136\u4e0d\u662f\u4e34\u65f6\u5bf9\u8c61\u7684\u5f15\u7528\uff0c\u4e00\u5b9a\u662f\u6210\u5458\u53d8\u91cf\u6216\u8005\u51fd\u6570\u53c2\u6570\u3002\uff08\u53ea\u8981\u53c2\u6570\u4e0d\u9700\u8981\u4fee\u6539\u4e00\u5b9a\u52a0\u4e0aconst\uff09

    const\u53c2\u6570\u5fc5\u987b\u4f20\u7b7e\u540d\u540e\u5e26const\u7684\u51fd\u6570\uff1a\u8981\u628athis\u6307\u9488\u53d8\u6210const

    \u600e\u6837\u6784\u6210\u91cd\u8f7d - \u4e0d\u91cd\u8f7d\u7684 

    const int& fun(int& a); // \u53c2\u6570\u5217\u8868\u6ca1\u6709\u53d8 \nint& fun(const int a); // \u56e0\u4e3a\u662f\u503c\u4f20\u9012\uff0c\u4e0d\u662fconst\u7684\u4e5f\u80fdtype conversion\n

    "},{"location":"docs/1-cs/oop/final_review/#inline-function","title":"inline function","text":"

    \u4ee3\u66ff\u5b8f\u7684\u4e00\u79cd\u64cd\u4f5c\uff0c\u5728\u7f16\u8bd1\u9636\u6bb5\u628a\u6240\u6709\u51fd\u6570\u540d\u66ff\u6362\u6210inline function\u7684\u5b9e\u73b0 \u6bd4\u51fd\u6570\u7684\u4f18\u70b9\uff1a\u4e0d\u7528\u9891\u7e41\u8fdb\u6808\u51fa\u6808 \u6bd4\u5b8f\u7684\u4f18\u70b9\uff1a\u6709\u7c7b\u578b\u68c0\u67e5\uff0c\u80fd\u5199\u591a\u884c\uff0c\u80fd\u64cd\u4f5c\u7c7b\u7684\u79c1\u6709\u6210\u5458 inline\u5173\u952e\u5b57\u53ea\u6709\u51fa\u73b0\u5728\u51fd\u6570\u7684\u5b9a\u4e49\u800c\u4e0d\u662f\u58f0\u660e\u524d\u65f6\u624d\u6709\u7528\u3002 \u9759\u6001\u7ed1\u5b9a\u00a0Static\u00a0Binding \u3002\u80fd\u591f\u660e\u786e\u8fd0\u884c\u7684\u662f\u54ea\u4e2a\u7c7b\u7684\u65b9\u6cd5\u65f6\u4f1a\u53d1\u751f\u9759\u6001\u7ed1\u5b9a \u3002\u53d1\u751f\u5728\u7f16\u8bd1\u65f6\u523b\uff0c\u6240\u4ee5\u53c8\u53eb\u65e9\u7ed1\u5b9a \u52a8\u6001\u7ed1\u5b9aDynamic\u00a0Binding \u3002\u51fa\u73b0\u591a\u6001\uff0c\u7f16\u8bd1\u5668\u4e0d\u80fd\u660e\u786e\u5230\u5e95\u4f7f\u7528\u54ea\u4e2a\u7c7b\u7684\u65b9\u6cd5\u65f6\u53d1\u751f\u52a8\u6001\u7ed1\u5b9a \u3002\u53d1\u751f\u5728\u8fd0\u884c\u65f6\u523b\uff0c\u6240\u4ee5\u53c8\u53eb\u665a\u7ed1\u5b9a \u3002\u53ea\u6709\u5b58\u5728\u00a0virtual\u00a0\u65e6\u901a\u8fc7\u6307\u9488\u8bbf\u95ee\u65f6\uff0c\u624d\u4f1a\u53d1\u751f\u52a8\u6001\u7ed1\u5b9a

    static binding \u7f16\u8bd1\u65f6 

    class Animal { public: void eat() { cout << \"Animal eats\" << endl; } }; class Dog : public Animal { public: void eat() { cout << \"Dog eats\" << endl; } };\n

    dynamic binding \u8fd0\u884c\u65f6 

    class Animal { public: virtual void eat() { cout << \"Animal eats\" << endl; } }; class Dog : public Animal { public: void eat() { cout << \"Dog eats\" << endl; } };\n
    \u200b

    \u5728\u4e0b\u9762\u7684\u60c5\u51b5\u4e0b\uff0c\u6784\u9020\u51fd\u6570\u4f1a\u88ab\u8c03\u7528\uff1a - \u5bf9\u4e8e\u5168\u5c40\u5bf9\u8c61\uff0c\u5728main()\u4e24\u6570\u8fd0\u884c\u4e4b\u524d\uff0c\u6216\u8005\u5728\u540c\u4e00\u4e2a\u7f16\u8bd1\u5355\u5143\u5185\u5b9a\u4e49\u7684\u4efb\u4e00\u51fd\u6570\u6216\u5bf9\u8c61 \u88ab\u4f7f\u7528\u4e4b\u524d\u3002\u5728\u540c\u4e00\u4e2a\u7f16\u8bd1\u5355\u5143\u5185\uff0c\u5b83\u4eec\u7684\u6784\u9020\u4e24\u6570\u6309\u7167\u58f0\u660e\u7684\u987a\u5e8f\u521d\u59cb\u5316\u3002 - \u5bf9\u4e8e static\u00a0local\u00a0variables\uff0c\u00a0\u5728\u7b2c\u4e00\u6b21\u8fd0\u884c\u5230\u5b83\u7684\u58f0\u660e\u7684\u65f6\u5019. - \u5bf9\u4e8e automatic\u00a0storage\u00a0duration\u00a0\u7684\u5bf9\u8c61\uff0c\u5728\u5176\u58f0\u660e\u88ab\u8fd0\u884c\u65f6\u3002 - \u5bf9\u4e8e dynamic\u00a0storage\u00a0duration\u00a0\u7684\u5bf9\u8c61\uff0c\u5728\u5176\u7528\u00a0new\u00a0\u8868\u8fbe\u5f0f\u521b\u5efa\u65f6\u3002

    "},{"location":"docs/1-cs/oop/final_review/#_7","title":"\u667a\u80fd\u6307\u9488","text":"
    std::unique_ptr<T> //\u72ec\u5360\u8d44\u6e90\u6240\u6709\u6743\u7684\u6307\u9488\u3002 \nstd::shared_ptr<T> //\u5171\u4eab\u8d44\u6e90\u6240\u6709\u6743\u7684\u6307\u9488\u3002 \nstd::weak_ptr<T> //\u5171\u4eab\u8d44\u6e90\u7684\u89c2\u5bdf\u8005\uff0c\u9700\u8981\u548cstd::shared_ptr \u4e00\u8d77\u4f7f\u7528\uff0c\u4e0d\u5f71\u54cd\u8d44\u6e90\u7684\u751f\u547d\u5468\u671f\u3002\n

    \u4f7f\u7528\u88f8\u6307\u9488 \u6240\u4ee5\u9ed8\u8ba4\u53c2\u6570\u662f\u548c\u865a\u8868\u65e0\u5173\u4e0e\u5f53\u524d\u7c7b\u578b\u6709\u5173\u5417 \u662f\u7684 \u9ed8\u8ba4\u53c2\u6570\u4e0d\u8fdb\u865a\u8868 \u2192 upcasting\u7684\u65f6\u5019

    "},{"location":"docs/1-cs/oop/final_review/#upcasting","title":"upcasting","text":""},{"location":"docs/1-cs/oop/templates/","title":"\u6a21\u677fTemplate \u548c \u6807\u51c6\u6a21\u677f\u5e93STL","text":"

    :material-circle-edit-outline: \u7ea6 1186 \u4e2a\u5b57 :fontawesome-solid-code: 361 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f

    \u9700\u6c42\uff1a\u8ba9\u6211\u4eec\u7684\u4ee3\u7801\u72ec\u7acb\u4e8e\u5177\u4f53\u7684\u7c7b\u578b\u5de5\u4f5c\u3002

    \u6211\u4eec\u5199\u51fa\u4e00\u4e2a\u9002\u7528\u4e8e\u6240\u6709\u7c7b\u578b\u7684\u6570\u636e\u7ed3\u6784\u7684\u7c7b\u6216\u7b97\u6cd5\uff08\u51fd\u6570\uff09\uff0c\u5728\u771f\u6b63\u9700\u8981\u4f7f\u7528\u65f6\u751f\u6210\u4e00\u4e2a\u9002\u7528\u4e8e\u6240\u9700\u7c7b\u578b\u7684\u5b9e\u4f8b\u3002\u8fd9\u79cd\u7f16\u7a0b\u8303\u5f0f\u79f0\u4e3a\u8303\u578b\u7f16\u7a0b\u3002

    \u6a21\u677f\u7c7b\u7684\u5199\u6cd5 

    template<typename T>\nclass Container{\nT *data;\nunsigned size, capa;\npiblic:\nContainer(unsigned capa = 512): data(new T[capa]){}\n~Container() {delete[] data;}\nT& operator[](unsigned index) {return data[index];}\n}\n

    \u8fd9\u91cctemplate T\u8868\u660e\u5b83\u63a5\u53d7\u4e00\u4e2a\u7c7b\u578b\u4f5c\u4e3a\u53c2\u6570\uff0c\u540d\u5b57\u662fT\u3002\u5728\u6a21\u677f\u7684\u5b9a\u4e49\u5185\u90e8\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5230\u8fd9\u4e2a\u7c7b\u578b\u53d8\u91cfT\u3002

    \u7279\u5316\uff1a\u6839\u636e\u6a21\u677f\u751f\u6210\u5b9e\u9645\u7684\u7c7b\u7684\u8fc7\u7a0b 

    Container<int> ci;\nContainer<double> cd;\n

    \u6a21\u677f\u51fd\u6570\u8981\u600e\u4e48\u5199 

    template<typename T>\nT abs(T x) {return x>0?x:-x;}\n

    \u6a21\u677f\u8fd0\u7b97\u7b26\u91cd\u8f7d\u600e\u4e48\u5199 

    template<typename T>\nclass Container {\nT* data;\nunsigned size = 0, capa;\npublic: Container(unsigned capa = 512) : data(new T[capa]), capa(capa){}\n~Container(){delete[] data;}\nT& operator[](unsigned index) {return data[index];}\nconst T& operator[](unsigned idnex) const {return data[index];}\nunsigned getSize() const {return size;}\nunsigned getCapa() const {return capa;}\nContainer &add(T val){\ndata[size++] = val;\nreturn *this;\n}\n};\ntemplate<typename T>\nostream & operator<<(ostream& os, const Container<T>&c){\nfor (unsigned i = 0; i < c.getSize(); i++){\nos << c[i] << ' ';\nreturn os;\n}\n}\n

    "},{"location":"docs/1-cs/oop/templates/#reference","title":"Reference","text":"

    7 \u6a21\u677f (I) - \u57fa\u672c\u77e5\u8bc6\u4e0e STL \u4f7f\u7528 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4

    "},{"location":"docs/1-cs/oop/templates/#template","title":"\u53ef\u53d8\u53c2\u6570\u6a21\u677f template

    C++11\u7684\u65b0\u7279\u6027 \u5bf9\u53c2\u6570\u9ad8\u5ea6\u6cdb\u5316\uff0c\u53ef\u4ee5\u8868\u793a0\u5230\u4efb\u610f\u4e2a\u4efb\u610f\u7c7b\u578b\u7684\u53c2\u6570\u3002

    \u8bed\u6cd5 

    template <class ...T>  // \u58f0\u660e\u4e00\u4e2a\u53c2\u6570\u5305\uff0c\u8fd9\u4e2a\u53c2\u6570\u5305\u4e2d\u5305\u542b0\u5230\u4efb\u610f\u4e00\u4e2a\u53c2\u6570\u6a21\u677f\nvoid f(T... args);     // \u5728\u6a21\u677f\u5b9a\u4e49\u7684\u53f3\u8fb9\uff0c\u53ef\u4ee5\u5c06\u53c2\u6570\u5305\u5c55\u5f00\u6210\u4e00\u4e2a\u4e00\u4e2a\u72ec\u7acb\u53c2\u6570\n

    \u6700\u5927\u7684\u96be\u70b9\uff1a\u5982\u4f55\u5c55\u5f00\u53ef\u53d8\u6a21\u677f\u53c2\u6570

    \u6253\u5370\u53c2\u6570\u4e2a\u6570\uff1a 

    template<class ...T>\nvoid f(T... args)\n{\n        cout << sizeof...(args) << endl;\n}\n\nf();\nf(1, 2);\nf(1, 2.5, \"\");\n

    \u9012\u5f52\u65b9\u5f0f\u5c55\u5f00\u53c2\u6570\u5305 

    #include <iostream>\nusing namespace std;\n\n// \u9012\u5f52\u7ec8\u6b62\u51fd\u6570\nvoid print(){\n    cout << \"empty\" << endl;\n}\n\n// \u5c55\u5f00\u51fd\u6570\ntemplate<class T, class ...Args>\nvoid print(T head, Args... rest){\n    cout << \"parameter\" << head << endl;\n    print(rest...);\n}\n\nint main(){\n    print(1, 2, 3, 4);\n    return 0;\n}\n

    \u4e0a\u8ff0\u4f8b\u5b50\u4f1a\u8f93\u51fa\u6bcf\u4e00\u4e2a\u53c2\u6570\uff0c\u76f4\u5230\u7a7a\u65f6\u8f93\u51faempty\u3002\u5c55\u5f00\u53c2\u6570\u5305\u7684\u51fd\u6570\u6709\u4e24\u4e2a\uff0c\u4e00\u4e2a\u662f\u9012\u5f52\u51fd\u6570\uff0c\u53e6\u4e00\u4e2a\u662f\u9012\u5f52\u7ec8\u6b62\u51fd\u6570\uff0c\u53c2\u6570\u5305Args\u2026\u5728\u5c55\u5f00\u7684\u8fc7\u7a0b\u4e2d\u9012\u5f52\u8c03\u7528\u81ea\u5df1\uff0c\u6bcf\u8c03\u7528\u4e00\u6b21\uff0c\u53c2\u6570\u5305\u4e2d\u7684\u53c2\u6570\u5c31\u5c11\u4e00\u4e2a\uff0c\u76f4\u5230\u6240\u6709\u53c2\u6570\u90fd\u5c55\u5f00\u4e3a\u6b62\u3002\u5f53\u6ca1\u6709\u53c2\u6570\u65f6\uff0c\u5219\u8c03\u7528\u975e\u6a21\u677f\u51fd\u6570print()\u7ec8\u6b62\u9012\u5f52\u8fc7\u7a0b\u3002

    \u7ec8\u6b62\u51fd\u6570\u4e5f\u53ef\u4ee5\u5199\u6210 

    template<class T>\nvoid print(T t){\n    cout << t << endl;\n}\n

    \u53ef\u53d8\u6a21\u677f\u53c2\u6570\u6c42\u548c 

    template<typename T>\nT sum(T t){\n    return t;\n}\ntemplate<typename T, typename ... Types>\nT sum(T first, Types ...rest){\n    return first + sum<T> (rest...);\n}\n\nsum(1, 2, 3, 4);\n

    \u9012\u5f52\u51fd\u6570\u5c55\u5f00\u53c2\u6570\u5305\u662f\u4e00\u79cd\u6807\u51c6\u505a\u6cd5\uff0c\u4e5f\u6bd4\u8f83\u597d\u7406\u89e3\uff0c\u4f46\u662f\u7f3a\u70b9\u65f6\u5fc5\u987b\u8981\u4e00\u4e2a\u91cd\u8f7d\u7684\uff08\u540c\u540d\uff09\u9012\u5f52\u7ec8\u6b62\u51fd\u6570\u6765\u7ec8\u6b62\u9012\u5f52\u3002

    \u6216\u8005\u4e0d\u9012\u5f52\u65b9\u5f0f\uff0c\u8fd9\u79cd\u65b9\u5f0f\u9700\u8981\u501f\u52a9\u9017\u53f7\u8868\u8fbe\u5f0f\u548c\u521d\u59cb\u5316\u5217\u8868\u3002\u524d\u9762\u7684print\u53ef\u4ee5\u8fd9\u4e48\u5199 

    template<class T>\nvoid printarg(T t){\n    cout << t << endl;\n}\n\ntemplate <class ...Args>\nvoid expand(Args... args){\n    int arr[] = {(printarg(args), 0)...};\n}\n\nexpand(1, 2, 3, 4);\n

    arr\u8fd9\u4e2a\u6570\u7ec4\u7684\u76ee\u7684\u5355\u7eaf\u662f\u5c55\u5f00\u53c2\u6570\u5305

    \u5982\u679c\u5c06\u51fd\u6570\u4f5c\u4e3a\u53c2\u6570\uff0c\u5c31\u53ef\u4ee5\u652f\u6301lambda\u8868\u8fbe\u5f0f 

    template<class F, class... Args> void expand(const F& f, Args&&...args){\ninitializer_list<int>{(f(std::forward< Args>(args)), 0)};\n}\nexpand([](int i){cout << i << endl;}, 1,2,3);\n

    \u53ef\u4ee5\u5e26\u4efb\u610f\u4e2a\u6570\u4e0d\u540c\u7684\u53c2\u6570\uff0c\u6bd4\u5982std::tuple 

    template<class... Types>\nclass tuple;\n

    \u6a21\u677f\u504f\u7279\u5316\u548c\u9012\u5f52\u65b9\u5f0f\u5c55\u5f00\u53c2\u6570\u5305

    \u53ef\u53d8\u53c2\u6570\u6a21\u677f\u7c7b\u7684\u5c55\u5f00\u4e00\u822c\u9700\u8981\u5b9a\u4e49\u4e24\u5230\u4e09\u4e2a\u7c7b\uff0c\u5305\u62ec\u7c7b\u58f0\u660e\u548c\u504f\u7279\u5316\u7684\u6a21\u677f\u7c7b 

    // \u524d\u5411\u58f0\u660e\ntemplate<typename... Args>\nstruct Sum;\n\n// \u57fa\u672c\u5b9a\u4e49\ntemplate<typename First, typename... Rest>\nstruct Sum<First, Rest...>{\n    enum { value = Sum<First>::value + Sum<Rest...>::value };\n}\n\n// \u9012\u5f52\u7ec8\u6b62\ntemplate<typename Last>\nstruct Sum<Last>{\n    enum { value = sizeof(Last) };\n}\n

    ","text":""},{"location":"docs/1-cs/oop/templates/#stl","title":"\u6807\u51c6\u6a21\u677f\u5e93 STL

    STL\u516d\u5927\u90e8\u4ef6\uff1a\u5bb9\u5668\uff08containers\uff09\uff0c\u5206\u914d\u5668\uff08allocators\uff09\uff0c\u7b97\u6cd5\uff08algorithm\uff09\uff0c\u8fed\u4ee3\u5668\uff08iterator\uff09\uff0c\u9002\u914d\u5668\uff08adapters\uff09\uff0c\u4eff\u51fd\u6570\uff08functors\uff09

    ","text":""},{"location":"docs/1-cs/oop/templates/#_1","title":"\u5e38\u7528\u7684\u5bb9\u5668","text":"

    vector, deque, list, set/multiset, map/multimap \u7b49

    "},{"location":"docs/1-cs/oop/templates/#1-vector","title":"1. Vector","text":"

    Vector\u662f\u4e00\u79cd\u53d8\u957f\u6570\u7ec4\u3002 

    #include<vector>\nusing namespace std;\nvector<int> name;\nvector<double> name;\nvector<char> name;\nvector<struct node> name;\n// \u8fd9\u4e24\u4e2a\u4e3b\u8981\u6709\u901f\u5ea6\u4e0a\u7684\u533a\u522b\uff0carray\u975e\u5e38\u6162\uff0cvector\u5feb\u4e00\u4e9b\nvector< vector<int> > name; // > >\u4e4b\u95f4\u8981\u52a0\u7a7a\u683c\uff0c\u65b0\u6807\u51c6\u4e0d\u7528\u52a0\u4e86\nvector<int> array[SIZE]; // \u8fd9\u4e2a\u4e0d\u662f\u5f88\u5e38\u7528\uff0c\u56e0\u4e3a\u5bb9\u6613\u51fa\u9519\uff0c\u4e14\u6570\u7ec4\u4e0d\u77e5\u9053\u81ea\u5df1\u7684\u957f\u5ea6\uff0c\u8fd8\u6709std::array\n

    \u8bbf\u95ee\u65b9\u5f0f 

    // 1. \u901a\u8fc7\u4e0b\u6807\n#include<iostream>\n#include<vector>\nusing namespace std;\nint main()\n{\nvector<int> vi;\nvi.push_back(1);\ncout<<vi[0]<<endl;\nreturn 0;\n}\n// 2. \u901a\u8fc7\u8fed\u4ee3\u5668\nvector<int>::iterator\nvector<double>::iterator\n// \u4f8b\n#include<iostream>\n#include<vector>\nint main()\n{\nvector<int> v;\nfor(int i = 0; i < 5; i++)\n{\nv.push_back(i); }\nvector<int>::iterator it=v.begin();\nfor(int i = 0; i < v.size(); i++)\n{\ncout << it[i] << \" \";\n// \u4e5f\u53ef\u4ee5\u5199\u6210 cout << * (it + i) << \" \";\n}\nreturn 0;\n}\n// \u6216\u8005\u4f18\u96c5\u7684\u5199\u6cd5\n// \u56e0\u4e3a\u8fed\u4ee3\u5668\u4e0d\u652f\u6301 it < v.end()\u7684\u5199\u6cd5\uff0c\u53ea\u80fd\u5199!=\nfor (vector<int>::iterator it=v.begin(); it!=v.end();it++)\n{\ncout << *it << \" \";\n}\n
    \u5e38\u7528\u51fd\u6570 
    push_back(item) // \u5728vector\u540e\u9762\u6dfb\u52a0\u4e00\u4e2a\u5143\u7d20\npop_back(item) // \u5728vector\u540e\u9762\u5220\u9664\u4e00\u4e2a\u5143\u7d20\nsize(vector) // \u8fd4\u56de\u5143\u7d20\u4e2a\u6570\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(1)\nclear(vector) // \u6e05\u9664\u6240\u6709\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(N)\ninsert(position, x) // \u5728position\u7684\u5730\u65b9\u63d2\u5165\u4e00\u4e2ax\n// \u4f8b\nv.insert(v.begin()+2, -1); // \u76f8\u5f53\u4e8e\u5728v[2]\u5904\u63d2\u5165\u4e00\u4e2a-1\nerase(position);\nerase(positionBegin, positionEnd);  // \u5de6\u95ed\u53f3\u5f00\n

    "},{"location":"docs/1-cs/oop/templates/#2-set","title":"2. set","text":"

    \u96c6\u5408\u662f\u4e0d\u5141\u8bb8\u5143\u7d20\u91cd\u590d\u7684\u65e0\u5e8f\u5bb9\u5668 

    #include<set>\nusing namespace std;\nset<int> name;\nset<double> name;\nset<char> name;\nset<struct node> name;\nset<set<int> > name;\n
    \u56e0\u4e3a\u65e0\u5e8f\uff0cset\u53ea\u80fd\u901a\u8fc7iterator\u8bbf\u95ee\uff0c\u9664\u4e86vector\u548cstring\u4e4b\u5916\u7684\u5bb9\u5668\u90fd\u4e0d\u80fd\u901a\u8fc7\u4e0b\u6807\u8bbf\u95ee 
    set<int>::iterator it;\nset<char>::iterator it;\n
    \u5e38\u7528\u51fd\u6570 
    st.insert(X);\nst.find(X); // \u8fd4\u56deset\u4e2dvalue\u6240\u5bf9\u5e94\u7684\u8fed\u4ee3\u5668\uff0c\u4e5f\u5c31\u662fvalue\u7684\u6307\u9488\n// \u4f8b\nset<int>::iterator it = st.find(2);\ncout << *it << endl;\n// \u53ef\u4ee5\u76f4\u63a5\u5199\u6210\ncout << *(st.find(2)) << endl;\nst.erase(it); // \u5220\u9664\u67d0\u4e2a\u5730\u5740\u7684\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(1)\nst.erase(X); // \u5220\u9664\u67d0\u4e2a\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(N)\nst.erase(itBegin, itEnd);\nst.size();\n

    "},{"location":"docs/1-cs/oop/templates/#3-deque","title":"3. deque","text":"

    deque\u662f\u7531\u4e00\u6bb5\u5b9a\u91cf\u8fde\u7eed\u7a7a\u95f4\u6784\u6210\uff0c\u4e00\u65e6\u8981\u5728deque\u7684\u524d\u7aef\u548c\u5c3e\u7aef\u589e\u52a0\u7a7a\u95f4\uff0c\u4fbf\u914d\u7f6e\u4e00\u6bb5\u8fde\u7eed\u7a7a\u95f4\uff0c\u4e32\u5728\u6574\u4e2adeque\u7684\u5934\u90e8\u548c\u5c3e\u90e8.

    "},{"location":"docs/1-cs/oop/templates/#4-list","title":"4. list","text":""},{"location":"docs/1-cs/oop/templates/#5-mapunordered_map","title":"5. map/unordered_map","text":""},{"location":"docs/1-cs/oop/templates/#6-string","title":"6. string","text":"
    // init\n#include<string>\nstring str;\nstring str = \"Hello\";\ncin >> str;\ncout << str;\n// assignment\nchar cstr1[20];\nchar cstr2[20] = \"jaguar\";\nstring str1;\nstring str2 = \"panther\";\ncstr1 = cstr2; // illegal\nstr1 = str2; // legal\n// concatenation\nstring str3;\nstr3 = str1 + str2;\nstr1 += str2;\nstr1 += \"a string literal\";\n// constructors (Ctors)\nstring (const char *cp, int len);\nstring (const string& s2, int pos);\nstring (const string& s2, int pos, int len);\n// sub-string\nsubstr (int pos, int len);\n// modification\nassign (...);\ninsert (...);\ninsert (int pos, const string& s);\nerase (...);\nappend (...);\nreplace (...);\nreplace (int pos, int len, const string& s);\n...\n// search\nfind (const string& s);\n// File I/O\n#include <ifstream> // read from file\n#include <ofstream>  // write to file\n// write into file\nofstream File1(\"...\");\nFile1 << \"Hello world\" << std::enl;\n// read from file\nifstream File2(\"...\");\nstd::string str;\nFile2 >> str;\n
    "},{"location":"docs/1-cs/oop/templates/#_2","title":"\u7b97\u6cd5","text":"

    \u7b97\u6cd5\u90e8\u5206\u4e3b\u8981\u7531<algorithm> <numeric> <functional>\u7ec4\u6210 <algorithm>\u662f\u6700\u5927\u7684\u4e00\u4e2a <numeric>\u4f53\u79ef\u5f88\u5c0f\uff0c\u53ea\u5305\u62ec\u51e0\u4e2a\u5728\u5e8f\u5217\u4e0a\u8fdb\u884c\u7b80\u5355\u6570\u5b66\u8fd0\u7b97\u7684\u6a21\u677f\u51fd\u6570 <functional>\u5b9a\u4e49\u4e86\u4e00\u4e9b\u6a21\u677f\u7c7b\uff0c\u7528\u4ee5\u58f0\u660e\u51fd\u6570\u5bf9\u8c61

    "},{"location":"docs/1-cs/oop/templates/#iterator","title":"\u8fed\u4ee3\u5668 Iterator","text":"

    \u7528\u8fed\u4ee3\u5668\u53ef\u4ee5\u8bfb\u53d6\u5b83\u6307\u5411\u7684\u5143\u7d20\u3002\u8fed\u4ee3\u5668\u540d\u5c31\u8868\u793a\u8fed\u4ee3\u5668\u6307\u5411\u7684\u5143\u7d20\uff0c\u901a\u8fc7\u975e\u5e38\u91cf\u8fed\u4ee3\u5668\u8fd8\u80fd\u4fee\u6539\u5176\u6307\u5411\u7684\u5143\u7d20\u3002 

    #include<iostream> #include<vector> using namespace std; int main() { vector<int> v; for (int n = 0; n < 5; ++n) v.push_back(n); vector<int>::iterator i; for (i = v.begin(); i != v.end(); i++) { cout << *i << \" \"; // *i \u662f i \u6307\u5411\u7684\u5143\u7d20 *i *= 2; \n} }\n

    "},{"location":"docs/1-cs/oop/templates/#stl_1","title":"\u7c7b\u5e93\u548cSTL

    STL\u662f\u8303\u578b\u7a0b\u5e8f\u8bbe\u8ba1\u7684\u4e00\u4e2a\u8303\u4f8b\uff0c\u542b\uff1a\u5bb9\u5668\uff08container\uff09\u3001\u8fed\u4ee3\u5668\uff08iterator\uff09\u3001\u7b97\u6cd5\uff08algorithm\uff09\u3001\u51fd\u6570\u5bf9\u8c61\uff08function object\uff09\u3002\u7c7b\u5e93\u662f\u7c7b\u7684\u96c6\u5408\uff0c\u662f\u4e00\u79cd\u9884\u5b9a\u4e49\u7684\u9762\u5411\u5bf9\u8c61\u7684\u7a0b\u5e8f\u5e93\u3002

    ","text":""},{"location":"docs/1-cs/oop/templates/#c","title":"C++\u7684\u6807\u51c6\u5e93","text":"

    using namespace std;

    "},{"location":"docs/1-cs/oop/templates/#stl_2","title":"STL\u4e2d\u7684\u5bb9\u5668\u7c7b","text":"

    \u5bb9\u5668\uff08container\uff09\u7c7b\u662f\u7528\u6765\u5bb9\u7eb3\u3001\u5305\u542b\u4e00\u7ec4\u5143\u7d20\u6216\u5143\u7d20\u96c6\u5408\u7684\u5bf9\u8c61\u7684\u3002STL\u4e2d\u5b9a\u4e49\u4e86\u591a\u79cd\u4e0d\u540c\u7c7b\u578b\u7684\u5bb9\u5668\uff0c\u4f8b\u5982

    "},{"location":"docs/1-cs/oop/templates/#vector","title":"\u5411\u91cf vector","text":"

    \u5b9a\u4e49

    vector<int> iv;\nvector<int> cv(5);\nvector<int> cv(5, 'x');\nvector<int> iv2(iv);\n

    \u4f7f\u7528

    #include<iostream>\n#include<vector>\nusing namespace std;\nint main()\n{\nvector<char> v;  // create zero-len vector\nint i;\n// put values into a vector\nfor (i = 0; i < 10; i++)\nv.push_back('A' + i);\n// can access vector contents using subsripting\nfor (i = 0; i < 10; i++)\ncout << v[i] << \" \";\ncout << endl;\n// access via iterator\nvector<char>::iterator p = v.begin();\nwhile(p != v.end())\n{\ncout << *p << \" \";\np++;\n}\nreturn 0;\n}\n
    "},{"location":"docs/1-cs/oop/templates/#list","title":"\u7ebf\u6027\u8868 list","text":"

    \u5b9a\u4e49\u4e86\u53cc\u5411\u7684\u7ebf\u6027\u8868\uff0c\u53c8\u53ef\u79f0\u4e3a\u53cc\u5411\u94fe\u8868\u3002list\u7c7b\u53ea\u652f\u6301\u987a\u5e8f\u8bbf\u95ee\u3002

    // sort a list\n#include<iostream>\n#include<list>\n#include<cstdlib>\nusing namespace std;\nint main()\n{\nint i;\nlist<char> lst;\n// create a list of random characters\nfor (i = 0; i < 10; i++)\nlist.push_back('A' + (rand()%26));\n}\n
    "},{"location":"docs/1-cs/oop/templates/#set","title":"\u96c6\u5408 set","text":"
    #include<set>\n#include<iostream>\n#include<string>\nint main()\n{\nstd::set<std::string> source;\nstd::string input;\nfor(int i=0;i<6;i++)\n{\nstd::cin>>input;\nsource.insert(input);\n}\nstd::set<std::string>::iterator at = source.begin();\nwhile(at != source.end())\nstd::cour << * at++ << std::endl;\n}\n
    "},{"location":"docs/1-cs/oop/templates/#multiset","title":"multiset","text":""},{"location":"docs/1-cs/oop/templates/#map","title":"\u6620\u5c04 map","text":""},{"location":"docs/1-cs/oop/templates/#queue","title":"\u961f\u5217 queue","text":""},{"location":"docs/1-cs/oop/templates/#stdstack","title":"std::stack","text":""},{"location":"docs/1-cs/oop/templates/#stdpair","title":"std::pair","text":""},{"location":"docs/1-cs/oop/templates/#string","title":"\u5b57\u7b26\u4e32string","text":""},{"location":"docs/1-cs/oop/templates/#_3","title":"\u7b97\u6cd5\u5e93 ` ","text":""},{"location":"docs/1-cs/oop/templates/#sort","title":"\u6392\u5e8f\u7b97\u6cd5sort","text":"
    #include<algorithm>\n#include<iostream>\n#include<string>\n#include<vector>\nusing namespace std;\nvoid load(vector<string>&);\nvoid print(vector<string>);\nconst int SIZE = 8;\nint main()\n{\nvector<string> v(SIZE);\nload(v);\nsort(v.begin(), v.end());  // \u6307\u5b9a\u6392\u5e8f\u7684\u8d77\u6b62\u4f4d\u7f6e\nprint(v);\nreturn 0;\n}\n// \u4f1a\u6309\u7167\u5b57\u6bcd\u5e8f\u6392\u5e8f\n
    "},{"location":"docs/1-cs/oop/templates/#_4","title":"\u8fed\u4ee3\u5668

    \u662f\u4e00\u79cd\u7c7b\u4f3c\u6307\u9488\u7684\u5bf9\u8c61\uff0c\u53ef\u4ee5\u4f7f\u7528\u8fed\u4ee3\u5668\u6765\u8bbf\u95ee\u5bb9\u5668\u4e2d\u7684\u5143\u7d20\u3002

    ","text":""},{"location":"docs/1-cs/oop/templates/#reverse-iterator","title":"\u53cd\u5411\u8fed\u4ee3\u5668 reverse iterator","text":"
    #include<list>\n#include<iostream>\nint main()\n{\nusing namespace std;\nlist<int> c1;\nlist<int>::iterator c1_Iter;\nlist<int>::reverse_iterator c1_rIter;\nc1_rIter = c1.rbegin(); // the last element\n}\n
    "},{"location":"docs/1-cs/oop/templates/#_5","title":"\u53c2\u8003\u8d44\u6599

    https://zhuanlan.zhihu.com/p/344558356 LJJ PPT

    ","text":""},{"location":"docs/1-cs/os/","title":"\u7d22\u5f15","text":"

    :material-circle-edit-outline: \u7ea6 384 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u6211\u89c9\u5f97 x+i for i in [x, y, g] \u4e09\u4f4d\u7684\u7b14\u8bb0\u5bf9\u4e8e\u8fd9\u95e8\u8bfe\u7406\u8bba\u90e8\u5206\u7684\u4ecb\u7ecd\u5df2\u7ecf\u975e\u5e38\u5145\u5206\u4e86\u3002\u5927\u5bb6\u53ef\u4ee5\u5728\u6211 root \u7d22\u5f15\u9875\u6307\u5411\u7684 xy \u7b14\u8bb0\u627e\u5230\u6211\u8fd9\u91cc\u63d0\u5230\u7684\u4e09\u4efd\u7b14\u8bb0\u3002

    \u6211\u4ecd\u8981\u5199\u8fd9\u95e8\u8bfe\u7684\u5b9e\u9a8c\u90e8\u5206\u7684\u539f\u56e0\u662f\uff0c\u81ea\u5df1\u89c9\u5f97\u5b9e\u9a8c\u624b\u518c\u5199\u5f97\u4ecd\u6709\u4e00\u4e9b\u5bfc\u81f4\u4e0d\u592a\u597d\u7406\u89e3\u7684\u7f3a\u9677\uff0c\u6bd4\u5982\u7406\u8bba\u548c\u64cd\u4f5c\u5206\u6210\u4e0a\u4e0b\u4e24\u5927\u5757\u6765\u5199\uff0c\u5bfc\u81f4\u67e5\u8d77\u6765\u7684\u65f6\u5019\u50cf\u5728\u5403\u4e00\u76d8\u94a2\u4e1d\u7403\u7092\u610f\u5927\u5229\u9762\uff0c\u6bd4\u5982\u6709\u65f6\u5728\u8bf4\u64cd\u4f5c\u65f6\u4e0d\u5206\u5df2\u7ecf\u5b9e\u73b0\u597d\u7684/\u6211\u8981\u505a\u7684/linux\u4f1a\u505a\u4f46\u662f\u6211\u4eec\u4e0d\u5173\u5fc3\u7684\u3002

    \u6211\u7684\u9884\u671f\u662f\u628a\u8fd9\u4efd\u7b14\u8bb0\u5199\u6210\u4e00\u5757\u4e00\u5757\u7684\u4e1c\u897f\uff0c\u6bcf\u4e00\u5757\u662f\u4e00\u4e2a\u7406\u8bba+\u64cd\u4f5c+\u4e00\u4e2a\u80fd\u8dd1\u8d77\u6765\u7684\u6700\u5c0f\u5355\u5143\u3002\u73b0\u5b9e\u662f\u6211\u7684\u65f6\u95f4\u771f\u7684\u592a\u4e0d\u8db3\u4e86\uff0c\u611f\u89c9\u53ea\u6765\u5f97\u53ca\u53bb\u8865\u5145\u4e00\u4e9b\u5b9e\u9a8c\u624b\u518c\u91cc\u6ca1\u6709\u5199\u7684\u80cc\u666f\u6216\u8005\u662f\u6211\u81ea\u5df1\u64cd\u4f5c\u65f6\u7684\u4e00\u4e9b\u5fc3\u5f97\u6216\u603b\u7ed3\uff0c\u53ea\u80fd\u5f53\u5b9e\u9a8c\u624b\u518c\u7684\u8865\u5145\u6765\u770b\u3002\u7136\u540e\u672c\u6765\u8fd9\u91cc\u5e94\u5f53\u6709\u4e00\u53e5\u5e0c\u671b\u4ee5\u540e\u6709\u65f6\u95f4\u80fd\u5199\u5b8c\uff0c\u4f46\u662f\u6211\u4e5f\u4e0d\u60f3\u8fd9\u6837\u627f\u8bfa\u4e86\uff0c\u6211\u66f4\u613f\u610f\u8bf4\u4e00\u4e9b\u73b0\u5b9e\u7684\u6bd4\u5982\u6211\u4e0d\u4f1a\u518d\u66f4\u65b0\u8fd9\u4efd\u7b14\u8bb0\u4e86\uff0c\u4f46\u662f\u5e0c\u671b\u8bfb\u8005\u505a\u5b9e\u9a8c\u7684\u65f6\u5019\u53ef\u4ee5\u5e26\u7740\u4e0a\u8ff0\u63d0\u5230\u7684\u601d\u8def\u53bb\u6574\u7406\u81ea\u5df1\u7684\u601d\u7ef4\u548c\u5b9e\u9a8c\u62a5\u544a\u3002

    \u63a5\u4e0b\u6765\u8bf7\u70b9\u8fdb\u53e6\u4e00\u4e2a lab \u9875\u9762\u7ee7\u7eed\u9605\u8bfb\u3002

    "},{"location":"docs/1-cs/os/lab/","title":"OS lab","text":"

    :material-circle-edit-outline: \u7ea6 8965 \u4e2a\u5b57 :fontawesome-solid-code: 91 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 31 \u5206\u949f

    \u76ee\u5f55\uff1a\u8fd9\u91cc\u4f1a\u5148\u8bb2\u4e00\u4e0b\u7528\u5230\u7684\u80cc\u666f\u77e5\u8bc6\u548c mac \u4e0b\u7684\u73af\u5883\u914d\u7f6e\u6280\u5de7\uff08\u56e0\u4e3a\u624b\u518c\u8bb2 mac \u4e0d\u591a\uff09\uff0c\u7136\u540e\u6328\u4e2a\u5b9e\u9a8c\u6211\u60f3\u8fdb\u884c\u4e00\u4e9b\u7efc\u8ff0\uff0c\u4e0d\u77e5\u9053\u7cbe\u529b\u80fd\u652f\u6491\u5199\u591a\u5c11\uff0c\u6700\u540e\u8865\u5145\u4e24\u4e2a\u6211\u5b9e\u9a8c\u4e2d\u603b\u9047\u5230\u7684\u4f46\u624b\u518c\u6ca1\u6d89\u53ca\u7684\u95ee\u9898\u3002\u81ea\u77e5\u5b66\u5f97\u4e0d\u597d\uff0c\u4e0d\u786e\u5b9a\u7684\u5730\u65b9\u6211\u4f1a\u6807\u51fa\u6765\u3002

    "},{"location":"docs/1-cs/os/lab/#overview","title":"overview","text":"

    Warning

    \u7ed3\u6784\u56fe TODO

    \u4e00\u4e2a\u6700\u540e\u505a\u51fa\u6765\u7684 lab \u7ed3\u6784\u56fe:

    "},{"location":"docs/1-cs/os/lab/#_1","title":"\u80cc\u666f\u77e5\u8bc6","text":"

    \u5148\u4ecb\u7ecd\u4e00\u4e0b\u6574\u4e2a\u5b9e\u9a8c\u548c\u5b9e\u9a8c\u73af\u5883\u7684\u5927\u80cc\u666f\u3002

    "},{"location":"docs/1-cs/os/lab/#os","title":"\u8ba1\u7b97\u673a\u4e0a\u7535\u5230OS\u8fd0\u884c\u7684\u8fc7\u7a0b","text":"

    \u5d4c\u5165\u5f0f\u7cfb\u7edf\uff08\u76f8\u6bd4\u8ba1\u7b97\u673a\u7cfb\u7edf\u6bd4\u8f83\u7b80\u5355\uff0c\u53ea\u80fd\u5728\u7279\u5b9a\u786c\u4ef6\u4e0a\u8fd0\u884c\uff09\u7684\u542f\u52a8\u8fc7\u7a0b\u6bd4\u8f83\u7b80\u5355\uff0c\u7528\u5b83\u6765\u505a\u4f8b\u5b50\u8bb2\u89e3\uff0c\u8fc7\u7a0b\u662f\uff1a

    Hardware             RISC-V M Mode           RISC-V S Mode \n+------------+         +--------------+         +----------+\n|  Power On  |  ---->  |  Bootloader  |  ---->  |  Kernel  |\n+------------+         +--------------+         +----------+\n
    "},{"location":"docs/1-cs/os/lab/#sbiopensbi","title":"sbi\u548copensbi","text":"

    \u4ecb\u7ecd\u5b9e\u9a8c\u73af\u5883\u7528\u7684\u7b2c\u4e00\u4e2a\u5de5\u5177\uff1asbi (supervisor binary interface)\u662f s-mode \u7684 kernel \u548c m-mode \u6267\u884c\u73af\u5883\u4e4b\u95f4\u7684\u63a5\u53e3\u89c4\u8303

    opensbi\u662f\u4e00\u4e2ariscv sbi\u89c4\u8303\u7684\u5f00\u6e90\u5b9e\u73b0\uff0c\u603b\u4e4b\u610f\u601d\u662fopensbi\u662f\u4e00\u4e9b\u5bf9m-mode\u4e0b\u786c\u4ef6\u7684\u7edf\u4e00\u5b9a\u4e49\uff0c\u5728s-mode\u4e0b\u7684\u5185\u6838\u53ef\u4ee5\u6309\u7167\u8fd9\u4e9b\u89c4\u8303\u5bf9\u4e0d\u540c\u786c\u4ef6\u64cd\u4f5c\u3002

    \u6211\u4eecopensbi\u53ef\u4ee5\u4f5c\u4e3abootloader\u5b8c\u6210\u673a\u5668\u542f\u52a8\u65f6m-mode\u4e0b\u7684\u786c\u4ef6\u521d\u59cb\u5316\u548c\u5bc4\u5b58\u5668\u8bbe\u7f6e\uff0c\u53ef\u4ee5\u5229\u7528opensbi\u5b8c\u6210\u5b57\u7b26\u6253\u5370\u4e4b\u7c7b\u7684\u64cd\u4f5c\u3002

    qemu\u4f1a\u628aopensbi\u8d77\u59cb\u5730\u5740\u52a0\u8f7d\u52300x80000000\u5904.

    opensbi\u521d\u59cb\u5316\u540e\u4f1a\u8df3\u8f6c\u52300x80200000\u5904\uff0c\u5373kernel\u7684\u8d77\u59cb\u5730\u5740\u3002\u6240\u4ee5\u8981\u7f16\u8bd1\u7684\u4ee3\u7801\u57280x80200000\u5904\u3002

    "},{"location":"docs/1-cs/os/lab/#_2","title":"\u7279\u6743\u6a21\u5f0f","text":"

    riscv\u6709\u4e09\u79cd\u7279\u6743\u6a21\u5f0f\uff1aUser, Supervisor, & Machine\u3002\u6574\u4e2a\u5b9e\u9a8c\u4e2d\u6211\u4eec\u4e00\u5f00\u59cb\u90fd\u8981\u5728 s-mode \u64cd\u4f5c\uff0c\u4e4b\u540e\u6162\u6162\u5b9e\u73b0 u-mode\u3002

    Level Encoding Name Abbreviation \u4ecb\u7ecd 0 00 User/Application U \u5bf9\u786c\u4ef6\u6a21\u5f0f\u7684\u62bd\u8c61\uff0c\u6709\u6700\u9ad8\u7ea7\u522b\u7684\u6743\u9650 1 01 Supervisor S \u5bf9\u5e94\u4e0e\u5185\u6838\u6001Kernel\u3002\u5f53\u7528\u6237\u9700\u8981\u5185\u6838\u8d44\u6e90\u65f6\uff0c\u5411\u5185\u6838\u7533\u8bf7\uff0c\u5e76\u5207\u6362\u5230\u5185\u6838\u6001\u8fdb\u884c\u5904\u7406 2 10 Reserved 3 11 Machine M \u7528\u6237\u6001\uff0c\u6700\u4f4e\u7ea7\u522b\u6743\u9650

    \u4e00\u822c\u6bcf\u79cd\u6a21\u5f0f\u53ef\u4ee5\u8fd0\u884c\u7684\u7a0b\u5e8f\u6709

    supported modes intended usage M simple embedded systems M, U secure embedded systems M, S, U systems running unix-like operating systems"},{"location":"docs/1-cs/os/lab/#_3","title":"\u73af\u5883\u914d\u7f6e","text":""},{"location":"docs/1-cs/os/lab/#docker","title":"Docker","text":"

    \u5728\u5b98\u7f51\u5b89\u88c5Docker\u3002\u4e4b\u540e\u9700\u8981\u6253\u5f00Docker app\uff0c\u767b\u9646\u540e\u624d\u80fd\u5728terminal\u4e2d\u4f7f\u7528docker\u547d\u4ee4\u3002

    $ sudo hdiutil attach Docker.dmg\n$ sudo /Volumes/Docker/Docker.app/Contents/MacOS/install\n$ sudo hdiutil detach /Volumes/Docker\n

    \u521b\u5efa\u5bb9\u5668

    docker pull ubuntu:22.04\ndocker run -it --name my_linux ubuntu:22.04 bash\n

    \u51fa\u73b0root@xxxxxxx:?# \u5373\u521b\u5efa\u6210\u529f\uff0c\u5176\u4e2dxxxxxxx\u4e00\u4e32\u662f\u5f53\u524d\u5bb9\u5668\u7684id\uff0c\u9700\u8981\u8bb0\u5f55\u4e0b\u6765\uff0c\u4e0b\u6b21\u53ef\u4ee5\u901a\u8fc7\u8be5id\u8fdb\u5165\u76f8\u540c\u5bb9\u5668\u3002

    \u5b89\u88c5\u4ea4\u53c9\u7f16\u8bd1\u5de5\u5177\u5305\uff0cqemu\uff0cgdb\uff0c\u8fd9\u51e0\u6b65\u9700\u8981\u5f00\u7740\u547d\u4ee4\u884c\u4ee3\u7406\uff0c\u622a\u56fe\u7565\u3002

    "},{"location":"docs/1-cs/os/lab/#docker_1","title":"\u806a\u660e\u5730\u4f7f\u7528docker","text":"

    \u8fd8\u662f\u6700\u597d\u914d\u7f6e\u4e00\u4e0b vscode \u91cc\u7684\u56fe\u5f62\u754c\u9762\u3002\u6b65\u9aa4\uff1a

    "},{"location":"docs/1-cs/os/lab/#_4","title":"\u65b9\u6cd5\u4ecb\u7ecd","text":"

    Warning

    TODO \u8fd9\u5757\u5e94\u8be5\u518d\u6269\u5199\u4e00\u4e0b\u7684

    "},{"location":"docs/1-cs/os/lab/#qemu-gdb","title":"qemu + gdb \u8c03\u8bd5","text":"

    \u9700\u8981\u8c03\u8bd5\u65f6\uff0c\u56e0\u4e3a\u9876\u5c42 makefile \u5e2e\u6211\u4eec\u5199\u597d\u4e86\u8c03\u8bd5\u547d\u4ee4\uff0c\u6211\u4eec\u7b2c\u4e00\u4e2a terminal \u53ea\u9700\u8981\u8f93\u5165 make debug\u3002 \u7136\u540e\u65b0\u5f00\u4e00\u4e2a terminal \u8f93\u5165 gdb-multiarch path/to/vmlinux \u5176\u4e2d vmlinux \u662f\u7f16\u8bd1\u597d\u7684\u6587\u4ef6\u3002

    gdb \u4f7f\u7528\u7684\u65b9\u6cd5/\u7a8d\u95e8

    \u663e\u793a\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u663e\u793a\u6e90\u4ee3\u7801 layout src \u663e\u793a\u6c47\u7f16\u4ee3\u7801 layout asm \u9000\u51fa\u6c47\u7f16\u663e\u793a ctrl+x, A \u9000\u51fagdb quit \u6267\u884c\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u5355\u6b65\u6267\u884c\uff0c\u8fd0\u884c\u7a0b\u5e8f\uff0c\u505c\u5728\u7b2c\u4e00\u6267\u884c\u8bed\u53e5 start \u65ad\u70b9\u540e\u7ee7\u7eed\u6267\u884c c continue \u5355\u6b65\u8c03\u8bd5\uff08\u9010c\u8bed\u8a00\u8bed\u53e5\uff0c\u51fd\u6570\u76f4\u63a5\u6267\u884c\uff09 n next \u6267\u884c\u5355\u6761\u6307\u4ee4 si step instruction \u91cd\u65b0\u5f00\u59cb\u8fd0\u884c\u6587\u4ef6\uff08run-text\uff1a\u52a0\u8f7d\u6587\u672c\u6587\u4ef6\uff0crun-bin\uff1a\u52a0\u8f7d\u4e8c\u8fdb\u5236\u6587\u4ef6\uff09 r run \u7ed3\u675f\u5f53\u524d\u51fd\u6570\uff0c\u8fd4\u56de\u5230\u51fd\u6570\u8c03\u7528\u70b9 finish \u65ad\u70b9\u6709\u5173 \u7b80\u5199 \u6307\u4ee4 \u8bbe\u7f6e\u65ad\u70b9\u5728foo\u51fd\u6570 b foo break foo \u65ad\u5728\u67d0\u5730\u5740 b * 0x80200000 break * 0x80200000 \u67e5\u770b\u7b2cm\u4e2a-\u7b2cn\u4e2a\u65ad\u70b9 info breakpoints [LIST] \u67e5\u770b\u6240\u6709\u65ad\u70b9 info breakpoints \u5220\u9664N\u53f7\u65ad\u70b9 delete [N] \u5c55\u793a\u503c\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u67e5\u770b\u51fd\u6570\u7684\u8c03\u7528\u7684\u6808\u5e27\u548c\u5c42\u7ea7\u5173\u7cfb bt backtrace \u5207\u6362\u51fd\u6570\u7684\u6808\u5e27 f frame \u6253\u5370\u503c\u53ca\u5730\u5740 p print \u67e5\u770b\u51fd\u6570\u5185\u90e8\u5c40\u90e8\u53d8\u91cf\u7684\u6570\u503c i ifo \u67e5\u770b\u5bc4\u5b58\u5668 ra \u7684\u503c i r ra \u8ffd\u8e2a\u67e5\u770b\u5177\u4f53\u53d8\u91cf\u503c display [] \u4ee5 16 \u8fdb\u5236\u6253\u5370\u00a0\u00a0\u5904\u5f00\u59cb\u7684 16 Bytes \u5185\u5bb9 x/4x \u663e\u793a\u6570\u7ec4 p *swapper_pg_dir@100 16\u8fdb\u5236\u663e\u793a\uff08x\u500d\u6570\u53ea\u80fd\u4e3a1\uff09 p/x swapper_pg_dir [start]@1

    \u8c03\u8bd5\u7684\u65f6\u5019\u9700\u8981\u770b\u4ec0\u4e48\u5462\uff1f

    \u8fd9\u662f\u6211\u521a\u4e0a\u624b\u8c03\u8bd5\u7684\u65f6\u5019\u611f\u5230\u56f0\u6270\u7684\u4e00\u4e2a\u95ee\u9898\u3002

    \u540e\u6765\u6211\u9010\u6e10\u60f3\u6e05\u695a\u7684\u662f\uff0c\u9996\u5148\u6211\u8ba4\u4e3a\u5982\u679c\u4e0d\u77e5\u9053\u6b63\u5728\u8fd0\u884c\u7684\u7a0b\u5e8f\u8fd0\u884c\u7684\u6d41\u7a0b\uff08\u6bd4\u5982\u5148\u54ea\u4e2a\u51fd\u6570\u518d\u54ea\u4e2a\u51fd\u6570\uff09\uff0c\u662f\u4e0d\u9002\u5408\u5f00\u59cb\u8c03\u8bd5\u7684\uff0c\u5e94\u5f53\u56de\u53bb\u518d\u601d\u8003\u4e00\u904d lab \u7684\u7406\u8bba\uff0c\u8d77\u7801\u77e5\u9053\u81ea\u5df1\u7a0b\u5e8f\u7684\u5404\u79cd\u9884\u671f\u7ed3\u679c\u3002\u66b4\u8bba\u4e00\u70b9\u8bf4\u5176\u5b9e\u6211\u89c9\u5f97\u8c03\u8bd5\u65f6\u957f\u5927\u4e8e\u5f00\u53d1\u65f6\u957f\u90fd\u662f\u4e0d\u592a\u597d\u7684\uff0c\u66b4\u9732\u51fa\u80af\u5b9a\u54ea\u91cc\u7406\u8bba\u6ca1\u5543\u900f\u5c31\u5f00\u59cb\u52a8\u7b14\u4e86\u3002

    \u7136\u540e\u53ef\u4ee5\u7531\u5927\u5230\u5c0f\uff0c\u6bd4\u5982\u5148\u628a\u51e0\u4e2a\u65ad\u70b9\u6253\u5728\u731c\u6d4b\u53ef\u80fd\u51fa\u9519\u4e86\u7684\u51e0\u4e2a\u51fd\u6570\u4e0a\uff0c\u786e\u5b9a\u5177\u4f53\u5728\u54ea\u4e2a\u51fd\u6570\u51fa\u9519\u540e\u518d\u9010 c \u8bed\u8a00\u884c\u8fd0\u884c\uff0c\u786e\u5b9a\u662f\u54ea\u4e2a c \u8bed\u8a00\u884c\u51fa\u9519\u540e\u518d\u9010\u6c47\u7f16\u884c\u8fd0\u884c\uff0c\u5faa\u5e8f\u6e10\u8fdb\u627e\u5230\u5177\u4f53\u51fa\u9519\u7684\u6307\u4ee4\u3002\u5728\u9644\u8fd1\u6253\u5370\u6253\u5370\u51e0\u4e2a\u5bc4\u5b58\u5668\u7684\u503c\uff08\u53ef\u4ee5\u770b\u7684\u5bc4\u5b58\u5668\u6211\u4f1a\u5728\u4e0b\u4e00\u8282\u4ecb\u7ecd\uff09\uff0c\u7136\u540e\u5728\u6b64\u57fa\u7840\u4e0a\u601d\u8003\u9519\u8bef\u539f\u56e0\u3002

    "},{"location":"docs/1-cs/os/lab/#gdb","title":"\u806a\u660e\u5730\u4f7f\u7528 gdb","text":"

    gdb \u81ea\u5e26\u7684\u547d\u4ee4\u884c ui \u7f3a\u70b9\u4e3b\u8981\u5728\u4e8e\u4e0d\u80fd\u968f\u65f6\u663e\u793a\u5bc4\u5b58\u5668\u548c\u53d8\u91cf\u7684\u503c\uff0c\u8c03\u8bd5\u4f1a\u4e0d\u8212\u670d\u3002\u6709\u4e00\u4e9b\u66f4\u597d\u7684 ui \u5de5\u5177\u3002

    \u6211\u6ca1\u6709\u914d\u6240\u4ee5\u4e0d\u80fd\u63d0\u4f9b\u5f88\u597d\u7684\u6211\u7684\u63a8\u8350\uff0c\u8d34\u4e00\u4e9b\u522b\u4eba\u7684\u5e16\u5b50\u3002\u9664\u4e86\u4e0b\u9762\u5e16\u5b50\u91cc\u63d0\u5230\u7684\u51e0\u4e2a\uff0c\u8431\u8431\u8fd8\u63d0\u5230\u4e00\u4e2a gdbpeda\u3002

    \u63a8\u8350\u51e0\u4e2a\u597d\u7528\u7684GDB\u56fe\u5f62\u5316\u529f\u80fd\u589e\u5f3a\u63d2\u4ef6

    "},{"location":"docs/1-cs/os/lab/#lab0","title":"lab0","text":"

    \u6ca1\u96be\u5ea6\u4e0d\u7528\u8bb2

    "},{"location":"docs/1-cs/os/lab/#lab1","title":"lab1","text":""},{"location":"docs/1-cs/os/lab/#c-risc-v","title":"C & RISC-V \u5185\u8054\u6c47\u7f16","text":"

    Note

    \u8fd9\u5757\u6765\u81ea\u4e8e\u5bf9 lab1 \u6587\u6863\u7684\u6574\u7406\u3002\u5e0c\u671b\u6709\u6574\u7406\u5f97\u6bd4\u539f\u6587\u6863\u53ef\u8bfb\u4e00\u4e9b\u3002

    __asm__ volatile (\n\"instruction1\\n\"\n\"instruction2\\n\"\n......\n......\n\"instruction3\\n\"\n: [out1] \"=r\" (v1),[out2] \"=r\" (v2)\n: [in1] \"r\" (v1), [in2] \"r\" (v2)\n: \"memory\"\n);\n

    \u5176\u4e2d\uff0c\u4e09\u4e2a\u00a0:\u00a0\u5c06\u6c47\u7f16\u90e8\u5206\u5206\u6210\u4e86\u56db\u90e8\u5206\u3002\u8fd9\u56db\u90e8\u5206\u4e2d\u540e\u4e09\u90e8\u5206\u4e0d\u662f\u5fc5\u987b\u7684\uff1a

    \u8fd9\u6bb5\u6682\u65f6\u7528\u4e0d\u7740\u6211\u4e0d\u5199\u4e86\uff0c\u8d34\u4e00\u6bb5lab1\u4e2d\u7684\u539f\u6587\u7ed9\u7684\u793a\u4f8b\u3002e.g. 1

    unsigned long long s_example(unsigned long long type,unsigned long long arg0) {\nunsigned long long ret_val;\n__asm__ volatile (\n\"mv x10, %[type]\\n\"\n\"mv x11, %[arg0]\\n\"\n\"mv %[ret_val], x12\"\n: [ret_val] \"=r\" (ret_val)\n: [type] \"r\" (type), [arg0] \"r\" (arg0)\n: \"memory\"\n);\nreturn ret_val;\n}\n

    e.g. 1. \u4e2d\u6307\u4ee4\u90e8\u5206\uff0c%[type]\u3001%[arg0]\u4ee5\u53ca%[ret_val]\u4ee3\u8868\u7740\u7279\u5b9a\u7684\u5bc4\u5b58\u5668\u6216\u662f\u5185\u5b58\u3002\u8f93\u5165\u8f93\u51fa\u90e8\u5206\u4e2d\uff0c[type] \"r\" (type)\u4ee3\u8868\u7740\u5c06\u00a0()\u00a0\u4e2d\u7684\u53d8\u91cf\u00a0type\u00a0\u653e\u5165\u5bc4\u5b58\u5668\u4e2d\uff08\"r\"\u00a0\u6307\u653e\u5165\u5bc4\u5b58\u5668\uff0c\u5982\u679c\u662f\u00a0\"m\"\u00a0\u5219\u4e3a\u653e\u5165\u5185\u5b58\uff09\uff0c\u5e76\u4e14\u7ed1\u5b9a\u5230\u00a0[]\u00a0\u4e2d\u547d\u540d\u7684\u7b26\u53f7\u4e2d\u53bb\u3002[ret_val] \"=r\" (ret_val)\u00a0\u4ee3\u8868\u7740\u5c06\u6c47\u7f16\u6307\u4ee4\u4e2d\u00a0%[ret_val]\u00a0\u7684\u503c\u66f4\u65b0\u5230\u53d8\u91cf\u00a0ret_val \u4e2d\u3002

    e.g. 2

    #define write_csr(reg, val) ({\n__asm__ volatile (\"csrw \" #reg \", %0\" :: \"r\"(val)); })\n

    e.g. 2. \u5b9a\u4e49\u4e86\u4e00\u4e2a\u5b8f\uff0c\u5176\u4e2d\u00a0%0\u00a0\u4ee3\u8868\u7740\u8f93\u51fa\u8f93\u5165\u90e8\u5206\u7684\u7b2c\u4e00\u4e2a\u7b26\u53f7\uff0c\u5373\u00a0val\u3002 #reg\u00a0\u662fc\u8bed\u8a00\u7684\u4e00\u4e2a\u7279\u6b8a\u5b8f\u5b9a\u4e49\u8bed\u6cd5\uff0c\u76f8\u5f53\u4e8e\u5c06reg\u8fdb\u884c\u5b8f\u66ff\u6362\u5e76\u7528\u53cc\u5f15\u53f7\u5305\u88f9\u8d77\u6765\u3002\u4f8b\u5982\u00a0write_csr(sstatus,val)\u00a0\u7ecf\u5b8f\u5c55\u5f00\u4f1a\u5f97\u5230\uff1a

    ({\n__asm__ volatile (\"csrw \" \"sstatus\" \", %0\" :: \"r\"(val)); })\n

    \u6b64\u5916\uff0c\u8fd9\u4e2a\u793a\u4f8b\u4e2d\u7684\u00a0({...})\u00a0\u8fd8\u6d89\u53ca\u4e86\u4e00\u4e2a GNU \u5bf9 C \u7684\u6269\u5c55\uff0c\u53ef\u4ee5\u53c2\u8003\u00a0Statements and Declarations in Expressions\u3002\u590d\u5408\u8bed\u53e5\u4e2d\u7684\u6700\u540e\u4e00\u9879\u5e94\u8be5\u662f\u4e00\u4e2a\u8868\u8fbe\u5f0f\uff0c\u540e\u8ddf\u4e00\u4e2a\u5206\u53f7\u00a0;\u3002\u8be5\u5b50\u8868\u8fbe\u5f0f\u7684\u503c\u7528\u4f5c\u6574\u4e2a\u8bed\u53e5\u7684\u503c\uff0c\u53ef\u4ee5\u7528\u6765\u5b9e\u73b0\u7c7b\u4f3c\u201c\u8fd4\u56de\u503c\u201d\u7684\u6548\u679c\u3002

    "},{"location":"docs/1-cs/os/lab/#_5","title":"\u7f16\u8bd1\u7684\u77e5\u8bc6","text":"

    Note

    \u8fd9\u5757\u6765\u81ea\u4e8e\u5bf9 lab1 \u6587\u6863\u7684\u6574\u7406\u3002\u5e0c\u671b\u6709\u6574\u7406\u5f97\u6bd4\u539f\u6587\u6863\u53ef\u8bfb\u4e00\u4e9b\u3002

    `vmlinux.lds`` \u662f GNU ld\uff0c\u4e00\u79cd\u94fe\u63a5\u5668\uff0c\u5c06 .o \u6587\u4ef6\u548c\u5e93\u6587\u4ef6\u8fde\u63a5\u8d77\u6765\u6210\u53ef\u6267\u884c\u6587\u4ef6\u3002ld\u4f7f\u7528\u94fe\u63a5\u811a\u672clinker script\u63a7\u5236\u3002\u8fd9\u4e2a\u6587\u4ef6\u91cc\u6709\u5199\uff1a

    \u6211\u4eec\u9605\u8bfb\u4e00\u4e0b\u8fd9\u4e2a\u94fe\u63a5\u5668\u6587\u4ef6\uff0c\u5bf9\u4e4b\u540e\u7684\u5b9e\u9a8c\u5e2e\u52a9\u633a\u5927\u3002

    \u9996\u5148\u53ef\u4ee5\u7c97\u7565\u89c2\u5bdf\u5230\uff0ckernel \u7a7a\u95f4\u91cc\u662f\u5206\u6bb5(secition)\u7684\uff0c\u4e3b\u8981\u7684section\u6709\uff1a

    \u6bb5\u540d \u4e3b\u8981\u4f5c\u7528 .text \u901a\u5e38\u5b58\u653e\u7a0b\u5e8f\u6267\u884c\u4ee3\u7801 .rodata \u901a\u5e38\u5b58\u653e\u5e38\u91cf\u7b49\u53ea\u8bfb\u6570\u636e .data \u901a\u5e38\u5b58\u653e\u5df2\u521d\u59cb\u5316\u7684\u5168\u5c40\u53d8\u91cf \u9759\u6001\u53d8\u91cf .bss \u901a\u5e38\u5b58\u653e\u672a\u521d\u59cb\u5316\u7684\u5168\u5c40\u53d8\u91cf \u9759\u6001\u53d8\u91cf

    \u518d\u7ec6\u81f4\u4e00\u70b9\u53bb\u89c2\u5bdf\u91cc\u9762\u7684\u7b26\u53f7\u3002

    \u7f16\u8bd1\u51fa\u7684\u6587\u4ef6\u91cc\uff1a

    "},{"location":"docs/1-cs/os/lab/#risc-v","title":"RISC-V \u65f6\u949f\u4e2d\u65ad","text":"

    \u64cd\u4f5c\u7cfb\u7edf\u5728\u542f\u52a8\u540e\u7531\u4e8b\u4ef6(event)\u9a71\u52a8\uff0c\u6211\u4eec\u5c06\u5f15\u5165\u4e00\u79cd\u4e8b\u4ef6trap\uff0ctrap\u7ed9\u4e86os\u4e0e\u8f6f\u786c\u4ef6\u4ea4\u4e92\u7684\u80fd\u529b\u3002\u5728boot\u9636\u6bb5opensbi\u5b9e\u73b0\u4e86M\u6001\u7684trap\u5904\u7406\u3002\u6211\u4eec\u5b9e\u73b0\u7684\u662fs\u6001\u7684trap\u5904\u7406\u3002

    \u5e76\u4e14\u6211\u4eec\u660e\u786e\u4e00\u4e0b Interrupt, Exception \u548c Trap \u7684\u533a\u522b (from riscv unprivileged spec)\uff1a

    \u5b9e\u9a8c\u624b\u518c\u5219\u7ed9\u4e86\u4e0b\u8868\uff0c\u867d\u7136\u91cc\u9762\u6ca1\u6709\u8bb2\u5230 trap\uff0c\u4f46\u662f\u8fd9\u4e2a\u5bf9\u4e8e interrupt \u548c exception \u7684\u89e3\u91ca\u66f4\u6e05\u695a\u3002

    Interrupt Exception hardware generated software generated Asynchronous external requests (generated by e.g. keyboard or printer) synchronous internal requests for services based upon abnormal events (generated by e.g. illegal instructions, illegal address, overflow, etc.) normal events abnormal events

    \u7406\u89e3\u4e86\u4e0a\u8ff0\u4e24\u4e2a\u6982\u5ff5\u540e\u53ef\u4ee5\u628a trap \u5f53\u4f5c\u4e00\u79cd\u7edf\u79f0\uff0c\u53ef\u4ee5\u7406\u89e3\u4e3a trap = interrupt + exception\u3002\u6211\u4eec\u540e\u7eed\u5b9e\u73b0\u7684 trap_handler() \u65e2\u8981\u5904\u7406\u4e2d\u65ad\u4e5f\u8981\u5904\u7406\u5f02\u5e38\u3002

    \u8981\u5b9e\u73b0\u7684\u4e2d\u65ad\u7684\u6d41\u7a0b\u5982\u4e0b\uff0c\u53ef\u4ee5\u53c2\u7167\u8fd9\u4e2a\u5b8c\u6210 do_timer() switch_to() schedule() \u7b49\u51fd\u6570\uff1a

    "},{"location":"docs/1-cs/os/lab/#riscv","title":"RISCV \u5bc4\u5b58\u5668","text":"

    \u56de\u5fc6\u5185\u5b58\u7ed3\u6784\uff08\u5982\u679c\u4f60\u660e\u786e\u77e5\u9053\u5bc4\u5b58\u5668\u662f\u4ec0\u4e48\u5c31\u4e0d\u7528\u56de\u5fc6\u4e86\uff09\uff0c\u53ef\u89c1\u5bc4\u5b58\u5668\u5e76\u4e0d\u5728\u8fd0\u884c\u5185\u5b58\u91cc\uff1a

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [cache] - [\u5185\u5b58] - [\u5916\u5b58]\n

    riscv\u670932\u4e2a\u901a\u7528\u5bc4\u5b58\u5668 + \u5f88\u591a\u63a7\u5236\u72b6\u6001\u5bc4\u5b58\u5668 (control and status registers (CSRs))\u3002riscv \u7ed9\u6bcf\u4e2a\u5bc4\u5b58\u5668\u6709\u4e2a\u5143\u4fe1\u606f\uff0c\u8fd9\u4e2a\u5143\u4fe1\u606f\u5171\u7528 12-bit \u6765\u5b58\u50a8\u5373 csr[11:0]\uff0c\u6240\u4ee5\u4e00\u5171\u652f\u6301 4096 \u4e2a\u5bc4\u5b58\u5668\u3002\u5177\u4f53\u800c\u8a00\uff0ccsr[11:0] \u8fd9\u4e2a\u6570\u636e\u7ed3\u6784\u6bcf\u4e2a\u4f4d\u7684\u610f\u4e49\u5206\u914d\u5982\u4e0b\uff1a

    \u4f4d\u6570 11:10 9:8 7:4 \u957f\u5ea6 2 2 4 \u4f5c\u7528 11=read-only\uff0cother=read/write\uff1f \u80fd\u8bbf\u95ee\u8be5csr\u7684\u6700\u4f4e\u7684\u6743\u9650\u6a21\u5f0f \u6211\u731c\u662f\u4fdd\u7559\u7ed9\u6bcf\u4e2acsr\u7279\u5b9a\u7684

    \u9996\u5148\uff0c\u901a\u7528\u5bc4\u5b58\u5668\u6709\u5982\u4e0b\u8fd9\u4e9b\uff1a

    \u5728\u7f16\u5199\u6c47\u7f16\u4ee3\u7801\u7684\u65f6\u5019\u4e00\u822c\u4f7f\u7528\u5bc4\u5b58\u5668\u7684abi\u7684\u540d\u5b57\u800c\u4e0d\u662f\u5bc4\u5b58\u5668\u7684\u7f16\u53f7

    \u800c\u4e0b\u9762\u8981\u5355\u72ec\u8bb2\u4e00\u4e0b csr\u3002

    sstatus (supervisor status register)

    The sstatus register is an SXLEN(\u4ee3\u886832\u621664)-bit read/write register formatted as follows. \u6211\u4eec\u7528\u7684\u662f64\u4f4d\u3002

    \u4e5f\u5c31\u662f\u8bf4\u8fd9\u4e2a\u5bc4\u5b58\u5668\u628a\u5f88\u591a\u4e8b\u4ef6\u7684\u72b6\u6001\u90fd\u75280\u62161\u8868\u793a\uff0c\u62fc\u5230\u4e86\u540c\u4e00\u4e2a\u5bc4\u5b58\u5668\u91cc\u3002

    \u4f4d\u6570 \u540d\u79f0 \u7f6e1\u8868\u793a \u7f6e0\u8868\u793a 1 SIE \u54cd\u5e94\u6240\u6709\u7684S\u6001trap \u7981\u7528\u6240\u6709S\u6001trap 5 SPIE \u5728trap\u53d1\u751f\u524d\u7684SIE=1 \u5728trap\u53d1\u751f\u524d\u7684SIE=0 8 SPP \u5f53\u4e2d\u65ad\u53d1\u751f\u5b8c\u7684\u65f6\u5019\uff0c\u8fd4\u56de\u5230S-mode \u5f53\u4e2d\u65ad\u53d1\u751f\u5b8c\u7684\u65f6\u5019\uff0c\u8fd4\u56de\u5230U-mode

    \u624b\u518c\u91cc\u8fd8\u4ecb\u7ecd\u7684\u4f4d\u6709

    sie (supervisor interrupt enable register)

    \u5982\u679c\u5f00\u542f\u4e86sstatus[SIE]\uff0c\u5c31\u4f1a\u6839\u636esie\u4e2d\u7684\u6bd4\u7279\u4f4d\uff0c\u51b3\u5b9a\u662f\u5426\u5904\u7406interrupt

    Bits sip.SEIP and sie.SEIE are the interrupt-pending and interrupt-enable bits for supervisor- level external interrupts. If implemented, SEIP is read-only in sip, and is set and cleared by the execution environment, typically through a platform-specific interrupt controller. Bits sip.STIP and sie.STIE are the interrupt-pending and interrupt-enable bits for supervisor- level timer interrupts. If implemented, STIP is read-only in sip, and is set and cleared by the execution environment. Bits sip.SSIP and sie.SSIE are the interrupt-pending and interrupt-enable bits for supervisor- level software interrupts. If implemented, SSIP is writable in sip and may also be set to 1 by a platform-specific interrupt controller.

    stvec (supervisor trap vector base address register)

    \u4e2d\u65ad\u5411\u91cf\u8868\u57fa\u5740.

    WARL\u662f\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f\u7684\u5730\u5740

    MODE\u662f

    Value mode \u63cf\u8ff0 0 Direct \u6a21\u5f0f \u9002\u7528\u4e8e\u7cfb\u7edf\u4e2d\u53ea\u6709\u4e00\u4e2a\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f, \u5176\u6307\u5411\u4e2d\u65ad\u5904\u7406\u5165\u53e3\u51fd\u6570 \uff08 \u672c\u5b9e\u9a8c\u4e2d\u6211\u4eec\u6240\u7528\u7684\u6a21\u5f0f \uff09 1 Vectored\u6a21\u5f0f \u6307\u5411\u4e2d\u65ad\u5411\u91cf\u8868\uff0c \u9002\u7528\u4e8e\u7cfb\u7edf\u4e2d\u6709\u591a\u4e2a\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f \u22652 \u4fdd\u7559

    sscratch (supervisor scratch register)

    Typically, sscratch is used to hold a pointer to the hart-local supervisor context while the hart is executing user mode. At the beginning of a trap handler, sscratch is swapped with a user register to provide an initial working register.

    \u5728\u672c\u6b21\u5b9e\u9a8c\u4e2d\uff0c\u6211\u4eec\u62ffsscratch\u8bb0\u5f55s-mode\u7684stack pointer\uff0c\u5728trap\u53d1\u751f\u7684\u65f6\u5019\u4e0eu-mode stack pointer\u4ea4\u6362\uff08\u597d\u50cf\u662f\u6765\u7740\u5fd8\u4e86TODO\u4e00\u4f1a\u6838\u5b9e\uff09

    sepc (supervisor exception program counter)

    \u4f1a\u8bb0\u5f55 trap \u5904\u7406\u8fc7\u540e\u7684\u8fd4\u56de\u5730\u5740\u3002

    scause (supervisor cause register)

    \u4f1a\u8bb0\u5f55 trap \u53d1\u751f\u7684\u539f\u56e0\uff0c\u8fd8\u4f1a\u8bb0\u5f55\u8be5 trap \u662f\u00a0Interrupt\u00a0\u8fd8\u662f\u00a0Exception\u3002\u539f\u56e0\u6709\u4ee5\u4e0b\u51e0\u79cd\uff1a

    stval (supervisor trap value register)

    The stval register can optionally also be used to return the faulting instruction bits on an illegal instruction exception (sepc points to the faulting instruction in memory). If stval is written with a nonzero value when an illegal-instruction exception occurs, then stval will contain the shortest of:

    \u0088 the actual faulting instruction \u0088 the first ILEN bits of the faulting instruction \u0088 the first SXLEN bits of the faulting instruction

    The value loaded into stval on an illegal-instruction exception is right-justified and all unused upper bits are cleared to zero.

    satp (supervisor address translation and protection register)

    \u8bb0\u5f55\u6700\u9ad8\u7ea7\u9875\u8868\u7684\u7269\u7406\u5730\u5740\u3002MODE\u4f4d=8\u65f6\uff0c\u4f7f\u7528Sv39\u6a21\u5f0f\u865a\u62df\u5730\u5740\uff08\u672c\u5b9e\u9a8c\uff09

    \u4ee5\u4e0b\u662f\u65f6\u949f\u4e2d\u65ad\u76f8\u5173\u7684\u5bc4\u5b58\u5668\uff1a

    mtime

    \u8ba1\u65f6\u5668\uff0c\u4ee5\u6052\u5b9a\u9891\u7387\u81ea\u589e\uff08\u6211\u8bb0\u5f97\u5728\u672c\u5b9e\u9a8c\u91cc\u662f\u591a\u5c11\u5206\u4e4b\u4e00\u79d2\uff09

    mtimecmp\uff08machine timer register\uff09

    \u4e0b\u4e00\u6b21\u65f6\u949f\u4e2d\u65ad\u7684\u4e2d\u65ad\u70b9

    mcounteren\uff08counter enable register\uff09

    \uff08\u672c\u5b9e\u9a8c\u4e2d\u4e0d\u7528\u7ba1\uff0c\u4f46\u662f\u8bf4\u660e\u4e00\u4e0b\uff1a\uff09mtime\u672c\u6765\u662fm\u6001\u7684\u5bc4\u5b58\u5668\uff0c\u5728s\u6001\u4e0d\u80fd\u8bfb\u5199\uff0c\u4f46\u662fopensbi\u5df2\u7ecf\u8bbe\u7f6e\u8fc7\u53ef\u4ee5\u8bfb\u5199m\u6001

    "},{"location":"docs/1-cs/os/lab/#_6","title":"\u5bc4\u5b58\u5668\u64cd\u4f5c","text":"

    \u64cd\u4f5ccsr\u5bc4\u5b58\u5668\u7684riscv\u6307\u4ee4\u96c6 TODO\u5f85\u6574\u7406

    func scr rs1 rd

    \u5316\u7528\u4e00\u4e2a\u6682\u65f6\u4e0d\u60f3\u53bb\u627e\u6765\u6e90\u7684 CSDN \u5e16\u5b50\u7684\u603b\u7ed3\uff1a

    "},{"location":"docs/1-cs/os/lab/#lab2","title":"lab2","text":""},{"location":"docs/1-cs/os/lab/#_7","title":"\u7ebf\u7a0b","text":"

    \u672c\u5b9e\u9a8c\u5efa\u7acb\u7684\u7ebf\u7a0b\u90fd\u662f\u5185\u6838\u6001\u7ebf\u7a0b\u3002\u4e00\u4e2a\u4f9d\u636e\u5c31\u662f\u67d0\u4e2a\u7ebf\u7a0b trap \u540e\u4e0d\u4f1a\u963b\u585e\u5176\u5b83\u7ebf\u7a0b\u3002

    \u7ebf\u7a0b\u7684 task_struct \u53ef\u4ee5\u7406\u89e3\u4e3a\u7406\u8bba\u8bfe\u4e0a\u8bb2\u7684 PCB (\u662f\u4e0d\u662f\u8be5\u53eb TCB\uff1f)\u3002\u91cc\u9762\u7684\u4e1c\u897f\u4f1a\u968f\u7740\u9010\u4e2a lab \u6dfb\u52a0\u8fdb\u53bb\uff0c\u6700\u7ec8\u4f1a\u6709\u4ee5\u4e0b\u4e1c\u897f\uff1a

    Warning

    TODO \u4ee5\u4e0b\u5185\u5bb9\u9700\u8981\u518d\u68c0\u67e5\uff0c\u5ffd\u7136\u5206\u4e0d\u6e05\u6bcf\u4e2a\u7ebf\u7a0b\u603b\u5171\u662f\u5f00\u4e86\u4e00\u4e2a\u8fd8\u662f\u4e24\u4e2a\u5185\u5b58\u7a7a\u95f4

    \u7ebf\u7a0b\u5185\u5b58\u7a7a\u95f4\u7ed3\u6784\u5982\u4e0b\u3002

    \u5185\u6838\u865a\u62df\u5b58\u50a8\u5668 \u7528\u6237\u4e0d\u53ef\u89c1\u7684\u5b58\u50a8\u5668 0xc000 0000 \u7528\u6237\u6808 \u2190 sp 0x4000 0000 \u5171\u4eab\u5e93\u7684\u5b58\u50a8\u5668\u6620\u5c04\u533a\u57df \u8fd0\u884c\u65f6\u5806\uff08\u7531malloc\u521b\u5efa\uff09 \u2190 brk \u8bfb\u5199\u6bb5 .data .bss \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d \u53ea\u8bfb\u6bb5 .init .text .rodata \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d 0x0804 8000 \u672a\u7528\u7684 \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d"},{"location":"docs/1-cs/os/lab/#lab3","title":"lab3","text":"

    \u5230\u672c\u5b9e\u9a8c\u7ed3\u675f\u65f6\uff0c\u6211\u4eec\u7684\u7a0b\u5e8f\u5c06\u8981\u5b9e\u73b0\u8fd9\u6837\u4e00\u4e2a\u4ece\u542f\u52a8\u5230\u5f00\u542f\u6620\u5c04\u7684\u8fc7\u7a0b\uff08\u4e5f\u5bf9\u5e94 head.S \u5f00\u5934\u7684\u4e00\u5806\u51fd\u6570\u8c03\u7528\u6d41\u7a0b\uff09\uff1a

    "},{"location":"docs/1-cs/os/lab/#virtual-memory","title":"virtual memory","text":"

    lab2\u4e2d\u6211\u4eec\u505a\u7684\u90fd\u662f\u5185\u6838\u7ebf\u7a0b\uff0c\u53ef\u4ee5\u5171\u4eab\u8fd0\u884c\u7a7a\u95f4\uff0c\u5373\u8fd0\u884c\u4e0d\u540c\u7ebf\u7a0b\u5bf9\u5185\u8bad\u7684\u4fee\u6539\u662f\u76f8\u4e92\u53ef\u89c1\u7684\u3002\u5982\u679c\u9700\u8981\u7ebf\u7a0b\u76f8\u4e92\u9694\u79bb\u5c31\u9700\u8981\u5f15\u5165\u865a\u62df\u5185\u5b58\uff0c\u65b9\u4fbf\u591a\u7ebf\u7a0b\u9ad8\u6548\u5171\u4eab\u5185\u5b58\u3002\u5982\u679c\u5f88\u865a\u5730\u53bb\u8bb2\u865a\u62df\u5185\u5b58\u7684\u4f5c\u7528\uff1a

    \u6211\u4eec\u8981\u5b9e\u73b0\u7684\u865a\u62df\u5185\u5b58\u5e03\u5c40\uff0c\u9996\u5148\u7528\u4e00\u4e2a\u622a\u56fe\u6765\u7406\u89e3\uff1a

    \u4f4e\u5730\u5740<-                                       ->\u9ad8\u5730\u5740\n\nstart_address             end_address\n    0x0                  0x3fffffffff\n     \u2502                        \u2502\n\u250c\u2500\u2500\u2500\u2500\u2518                  \u250c\u2500\u2500\u2500\u2500\u2500\u2518\n\u2193        256G           \u2193                                \n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502      User Space       \u2502    ...   \u2502  Kernel Space  \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n                                   \u2191      256G      \u2191\n                      \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518                \u2502 \n                      \u2502                             \u2502\n              0xffffffc000000000           0xffffffffffffffff\n                start_address                  end_address\n

    \u7136\u540e\u5fc5\u987b\u8981\u641e\u660e\u767d\uff1a\u865a\u62df\u5185\u5b58\u4ece\u6765\u6ca1\u6709\u88ab\u771f\u6b63\u5f00\u8f9f\u8fc7\uff0c\u88ab\u771f\u6b63\u5f00\u8f9f\u7684\u53ea\u6709\u7269\u7406\u5185\u5b58\u3002\u6211\u4eec\u5728\u7a0b\u5e8f\u5b9e\u73b0\u8fc7\u7a0b\u4e2d\u5f00\u7684\u53d8\u91cf\u548c alloc \u7684 page\uff0c\u90fd\u662f\u5f00\u5728 kernel \u7684\u6808\u6216\u8005\u5806\u4e0a\uff08.data\u548c.bss\u6bb5\uff09\uff0c\u56e0\u4e3a\u67e5\u5730\u5740\u65f6\u53ef\u4ee5\u67e5\u5230\u5b83\u4eec\u7684\u7269\u7406\u5730\u5740\u3002\u800c\u5404\u79cd csr \u5728 cpu \u91cc\uff0c\u4e0d\u4f1a\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\u3002\u800c\u672c\u6b21\u5b9e\u9a8c\u6240\u8bb2\u7684\u201c\u5f00\u542f\u865a\u62df\u5185\u5b58\u201d\uff0c\u672c\u8d28\u4e0a\u53ea\u662f\u8bbe\u8ba1\u4e00\u4e2a\u865a\u62df\u5730\u5740\u5230\u7269\u7406\u5730\u5740\u7684\u8f6c\u6362\u51fd\u6570\uff0c\u8fd9\u4e2a\u51fd\u6570\u653e\u5728\u9875\u8868\u91cc\u3002

    "},{"location":"docs/1-cs/os/lab/#sv39","title":"Sv39 \u7684\u9875\u8868\u9879","text":"

    \u7406\u89e3\u4e00\u4e0b\u9875\u8868\u9879\uff08pte\uff09\u3002\u5b83\u7684\u4f4e\u4f4d\uff1a

    "},{"location":"docs/1-cs/os/lab/#_8","title":"\u5730\u5740\u7ffb\u8bd1\u8fc7\u7a0b","text":"

    create_mapping() \u51fd\u6570\u904d\u5386\u6574\u4e2a\u6620\u5c04\u5927\u5c0f\uff0c\u4f9d\u6b21\u6309\u4e8c\u7ea7\u9875\u8868\uff08\u5373\u6839\u9875\u8868\u7684\u4e0b\u4e00\u7ea7\uff09\u2192\u4e09\u7ea7\u9875\u8868\u2192\u7269\u7406\u9875\uff0c\u68c0\u67e5\u9875\u8868\u9879\u7684V bit\u770b\u9875\u8868\u9879\u662f\u5426\u5b58\u5728\uff0c\u4e0d\u5b58\u5728\u5219\u7528kalloc() \u5206\u914d\u4e00\u9875\u4f5c\u4e3a\u9875\u8868\u76ee\u5f55\uff1b\u5b58\u5728\u5219\u5728\u9875\u8868\u9879\u4e2d\u8bb0\u5f55\u9875\u8868\u7684\u7269\u7406\u5730\u5740\u3002

    pte : [ PPN2: 53-28 ][ PPN1: 27-19 ][ PPN0: 18-10 ][ perm: 9-0 ]

    vm_addr: [ VPN2: 38-30 ][ VPN1: 29-21 ][ VPN0:20-12 ][ offset: 11-0 ]

    \u56e0\u4e3a\u67e5\u8be2\u4e09\u7ea7\u9875\u8868\u7684\u6d41\u7a0b\u4e3a\uff1a

    \u6240\u4ee5\u53cd\u63a8\u8bbe\u7f6e\u7684\u6d41\u7a0b\u4e3a\uff1a

    "},{"location":"docs/1-cs/os/lab/#heads-todo-va2pa_offset","title":"\u4e3a\u4ec0\u4e48\u5728 head.S \u91cc\u4e00\u5f00\u59cb\u8981\u7ed9\u9875\u8868\u9879\u5730\u5740 (TODO\u574f\u4e86\u4e0d\u8bb0\u5f97\u662f\u4e0d\u662f\u5b83\u4e86) \u51cf\u53bb\u4e00\u4e2a VA2PA_offset","text":"

    \u5728 2023 \u5e74\u7248\u7684\u5b9e\u9a8c\u4e2d\uff0cvmlinux.lds \u4e2d\u8bbe\u7f6e\u4e86\u5c06\u7f16\u8bd1\u51fa\u7684\u7b26\u53f7\u8868\u90fd\u7528\u865a\u62df\u5730\u5740\u6765\u8868\u793a\uff0c\u65b9\u4fbf\u8c03\u8bd5\u3002\u4e5f\u5373\u7a0b\u5e8f\u8fd0\u884c\u5230\u6b64\u5904\u8bfb\u5230\u7684\u9875\u8868\u9879\u5730\u5740\u662f\u865a\u62df\u5730\u5740\u3002\u663e\u7136\uff0c\u5728 setup_vm() \u4e4b\u524d\uff0c\u865a\u62df\u5185\u5b58\u8fd8\u6ca1\u6709\u88ab\u5f00\u542f\uff0c\u6240\u4ee5\u8981\u51cf\u6389\u4e00\u4e2a\u504f\u79fb\u91cf\u4f7f\u5176\u80fd\u8bfb\u5230\u9875\u8868\u9879\u7684\u7269\u7406\u5730\u5740\u3002\u5728 relocate: \u5904\u7406\u504f\u79fb\u4e4b\u540e\u5c31\u4e0d\u7528\u7ba1\u4e86\u3002

    "},{"location":"docs/1-cs/os/lab/#lab4","title":"lab4","text":""},{"location":"docs/1-cs/os/lab/#_9","title":"\u66f4\u65b0\u540e\u7684\u865a\u62df\u5185\u5b58\u5e03\u5c40","text":"

    \u6211\u4eec\u56de\u5fc6 lab3 \u91cc\u865a\u62df\u5730\u5740\u53ea\u7528\u4e86\u9ad8\u4f4d\uff0c\u4f4e\u4f4d\u6ca1\u6709\u7528\uff0c\u5728\u672c\u5b9e\u9a8c\u6211\u4eec\u8981\u5c06\u4f4e\u4f4d 0x0-0x4000000 \u5206\u7ed9\u7528\u6237\u8fdb\u7a0b\u3002\u800c\u7528\u6237\u8fdb\u7a0b\u7684\u4ee3\u7801\u5b9e\u9645\u5728\u7269\u7406\u5730\u5740\u4e0a\u5206\u914d\u51fa\u6765\u7684\u67d0\u4e2a\u5730\u65b9\u3002\u603b\u4e4b\uff0c\u8981\u5b9e\u73b0\u4ee5\u4e0b\u7684\u5185\u5b58\u5e03\u5c40\uff1a

                   PHY_START   new allocated memory            allocated space end                              PHY_END\n                   \u2502         \u2502                                \u2502                                                 \u2502\n                   \u25bc         \u25bc                                \u25bc                                                 \u25bc\n       \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n PA    \u2502           \u2502         \u2502 uapp (copied from _sramdisk)   \u2502                                                 \u2502\n       \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n                             \u25b2                                \u25b2\n       \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518                                \u2502\n       \u2502            (map)                                     \u2502\n       \u2502                        \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n       \u2502                        \u2502\n       \u2502                        \u2502\n       \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n VA    \u2502           UAPP         \u2502                                                                   \u2502u mode stack\u2502\n       \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n       \u25b2                                                                                                         \u25b2\n       \u2502                                                                                                         \u2502\n\n   USER_START                                                                                                USER_END\n
    "},{"location":"docs/1-cs/os/lab/#riscv_1","title":"riscv\u5904\u7406\u5668\u652f\u6301\u7684\u6a21\u5f0f","text":"

    lab3\u521b\u5efa\u7684\u90fd\u662f\u5185\u6838\u7ebf\u7a0b \u516c\u7528\u4e86\u5730\u5740\u7a7a\u95f4\uff08\u9875\u8868swapper_pg_dir\uff09\u3002\u8981\u5f15\u5165\u7528\u6237\u6001\u8fdb\u7a0b\u9700\u8981\u505a\uff1a

    \u5177\u4f53\u5728\u6211\u4eec\u7684\u5b9e\u9a8c\u64cd\u4f5c\u4e2d\uff0c\u5b9e\u73b0\u7528\u6237\u6001\u548c\u5185\u6838\u6001\u5207\u6362\u7684\u65b9\u6cd5\u662f\uff1asstatus[SUM] \u548c PTE[U]

    Warning

    \u60f3\u5199\u4e00\u4e0b\u5728\u6c47\u7f16\u4ee3\u7801\u91cc\u7684\u64cd\u4f5c\uff0c\u5fd8\u5e72\u51c0\u4e86\uff0c\u6574\u4f53\u601d\u8def\u662f\u8fd9\u6837\u7684\uff0c\u4f46\u4e00\u4e9b\u7ec6\u8282\u5f85\u6838\u5b9e

    \u5e76\u4e14\u5728\u6c47\u7f16\u4ee3\u7801\u91cc\u9700\u8981\u5b9e\u73b0\u4e00\u7cfb\u5217 csr \u8bfb\u5199\u64cd\u4f5c\uff1a

    "},{"location":"docs/1-cs/os/lab/#buddy-system","title":"buddy system","text":"

    \u4e00\u79cd\u7269\u7406\u5185\u5b58\u7ba1\u7406\u7b97\u6cd5\uff0c\u7a7a\u95f2\u7a7a\u95f4\u9996\u5148\u88ab\u770b\u6210 2^N \u4e2a\u7269\u7406\u9875\u7684\u5927\u7a7a\u95f4\uff0c\u5f53\u4e00\u4e2a\u5927\u5c0f\u4e3a m \u7684\u9875\u8bf7\u6c42\u5185\u5b58\u5206\u914d\u65f6\uff0c\u4e0d\u505c\u628a\u7a7a\u95f4 /2 \u5212\u5206\uff0c\u6700\u540e\u627e\u5230\u6700\u63a5\u8fd1m\u76842\u7684\u6b21\u65b9\u7684\u4e00\u4e2a\u7a7a\u95f4\u5927\u5c0f\u5206\u7ed9 m\u3002\u5f53\u5757\u91ca\u653e\u65f6\uff0c\u5206\u914d\u5668\u5c31\u4f1a\u627e\u5230\u5176\u5b83\u7a7a\u95f2\u7684\u4f19\u4f34\u5757\u53bb\u5408\u5e76\u3002\u5b83\u7684\u5b9e\u73b0\u5728\u8fd9\u4e2a\u6587\u7ae0\u91cc\u8bb2\u5f97\u66f4\u597d Lab 6\uff1aRISC-V \u52a8\u6001\u5185\u5b58\u5206\u914d\u4e0e\u7f3a\u9875\u5f02\u5e38\u5904\u7406 - \u77e5\u4e4e (zhihu.com)\u3002

    "},{"location":"docs/1-cs/os/lab/#elf","title":"elf \u6587\u4ef6","text":"

    \u4e00\u4e2a elf \u6587\u4ef6\u50cf\u4e00\u4e2a\u5c01\u88c5\u590d\u6742\u7248\u7684\u4e8c\u8fdb\u5236\u7528\u6237\u7a0b\u5e8f\u3002\u7528\u62bd\u8c61\u7684\u753b\u56fe\u7ed9\u5b83\u7684\u7ed3\u6784\u505a\u4e00\u4e2a\u6bd4\u55bb\uff08\u5bf9\u4e0d\u8d77\u592a\u62bd\u8c61\u4e86\uff09\uff1a

    Elf_Ehdr     ehdr->e_phoff\n\u2b07\ufe0f            \u2b07\ufe0f\n[            [type: ???][type: LOAD][type: ???] ]\n

    \u5c31\u662f elf \u6587\u4ef6\u91cc\u6563\u843d\u7740\u51e0\u4e2a\u5c0f\u6bb5\uff0c\u5176\u4e2d\u4e00\u4e2a\u7c7b\u578b\u4e3a LOAD \u7684\u6bb5\u662f\u9700\u8981\u590d\u5236\u5230\u7ebf\u7a0b\u4ee3\u7801\u6bb5\u7684\uff0c\u4f46\u4e0d\u4e00\u5b9a\u590d\u5236\u5230\u7ebf\u7a0b\u5934\u7684\u8d77\u59cb\u5730\u5740 0x0\uff0cp_vaddr \u4f1a\u544a\u8bc9\u4f60\u8fd9\u6bb5\u4ee3\u7801\u5e0c\u671b\u88ab\u590d\u5236\u5230\u54ea\u91cc\u53bb\u3002e_entry \u4e5f\u8d34\u5fc3\u544a\u8bc9\u4f60\u7b2c\u4e00\u6761\u4ee3\u7801\u6307\u4ee4\u7684\u8d77\u59cb\u5730\u5740\u5728\u54ea\u3002\u603b\u4e4b\uff0c\u4f60\u9700\u8981\u5148\u901a\u8fc7\u4e00\u4e9b\u504f\u79fb\u91cf\u5728 Elf64_Ehdr \u8fd9\u4e2a\u6307\u9488\u91cc\u627e\u5230\u7b2c\u4e00\u4e2a segment\uff0c\u7136\u540e\u4ee5\u4e00\u4e2a Elf63_phdr \u7684\u5927\u5c0f\u4e3a\u5355\u4f4d\uff0c\u6328\u4e2a\u53bb\u5bfb\u627e\u4e00\u4e2a\u7c7b\u578b\u4e3a LOAD \u7684 segment\u3002\u7b49\u627e\u5230\u4e86\u5c31\u53ef\u4ee5\u62f7\u8d1d\u4e86\u3002

    \u5982\u679c\u4f60\u6309\u7167\u4e00\u5806\u6307\u9488\u7684\u5199\u6cd5\u88ab\u641e\u5f97\u6655\u5934\u8f6c\u5411\uff0c\u751a\u81f3\u53ea\u662f\u5148\u7528 readelf -h \u67e5\u770b\u4e00\u4e0b elf \u6587\u4ef6\u91cc\u5404\u4e2a\u4e1c\u897f\u7684\u5730\u5740\uff08\u67e5\u770b\u540e\u53ef\u4ee5\u53d1\u73b0\u4e0e\u5b9e\u9a8c\u6307\u5bfc\u4e2d\u7ed9\u7684\u4f8b\u5b50\u5c31\u662f\u540c\u4e00\u4e2a\u6587\u4ef6\uff09\uff0c\u7136\u540e\u76f4\u63a5\u628a\u6574\u4e2a uapp \u7a0b\u5e8f\u5168\u90e8\u62f7\u5230\u8fdb\u7a0b\u91cc\u6765\uff0c\u76f4\u63a5\u628a __dummy \u8fd4\u56de\u5730\u5740\u6307\u5230\u4f60\u5728\u6587\u4ef6\u91cc\u8bfb\u51fa\u6765\u7684\u90a3\u4e2a\u4ee3\u7801\u8d77\u59cb\u5730\u5740\uff0c\u751a\u81f3\u90fd\u80fd\u8dd1\u3002\u5728\u8dd1\u8d77\u6765\u4e4b\u540e\uff0c\u6839\u636e\u4f60\u7684\u7406\u89e3\u4e00\u70b9\u4e00\u70b9\u628a\u8bbe\u7f6e\u6307\u9488\u7684\u4ee3\u7801\u6309\u7167\u542b\u4e49\u66ff\u6362\u4e0a\uff0c\u6211\u611f\u89c9\u8fd9\u6837\u53cd\u7740\u505a\u4e5f\u884c\u3002

    "},{"location":"docs/1-cs/os/lab/#lab5","title":"lab5","text":"

    Warning

    \u4e0b\u9762\u51e0\u4e2a\u5b9e\u9a8c\u6211\u5199\u5f97\u6709\u70b9\u7b80\u7565\uff0c\u5c0f\u90e8\u5206\u56e0\u4e3a\u6211\u4e0d\u8bb0\u5f97\u4e86\uff0c\u5927\u90e8\u5206\u56e0\u4e3a\u6211\u81ea\u6211\u611f\u89c9\u6ca1\u6709\u5403\u900f\u8fd9\u4e2a\u5b9e\u9a8c\uff0c\u4e0d\u73ed\u95e8\u5f04\u65a7\u4e86\u3002\u4f46\u662f\u8fd9\u4e2a\u5730\u65b9\u53d1\u81ea\u5185\u5fc3\u5730\u60f3\u7559\u4e2a TODO \u5e0c\u671b\u80fd\u6709\u673a\u4f1a\u8865\u5b8c\u3002

    \u672c\u5b9e\u9a8c\u4e0e lab4 \u5185\u5b58\u5206\u914d\u7684\u533a\u522b\u662f\uff0c\u4e3a\u4e86\u9632\u6b62\u7269\u7406\u5185\u5b58\u4e0d\u8db3\uff0c\u5728 task \u521d\u59cb\u5316\u8bf7\u6c42\u7a7a\u95f4\u65f6\uff0c\u5148\u4e0d\u5206\u914d\u7269\u7406\u5185\u5b58\uff0c\u800c\u662f\u7528 do_mmap() \u5148\u628a task \u7684\u8bf7\u6c42\u7684\u6240\u6709\u53c2\u6570\u8bb0\u5f55\u4e0b\u6765\uff0c\u7b49 task \u771f\u6b63\u53bb\u8bbf\u95ee\u7684\u65f6\u5019\uff0c\u5fc5\u7136\u4f1a\u89e6\u53d1 page fault\uff0c\u7136\u540e\u5728 page fault handler \u91cc\u6839\u636e\u8bb0\u5f55\u7684\u53c2\u6570\uff0c\u518d\u5206\u914d\u7269\u7406\u5185\u5b58\u3002

    "},{"location":"docs/1-cs/os/lab/#lab6","title":"lab6","text":"

    \u5b9e\u9a8c\u4e3b\u8981\u76ee\u6807\u662f\u5b9e\u73b0\u521b\u5efa\u5b50\u8fdb\u7a0b\u7684\u903b\u8f91\uff0c\u5373\u5728\u7528\u6237\u7a0b\u5e8f\u8c03\u7528fork()\u51fd\u6570\uff0c\u4ea7\u751f220\u53f7\u7cfb\u7edf\u8c03\u7528\u7684\u65f6\u5019\uff0c\u5728sys_clone()\u8fd9\u4e2a\u51fd\u6570\u91cc\u521b\u5efa\u5b50\u8fdb\u7a0b\uff0c\u5e76\u4f7f\u5176\u52a0\u5165\u88ab\u8c03\u7528\u7684task\u961f\u5217\u3002

    "},{"location":"docs/1-cs/os/lab/#lab7","title":"lab7","text":"

    Warning

    lab7 \u6211\u53ea\u5b8c\u6210\u4e86\u5360 60% \u7684\u7b2c\u4e00\u90e8\u5206\uff0c\u4f46\u5176\u5b9e\u5de5\u4f5c\u91cf\u6bd4\u8f83\u5927\u7684\u8fd8\u5728\u7b2c\u4e8c\u90e8\u5206\u3002\u6211\u8fd9\u91cc\u53ea\u80fd\u603b\u7ed3\u7b2c\u4e00\u90e8\u5206\u4e86\u3002

    \u672c\u5b9e\u9a8c\u6bcf\u4e2atask\u90fd\u6709\u4e00\u4e2a\u7ed3\u6784\u4f53\u53bb\u7ef4\u62a4\u5df2\u7ecf\u6253\u5f00\u7684\u6587\u4ef6\u8868\u3002\u672c\u5b9e\u9a8c\u9996\u5148\u4fee\u6539task struct\uff0c\u5728\u6bcf\u4e2atask struct\u4e2d\u6dfb\u52a0\u4e86\u4e00\u4e2a\u9875(struct file* \u578b)\u53bb\u7ef4\u62a4\u8fd9\u4e2a\u6587\u4ef6\u8868\u3002

    \u6bcf\u4e2a\u6587\u4ef6\u8868\u6709\u4e00\u4e9b\u51fd\u6570\u6307\u9488\uff0c\u5206\u522b\u6307\u5411\u5bf9\u6587\u4ef6\u7684\u8bfb\u5199\u64cd\u4f5c\u51fd\u6570\u3002\u9996\u5148\u9700\u8981\u5b9e\u73b0\u8fd9\u4e9b\u51fd\u6570\uff0c\u5982 stdout_write() \u548c stdin_read() \u7b49\u3002

    \u5f53\u7528\u6237\u7a0b\u5e8f\u4ea7\u751f\u6587\u4ef6\u8bfb\u5199\u7684 system call \u65f6\uff0ctrap_handler() \u4e2d\u9700\u8981\u5b9e\u73b0\u5bf9\u8fd9\u4e9b system call \u7684\u5904\u7406\u51fd\u6570\u3002\u5177\u4f53\u64cd\u4f5c\u5c31\u662f\u6355\u83b7\uff0c\u7136\u540e\u4ec0\u4e48\u4e5f\u4e0d\u505a\uff0c\u76f4\u63a5\u628a\u53c2\u6570\u4ea4\u7ed9\u4e0a\u8ff0\u5b9e\u73b0\u7684\u6587\u4ef6\u8bfb\u5199\u51fd\u6570\u6765\u64cd\u4f5c\u3002

    "},{"location":"docs/1-cs/os/lab/#_10","title":"\u5e38\u89c1\u95ee\u9898\u4e4b\u8865\u5145\u53c8\u540d\u6211\u4e4b\u603b\u662f\u9047\u89c1\u95ee\u9898","text":"

    Q1: \u8fd0\u884c\u53d1\u73b0\u7a0b\u5e8f\u5728\u51e0\u4e2a\u521d\u59cb\u5316\u51fd\u6570\u4e4b\u95f4\u6765\u56de\u8df3\u8dc3\uff0c\u6bd4\u5982\u5df2\u7ecf\u5230\u4e86 set_up_vm_final()\uff0c\u53c8\u8df3\u56de set_up_vm()\uff0c\u518d\u5f80\u4e0b\u8fd0\u884c\u5c31\u5728\u8fd9\u51e0\u4e2a\u51fd\u6570\u4e4b\u95f4\u5faa\u73af\u3002\u8fdb\u5165 gdb \u8c03\u8bd5\uff0c\u5219\u53d1\u73b0\u53d1\u751f\u8df3\u8f6c\u7684\u5730\u65b9\u5e76\u6ca1\u6709\u4efb\u4f55 branch \u6216\u8005 call \u8bed\u53e5\u6307\u5411\u8df3\u5f80\u7684\u5730\u5740\uff0c\u4f46\u662f\u80fd\u89c2\u5bdf\u5230\u51fa\u73b0\u8df3\u8f6c\u7684\u5730\u65b9\uff0c\u5f80\u5f80\u662f\u8fdb\u4e86 memset() \u6216\u8005 memcopy() \u51fd\u6570\u3002

    A1: \u6574\u4e2a\u5b9e\u9a8c\u8fc7\u7a0b\u4e2d\u6211\u9047\u5230\u4e86\u4e09\u56db\u6b21\uff0c\u4e00\u5f00\u59cb\u89c9\u5f97\u662f\u4ee5\u5947\u602a\u7684\u65b9\u5f0f\u89e3\u51b3\u4e86\uff08\u6bd4\u5982\uff0c\u7a81\u7136\u53d1\u73b0\u81ea\u5df1\u5728\u521d\u59cb\u5316\u8fdb\u7a0b\uff0c\u5f15\u5165\u5916\u90e8\u9875\u8868\u65f6\u7528\u5230\u7684\u4ee3\u7801\u662f extern unsigned long *swapper_pg_dir;\uff0c\u800c\u4e0d\u662f extern unsigned long swapper_pg_dir[512] __attribute__((__aligned__(0x1000)));\uff0c\u5373\uff0c\u7f3a\u5c11\u4e86\u4e00\u4e2a\u5730\u5740\u5bf9\u9f50\u3002\u540c\u5b66\u6307\u51fa\u5982\u679c\u6ca1\u6709\u5bf9\u9f50\uff0c\u53ef\u80fd\u4f1a\u5bfc\u81f4\u9875\u8868\u8fb9\u7f18\u7684\u4e00\u4e9b\u6570\u636e\u7684\u4e22\u5931\u635f\u574f\u3002\uff09\uff0c\u540e\u6765\u6162\u6162\u53d1\u73b0\u89c4\u5f8b\u662f\uff1a\u53d1\u751f\u8fd9\u6837\u8df3\u8f6c\u7684\u6307\u4ee4\uff0c\u90fd\u5728\u5c1d\u8bd5\u5f80 0x80000000 \u8fd9\u4e2a\u7269\u7406\u5730\u5740\u4ee5\u4e0b\u7684\u7269\u7406\u5730\u5740\u5199\u4e1c\u897f\u3002\u6211\u4eec\u6ce8\u610f\u5230 qemu \u63d0\u4f9b\u7ed9\u6211\u4eec\u7684\u7269\u7406\u5730\u5740\u90fd\u662f 0x80000000 \u4ee5\u4e0a\u7684\u5730\u5740\uff0c\u867d\u7136\u6ca1\u6709\u8003\u8bc1\uff0c\u4f46\u662f\u5408\u7406\u731c\u6d4b\u5176\u4e0b\u7684\u5730\u5740\u662f qemu \u81ea\u5df1\u7684\u4ee3\u7801\u533a\uff0c\u652f\u6301 qemu \u81ea\u5df1\u7684\u8fd0\u884c\u903b\u8f91\u3002\u5982\u679c\u4e0d\u5c0f\u5fc3\u5199\u5230\u4e86\u8fd9\u4e2a\u5730\u65b9\uff0c\u5f53\u7136\u53ef\u80fd\u53d1\u751f\u4e0d\u80fd\u89e3\u91ca\u7684 qemu \u884c\u4e3a\u3002

    \u6240\u4ee5\u5982\u679c\u9047\u5230\u8fd9\u4e2a\u95ee\u9898\uff0c\u53ef\u884c\u7684\u4e00\u6b65\u4e00\u6b65\u68c0\u67e5\u65b9\u6cd5\u662f\uff1a

    \u603b\u4e4b\uff0c\u6839\u672c\u76ee\u6807\u662f\u53bb\u770b\u4e00\u4e0b\u6709\u6ca1\u6709\u5f80\u7269\u7406\u5730\u5740 0x80000000 \u4ee5\u4e0b\u7684\u5730\u65b9\u5199\u4e1c\u897f\u3002

    Q2: \u8fd0\u884c\u7a0b\u5e8f\u5230\u4e00\u534a\u5361\u4f4f\uff0c\u6ca1\u6709\u4efb\u4f55\u8f93\u51fa\u4e86\uff0c\u8c03\u8bd5\u53d1\u73b0\u6700\u540e\u662f\u5728 __dummy \u7684 sret \u540e\u5361\u4f4f\u4e86\u3002

    A2: \u53ef\u4ee5\u5148\u5b9e\u73b0\u4e00\u4e2a\u6f02\u4eae\u70b9\u7684 trap_handler() \u5e2e\u52a9\u8c03\u8bd5\u3002\u8fd9\u70b9\u5728 lab7 \u7684\u6307\u5bfc\u91cc\u624d\u6709\u63d0\u793a\u5230\uff0c\u4e0d\u8fc7\u6211\u89c9\u5f97\u5e94\u8be5\u65e9\u70b9\u5b9e\u73b0\u8d77\u6765\u3002\u6bd4\u5982\uff1a

    void trap_handler(uint64 scause, uint64 sepc, struct pt_regs* regs) {  // a0, a1, a2\nuint64 stval = csr_read(stval);\n// printk(\"[S] Trap @sepc = %#llx, @scause = %#llx, @stval = %#llx\\n\", sepc, scause, stval);\nint done = 0;\n/* Interrupt */\nif ((scause >> 63) && (scause & 0x7FFFFFFFFFFFFFFF) == 5) {\nclock_set_next_event();\nprintk(\"[S] Supervisor Timer Intterupt\\n\");\ndo_timer();\n} /* Exception */\nelse {\n/* instrution addr misaligned */\nif (scause == 0) {}\n/* Instruction access fault */\nelse if (scause == 1) {}\n/* Illegal instruction */\nelse if (scause == 2) {}\n/* breakpoint */\nelse if (scause == 3) {}\n/* load addr misaligned */\nelse if (scause == 4) {}\n/* load access fault */\nelse if (scause == 5) {}\n/* store/amo addr misaligned */\nelse if (scause == 6) {}\n/* store/amo access fault */\nelse if (scause == 7) {}\n/* ecall U-mode */\nelse if (scause == 8) {\nif (sys_call_num == SYS_WRITE) {\n// ...\n} else if (sys_call_num == SYS_GETPID) {\n// ...\n} else if (sys_call_num == SYS_CLONE) {\n// ...\n}\nregs->sepc += 4; // pc + 4\n} /* ecall S-mode */\nelse if (scause == 9) {}\n/* Instruction page fault */\n/* Load page fault */\n/* Store/amo page fault */\nelse if (scause == 12 || scause == 13 || scause == 15) {\ndone = do_page_fault(scause, regs);\n} else {\nprintk(\"[S] Unhandled exception with scause = %d, sepc = %lx\\n\", scause, sepc);\nwhile (1);\n}\n}\n// if (!done) while(1);\n}\n
    \u603b\u4e4b\uff0c\u5efa\u8bae\u5bf9 trap_handler() \u505a\u7684\u6539\u8fdb\u6709\u4e24\u4ef6

    \u5982\u679c\u786e\u5b9e\u662f\u5faa\u73af trap \u5bfc\u81f4\u7684\u7a0b\u5e8f\u5361\u4f4f\uff0c\u90a3\u4e48\u6309\u6253\u5370\u7684\u4fe1\u606f\u53bb\u601d\u8003\u5c31\u53ef\u4ee5\u4e86\u3002\u5982\u679c\u8fd8\u662f\u4ec0\u4e48\u8f93\u51fa\u90fd\u6ca1\u6709\uff08\u6211\u8bb0\u5f97\u4e5f\u6709\u8fd9\u79cd\u60c5\u51b5\uff09\uff0c\u6211\u4e0d\u8bb0\u5f97\u662f\u4ec0\u4e48\u539f\u56e0\u4e86\uff0c\u4f46\u662f\u8d77\u7801\u5e2e\u4f60\u6392\u9664\u4e86\u53d1\u751f\u4e86 trap \u7684\u53ef\u80fd\u6027\uff0c\u4f60\u53ef\u4ee5\u5728\u6b64\u57fa\u7840\u4e0a\u7ee7\u7eed\u601d\u8003\u662f\u4e3a\u4ec0\u4e48\u3002

    "},{"location":"docs/2-ling/","title":"Linguistic Notes","text":"

    :material-circle-edit-outline: \u7ea6 62 \u4e2a\u5b57

    This section mainly consists of the notes of the linguistics courses from Zhejiang University.

    "},{"location":"docs/2-ling/#contents","title":"Contents","text":"

    It is commonly considered that the subject linguistics consists of 6 main branches.

    Besides, we also talk about other topics,

    "},{"location":"docs/2-ling/acqusition/","title":"Language Acqusition","text":"

    :material-circle-edit-outline: \u7ea6 40 \u4e2a\u5b57

    \u4e3b\u8981\u53ef\u80fd\u5199\u4e00\u4e9b\u8bed\u6cd5\uff0c\u8bcd\u6cd5\u548c\u53e5\u6cd5\u7b49\u3002

    \u5355\u8bcd\u8bb0\u5fc6\u548c\u4e60\u60ef\u7528\u8bed\u4e0d\u5728\u672c\u5e16\u7684\u8bb0\u5f55\u8303\u56f4\u4e4b\u5185\u3002

    "},{"location":"docs/2-ling/acqusition/#contents","title":"Contents","text":""},{"location":"docs/2-ling/acqusition/french-tense/","title":"French Tense summarization","text":"

    :material-circle-edit-outline: \u7ea6 1161 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/2-ling/acqusition/french-tense/#overview","title":"Overview\uff1a\u8bed\u6001\u548c\u65f6\u6001","text":"

    \u52a8\u8bcd\u7684\u53d8\u4f4d\u6709\u4e24\u79cd\u5c5e\u6027\uff1a\u8bed\u6001\u548c\u65f6\u6001\u3002\u8bed\u6001\u5bf9\u5e94\u4e00\u4e2a\u52a8\u4f5c\u7684\u7edd\u5bf9\u8fdb\u884c\u7a0b\u5ea6\u5c5e\u6027\uff0c\u800c\u65f6\u6001\u5bf9\u5e94\u52a8\u4f5c\u7684\u76f8\u5bf9\u53d1\u751f\u65f6\u95f4\u3002

    \u6211\u627e\u5230\u4e86\u4e00\u4e2a\u5173\u4e8e\u8bed\u6001\u6bd4\u8f83\u597d\u7684\u793a\u610f\u56fe\uff0c\u6a2a\u5411\u8868\u793a\u52a8\u8bcd\u7684\u5b8c\u6210\u7a0b\u5ea6\uff0c\u7eb5\u5411\u8868\u793a\u52a8\u8bcd\u672c\u8eab\u7684\u6301\u7eed\u65f6\u957f\uff0c\u4e8e\u662f\u4e0a\u3001\u4e0b\u3001\u5de6\u3001\u53f3\u53ef\u4ee5\u5927\u81f4\u5bf9\u5e94\u77ac\u6001\u52a8\u8bcd\u3001\u6301\u7eed\u52a8\u8bcd\u3001\u5c06\u8981\u53bb\u505a\u3001\u5df2\u7ecf\u5b8c\u6210\u3002 

              \u77ac\u6001\n           /\\\n          /  \\\n         /\u975e\u5e38\u6001\\\n         -------\n\u4e0d\u5b9a\u6001  /         \\  \u5b8c\u6210\u6001\n       ------------\n           \u5e38\u6001\n
    \u800c\u65f6\u6001\u8868\u793a\u52a8\u4f5c\u53d1\u751f\u7684\u65f6\u95f4\u987a\u5e8f\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u4e0a\u8ff0\u4e09\u89d2\u5957\u5165\u8fc7\u53bb\u3001\u73b0\u5728\u3001\u5c06\u6765\u8fd9\u4e09\u4e2a\u76f8\u5bf9\u65f6\u95f4\uff0c\u7ec4\u5408\u5f97\u5230\u5bf9\u5e94\u65f6\u6001\u4e0b\u7684\u591a\u4e2a\u8bed\u6001\u3002

    \u6cd5\u8bed\u7684 3 \u79cd\u65f6\u6001\u6709\uff1a

    \u540c\u65f6\u8fd8\u6709 6 \u79cd\u8bed\u6001\uff1a

    \u4e8e\u662f\u53ef\u4ee5\u7ec4\u5408\u4ea7\u751f\u591a\u4e2a\u65f6\u6001\u4e0b\u7684\u591a\u4e2a\u8bed\u6001\uff0c\u5b83\u4eec\u4e00\u822c\u5408\u79f0\u53eb\u65f6\u6001\uff0c\u6709\u70b9\u6b67\u4e49\uff0c\u4e0d\u8fc7\u5c31\u8fd9\u6837\u53eb\u597d\u4e86\u3002\u4e0b\u9762\u4e00\u4e00\u4ecb\u7ecd\u3002

    "},{"location":"docs/2-ling/acqusition/french-tense/#_1","title":"\u5177\u4f53\u65f6\u6001\u4ecb\u7ecd","text":"

    \u9996\u5148\u63d0\u4f9b\u4e00\u4e2a overview\u3002

    Fig 1. \u4ec5\u4e0e\u5ba2\u89c2\u73b0\u5b9e\u6709\u5173\u7684\u51e0\u4e2a\u65f6\u6001\u7684\u65f6\u95f4\u8f74

    \u76f4\u9648\u5f0f (l'indicatif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u76f4\u9648\u5f0f\u73b0\u5728\u65f6l'indicatif pr\u00e9sent \u53d1\u751f\u5728\u73b0\u5728\u7684\u52a8\u4f5c\u6216\u5b58\u5728\u7684\u72b6\u6001\u3002 \u52a8\u8bcd\u8bcd\u6839 - \u8bcd\u5c3e + \u4e0d\u540c\u4eba\u79f0\u4e3b\u8bed\u5bf9\u5e94\u7684\u8bcd\u5c3e j'aime,tu aimes,il/elle/on aime,nous aimons,vous aimez,ils/elle aiment je choisis,tu choisis,il/elle/on choisit,nous choisissons,vous choisissez,ils/elles choisissent je dors,tu dors,il/elle/on dort,nous dormons,vous dormez,ils/elles dorment \u76f4\u9648\u5f0f\u590d\u5408\u8fc7\u53bb\u65f6le pass\u00e9 compos\u00e9 \u8868\u793a\u4ece\u73b0\u5728\u89d2\u5ea6\u770b\u5df2\u7ecf\u53d1\u751f\u7684\u52a8\u4f5c\u3002\u8868\u8fbe\u7684\u662f\u201c\u67d0\u4e8b\u5df2\u7ecf\u5b8c\u6210\u201d\u7684\u6982\u5ff5\u3002 \u00eatre \u7684\u76f4\u9648\u5f0f\u73b0\u5728\u65f6 + \u52a8\u8bcd\u8fc7\u53bb\u5206\u8bcd\uff08\u5c11\u90e8\u5206\u8868\u793a\u8d8b\u5411\u6027\u3001\u4f4d\u7f6e\u6216\u72b6\u6001\u53d8\u5316\u7684\u4e0d\u53ca\u7269\u52a8\u8bcd\u3001\u6240\u6709\u4ee3\u8bcd\u5f0f\u52a8\u8bcd\uff0csee Fig 2\uff09 \u6216avoir \u7684\u76f4\u9648\u5f0f\u73b0\u5728\u65f6 + \u52a8\u8bcd\u8fc7\u53bb\u5206\u8bcd\uff08\u5176\u5b83\uff09 .. .. .. \u76f4\u9648\u5f0f\u672a\u5b8c\u6210\u8fc7\u53bb\u65f6l'imparfait \u8868\u793a\u8fc7\u53bb\u53d1\u751f\u7684\u52a8\u4f5c\uff0c\u53ea\u662f\u4e8b\u60c5\u7684\u5b8c\u6210\u72b6\u6001\u662f\u4e0d\u660e\u786e\u7684\uff0c \u76f4\u9648\u5f0f\u6108\u8fc7\u53bb\u65f6le plus-que parfait \u76f4\u9648\u5f0f\u7b80\u5355\u8fc7\u53bb\u65f6le pass\u00e9 simple \u76f4\u9648\u5f0f\u5148\u8fc7\u53bb\u65f6le pass\u00e9 ant\u00e9rieur \u76f4\u9648\u5f0f\u6700\u8fd1\u8fc7\u53bb\u65f6le pass\u00e9 proche \u76f4\u9648\u5f0f\u7b80\u5355\u5c06\u6765\u65f6le furture simple \u76f4\u9648\u5f0f\u5148\u5c06\u6765\u65f6le future ant\u00e9rieur \u76f4\u9648\u5f0f\u6700\u8fd1\u5c06\u6765\u65f6le future proche \u76f4\u9648\u5f0f\u8fc7\u53bb\u5c06\u6765\u65f6le futur dans le pass\u00e9

    Fig 2. le pass\u00e9 compos\u00e9 \u4e2d\u4f7f\u7528 \u00eatre \u52a9\u52a8\u8bcd\u7684\u52a8\u8bcd

    \u547d\u4ee4\u5f0f (l'imp\u00e9ratif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u6761\u4ef6\u5f0f (le conditionnel)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u865a\u62df\u5f0f (le subjonctif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u5206\u8bcd\u5f0f (le participe)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent"},{"location":"docs/2-ling/acqusition/french-tense/#references","title":"References","text":""},{"location":"docs/2-ling/morphology/","title":"Morphology","text":"

    :material-circle-edit-outline: \u7ea6 2 \u4e2a\u5b57

    "},{"location":"docs/2-ling/morphology/#outline","title":"outline","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/","title":"TODO","text":"

    :material-circle-edit-outline: \u7ea6 327 \u4e2a\u5b57 :fontawesome-solid-code: 2 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    Aug. 25th. 2023

    This talk aims both to provide an introduction to the subject Philosophy of Language (a similar subject with semantics and pragmatics, according to its definition; PoL hereafter), and give a summary on the recent ongoing discussion on the linguistics concepts in NLP (e.g. \"meaning\", \"understanding\", \"reasoning\", \"grounding\").

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#a-preview-of-this-talk","title":"A Preview of This Talk","text":"

    1st 40min: History of philosophy of language 2nd 40min: Recent papers and discussions on PoL topics in NLP 3rd 10min: Discussion on take-away

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#the-location-of-pol-on-the-academic-coordinate","title":"The Location of PoL on the Academic Coordinate","text":"

    Before we start this talk, we will first provide a brief definition of the term Philosophy of Language in our talk here. The PoL concerns mainly the two following questions, (i) The relationship between the natural language and the world, (ii) The relationship between the human languages and their meaning. Chen (2003) believes that the PoL and the linguistics are two different subjects. He suggests that the linguistics is the study of language rules and patterns and the application of them, while the PoL pays more attention on the more abstract and essential features of the human language (e.g. its relation to the cognition). The author of this talk believes, according to the definition of PoL, it is a subject that closely involves the semantics and pragmatics branches in linguistics. However the PoL and linguistics overlap or not, it is commonly believed that the subject PoL was born in the 1920s, when the linguistic turn was put on stage in the European philosophy.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#history-of-pol","title":"History of PoL","text":"

    Now we will dive into the history of PoL. This section is parted \"person by person\". It is noticed that \"person-by-person\" is a common structure of most of the philosophy history, as most of the philosophy progresses are propelled by giants instead of the common people.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#gottfried-wilhelm-leibniz","title":"Gottfried Wilhelm Leibniz","text":"

    The main contribution of Leibniz is

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#ferdinand-de-saussure","title":"Ferdinand de Saussure","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#friedrich-ludwig-gottlob-frege","title":"Friedrich Ludwig Gottlob Frege","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#bertrand-russell","title":"Bertrand Russell","text":"

    Bertrand Russell is a pure logician.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#ludwig-wittgenstein","title":"Ludwig Wittgenstein","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#noam-chomsky","title":"Noam Chomsky","text":""},{"location":"docs/2-ling/philosophy/pol_zh/","title":"Philosophy of Language \u8bed\u8a00\u54f2\u5b66","text":"

    :material-circle-edit-outline: \u7ea6 3102 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    Nov. 9th. 2022

    "},{"location":"docs/2-ling/philosophy/pol_zh/#talk","title":"\u8fd9\u6b21talk\u4f1a\u8bb2\u4ec0\u4e48","text":"

    \u2705\u00a0\u4ecb\u7ecd\u8bed\u8a00\u54f2\u5b66\u7684\u601d\u6f6e\u6d41\u53d8\u5386\u7a0b\uff0c\u4ecb\u7ecd\u8bed\u8a00\u4e0a\u7684\u5b9e\u9a8c\u601d\u60f3\u5b9e\u9a8c\uff0c\u8ba8\u8bba\u4e00\u4e9b\u8bed\u8a00\u5b66\u3001\u8ba4\u77e5\u3001\u903b\u8f91\u548c\u54f2\u5b66\u7684\u5173\u8054

    "},{"location":"docs/2-ling/philosophy/pol_zh/#pol","title":"PoL","text":"

    \u8bed\u8a00\u54f2\u5b66\u7684\u57fa\u672c\u95ee\u9898\uff1a 1. \u8bed\u8a00\u548c\u4e16\u754c\u7684\u5173\u7cfb 2. \u8bed\u8a00\u6216\u8bed\u8bcd\u7684\u610f\u4e49\u95ee\u9898

    \u8bed\u8a00\u54f2\u5b66\u548c\u8bed\u8a00\u5b66 \u8bed\u8a00\u5b66\u548c\u8bed\u8a00\u54f2\u5b66\u7684\u8054\u7cfb\u7d27\u5bc6\uff0c\u4f46\u662f\u662f\u4e24\u95e8\u5b66\u79d1\u3002

    20\u4e16\u7eaa\u54f2\u5b66\u4e0a\u53d1\u751f\u4e86\u8bed\u8a00\u8f6c\u5411\uff0c\u8fd9\u4e5f\u662f\u73b0\u4ee3\u8bed\u8a00\u5b66\u5f62\u6210\u7684\u65f6\u5019\u3002

    \u8bed\u8a00\u5b66\u662f\u5bf9\u8bed\u8a00\u89c4\u5f8b\u548c\u8fd9\u4e9b\u89c4\u5f8b\u7684\u5e94\u7528\u7684\u7814\u7a76\uff0c\u8bed\u8a00\u54f2\u5b66\u66f4\u5173\u5fc3\u8bed\u8a00\u66f4\u672c\u8d28\u66f4\u62bd\u8c61\u7684\u610f\u4e49\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#history-of-pol","title":"History of PoL","text":"

    \u83b1\u5e03\u5c3c\u8328\uff1a\u63d0\u51fa\u903b\u8f91\u8bed\u8a00\uff0c\u7b80\u5386\u4eba\u5de5\u8bed\u8a00\u7684\u52aa\u529b

    \u5f3a\u8c03\u81ea\u7136\u8bed\u8a00\u4f9d\u8d56\u4e8e\u77e5\u8bc6\uff0c\u56e0\u6b64\u5206\u6709\u77e5\u89c9\u7684\u6a21\u7cca\u3001\u6b67\u4e49\u7b49\u79cd\u79cd\u7f3a\u9677\u3002\u81ea\u7136\u8bed\u8a00\u4e0d\u662f\u63cf\u8ff0\u5ba2\u89c2\u4e8b\u7269\u7684\u6700\u4f73\u5de5\u5177\uff0c\u4e3a\u4e86\u63a2\u7a76\u771f\u7406\uff0c\u5fc5\u987b\u5efa\u7acb\u4e00\u4e2a\u7531\u666e\u904d\u7b26\u53f7\u7ec4\u6210\u7684\u66f4\u4e3a\u6e05\u695a\u7684\u7b26\u53f7\u4f53\u7cfb\u3002\u8fd9\u79cd\u52aa\u529b\u5728\u6570\u5b66\u65b9\u9762\u662f\u5353\u6709\u6210\u6548\u7684\uff0c\u6bd4\u5982\u5fae\u79ef\u5206\u7b26\u53f7\u3002

    \u7d22\u7eea\u5c14\uff1a \u7d22\u7eea\u5c14\u6700\u5927\u7684\u5f71\u54cd\u662f\u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u3002\u6211\u4eec\u4e00\u822c\u8ba4\u4e3a\u7d22\u7eea\u5c14\u662f\u4e00\u4f4d\u8bed\u8a00\u5b66\u5bb6\uff0c\u4f46\u662f\u4ed6\u5728\u8fd9\u672c\u4e66\u4e2d\u63d0\u51fa\u7684\u201c\u80fd\u6307\u201d\u4e0e\u201c\u6240\u6307\u201d\u7406\u8bba\uff0c\u662f\u54f2\u5b66\u91cc\u7684\u7b26\u53f7\u5b66\u7684\u5f00\u7aef\u3002

    \u8bed\u8a00\u662f\u7528\u58f0\u97f3\u8868\u8fbe\u601d\u60f3\u7684\u7b26\u53f7\u7cfb\u7edf\uff0c\u7b26\u53f7\u662f\u7528\u4ee5\u8868\u793a\u8005\u548c\u88ab\u8868\u793a\u8005\u7684\u7ed3\u5408\u3002

    \u6211\u4eec\u4f1a\u8bf4\uff0c\u58f0\u97f3\u672c\u8eab\u4e0d\u80fd\u65bd\u6307\uff0c\u53ea\u6709\u5904\u5728\u67d0\u79cd\u7279\u5b9a\u5173\u7cfb\u4e2d\uff08\u8bed\u8a00\u5b9a\u4e49\u4e86\u58f0\u97f3\u548c\u5b9e\u4f53\u4e4b\u95f4\u7684\u5173\u7cfb\uff09\uff0c\u58f0\u97f3\u624d\u6709\u4e86\u610f\u4e49\u3002

    \u4efb\u610f\u6027\u539f\u5219\u662f\uff0c\u5982\u6b64\u8fd9\u822c\u7684\u65bd\u6307\u548c\u5982\u6b64\u8fd9\u822c\u7684\u6240\u6307\u7ed3\u5408\u800c\u6210\u7684\u4e00\u4e2a\u7b26\u53f7\uff0c\u662f\u4efb\u610f\u7684\u3002eg. \u989c\u8272\u4e0e\u989c\u8272\u8bcd\u7684\u8054\u7ed3\u662f\u4efb\u610f\u7684\uff0c\u989c\u8272\u7684\u754c\u9650\u4e0e\u989c\u8272\u8bcd\u7684\u8054\u7ed3\u4e5f\u662f\u4efb\u610f\u7684\u3002

    \"\u7eff\"\u4e0d\u4ec5\u548c\u7eff\u989c\u8272\u76f8\u8fde\uff0c\u800c\u4e14\u548c\u201c\u84dd\u201d\u201c\u9752\u201d\u7b49\u8bed\u8bcd\u76f8\u8fde\u3002\n\u5982\u679c\u6ca1\u6709\u201c\u84dd\u201d\u201c\u9752\u201d\uff0c\u6211\u4eec\u5c31\u4e0d\u80fd\u77e5\u9053\u201c\u7eff\u201d\u6240\u754c\u5b9a\u7684\u989c\u8272\u8303\u56f4\u3002\n\n\u201c\u4e03\u8272\u5f69\u8679\u201d\n\u65e5\u8bed\u4e0d\u533a\u5206\u201c\u84dd\u201d\u548c\u201c\u7eff\u201d\uff0c\u53ea\u6709\u4e00\u4e2a\u5355\u8bcd\u201c\u9752\u201d\uff08aoi\uff09\uff0c\u65e5\u8bed\u6bcd\u8bed\u8005\u5728\u9274\u522b\u84dd\u8272\u548c\u7eff\u8272\u65f6\u53cd\u5e94\u65f6\u9ad8\u4e8e\u82f1\u8bed\u6bcd\u8bed\u8005\u3002\n\u4e00\u79cd\u5317\u6b27\u8bed\u8a00\u6709\u4e03\u79cd\u84dd\u8272\u7684\u540d\u79f0\u3002\n

    \u6211\u4eec\u4e60\u60ef\u628a\u8bed\u8bcd\u548c\u60c5\u5883\u7684\u8054\u7cfb\u79f0\u4f5c\u7eb5\u5750\u6807\u6216\u8bed\u5883\u5750\u6807\uff0c\u628a\u8bed\u8bcd\u4e4b\u95f4\u7684\u8054\u7cfb\u79f0\u4f5c\u6a2a\u5750\u6807\u548c\u903b\u8f91\u5750\u6807\u3002

    eg. \u5b8c\u5f62\u586b\u7a7a\u9898

    eg. \u6570\u636e\u5e93\u5173\u7cfb\u6a21\u578b\u7684\u5c5e\u6027\u3001\u5143\u7ec4

    \u975e\u5e38\u6709\u8da3\uff0c\u7d22\u7eea\u5c14\u5199\u8fd9\u672c\u8bed\u8a00\u5b66\u6559\u6750\u65f6\uff0c\u4e16\u754c\u4e0a\u5e76\u6ca1\u6709\u7b26\u53f7\u5b66\u8fd9\u4e2a\u5b66\u79d1\u3002\u5728\u4ed6\u63d0\u51fa\u201c\u80fd\u6307\u201d\u201d\u6240\u6307\u201c\u8fd9\u4e2a\u6982\u5ff5\u540e\uff0c\u7b26\u53f7\u5b66\u5728\u4ed6\u201d\u80fd\u6307\u201c\u5728\u201d\u6240\u6307\u201c\u7684\u94fe\u6761\u4e0a\u6ed1\u52a8\u8fd9\u4e00\u8bba\u65ad\u7684\u57fa\u7840\u4e0a\u8bde\u751f\uff0c\u5e76\u81f3\u4eca\u6210\u4e3a\u6cd5\u56fd\u54f2\u5b66\u7684\u4e00\u4e2a\u91cd\u8981\u95ee\u9898\u3002

    \u5f17\u96f7\u683c\uff1a

    \u5f17\u96f7\u683c\u662f\u516c\u8ba4\u7684\u5206\u6790\u54f2\u5b66\u3001\u8bed\u8a00\u54f2\u5b66\u548c\u73b0\u4ee3\u6570\u7406\u903b\u8f91\u7684\u5f00\u521b\u8005\u3002

    \u300a\u6982\u5ff5\u6587\u5b57\uff1a\u4e00\u79cd\u6a21\u4eff\u7b97\u672f\u8bed\u8a00\u6784\u9020\u7684\u7eaf\u601d\u7ef4\u7684\u5f62\u5f0f\u8bed\u8a00\u300b\u4e3b\u8981\u5de5\u4f5c\u662f\uff0c\u8bbe\u8ba1\u4e86\u4e00\u5957\u4eba\u5de5\u7b26\u53f7\u7cfb\u7edf\uff0c\u6392\u9664\u4e86\u81ea\u7136\u8bed\u8a00\u4e2d\u4fee\u8f9e\u4e4b\u7c7b\u7684\u4e1c\u897f\uff0c\u4e13\u6ce8\u4e8e\u6982\u5ff5\u672c\u8eab\u548c\u6982\u5ff5\u4e4b\u95f4\u7684\u8054\u7cfb\uff0c\u56e0\u6b64\uff0c\u5b83\u5c06\u6392\u9664\u81ea\u7136\u8bed\u8a00\u7684\u6a21\u7cca\u6027\u548c\u4e0d\u786e\u5b9a\u6027\u3002\u7528\u8fd9\u5957\u7b26\u53f7\u7cfb\u7edf\u6765\u91cd\u65b0\u8868\u8ff0\u7b97\u672f\u7684\u57fa\u672c\u6982\u5ff5\u548c\u63a8\u7406\u89c4\u5219\uff0c\u660e\u786e\u6240\u6709\u63a8\u7406\u7684\u524d\u63d0\uff0c\u4fdd\u8bc1\u4e00\u4e2a\u8bc1\u660e\u4e2d\u5404\u4e2a\u547d\u9898\u95f4\u7684\u6240\u6709\u63a8\u7406\u89c4\u5219\uff0c\u4f7f\u63a8\u7406\u4e0d\u518d\u57fa\u4e8e\u76f4\u89c9\uff0c\u4e5f\u6ca1\u6709\u8df3\u8dc3\u548c\u8131\u8282\u3002

    \u5bf9\u8bed\u8a00\u54f2\u5b66\u5f71\u54cd\u6700\u6df1\u7684\u662f\u4ed6\u5728\u300a\u7b97\u672f\u57fa\u7840\u300b\u4e2d\u63d0\u51fa\u7684\u4e09\u6761\u8457\u540d\u539f\u5219\uff1a

    1. \u59cb\u7ec8\u628a\u5fc3\u7406\u7684\u4e1c\u897f\u548c\u903b\u8f91\u7684\u4e1c\u897f\u3001\u4e3b\u89c2\u7684\u4e1c\u897f\u548c\u5ba2\u89c2\u7684\u4e1c\u897f\u4e25\u683c\u533a\u5206\u5f00\u3002\u8fd9\u4e00\u6761\u53cd\u5bf9\u5f53\u65f6\u751a\u4e3a\u6d41\u884c\u7684\u5fc3\u7406\u4e3b\u4e49\u3002\u5f17\u96f7\u683c\u4e3b\u5f20\u903b\u8f91\u5b66\u5bb6\u7814\u7a76\u7684\u662f\u8bed\u8a00\u8868\u8fbe\u5f0f\u3002\u8bed\u8a00\u8868\u8fbe\u5f0f\u662f\u53ef\u4ee5\u516c\u5f00\u8003\u5bdf\u7684\uff0c\u610f\u4e49\u7814\u7a76\u5e94\u5f53\u57fa\u4e8e\u8fd9\u4e9b\u8868\u8fbe\u5f0f\uff0c\u800c\u4e0d\u662f\u4f9d\u8d56\u4e8e\u5bf9\u5fc3\u7406\u8fc7\u7a0b\u7684\u81c6\u6d4b\u3002
    2. \u7edd\u4e0d\u5b64\u7acb\u5730\u5bfb\u95ee\u4e00\u4e2a\u8bcd\u7684\u610f\u4e49\uff0c\u800c\u53ea\u5728\u4e00\u4e2a\u547d\u9898\u7684\u4e0a\u4e0b\u6587\u4e2d\u5bfb\u95ee\u8bcd\u7684\u610f\u601d\u3002\u88ab\u79f0\u4e3a\u8bed\u5883\u539f\u5219\u548c\u4e0a\u4e0b\u6587\u539f\u5219\uff0c\u6307\u51fa\u8bed\u4e49\u7814\u7a76\u7684\u6700\u5c0f\u5355\u4f4d\u8d77\u7801\u662f\u53e5\u5b50\uff0c\u4e0d\u662f\u8bcd\uff0c\u4e0d\u662f\u8868\u5c42\u8bed\u6cd5\u3002\u6211\u4eec\u6ce8\u610f\u5230\u8fd9\u4e00\u6761\u4e0e\u7b2c\u4e00\u6761\u76f8\u5173\uff0c\u56e0\u4e3a\u5982\u679c\u7814\u7a76\u8bcd\uff0c\u8bcd\u4f9d\u8d56\u7684\u5fc5\u7136\u662f\u610f\u4e49\u5728\u5fc3\u7406\u8fc7\u7a0b\u4e2d\u7684\u6620\u5c04\uff0c\u800c\u7814\u7a76\u53e5\u5b50\uff0c\u6211\u4eec\u4f1a\u628a\u8bed\u8bcd\u5728\u53e5\u5b50\u4e2d\u7684\u8054\u7cfb\u5f53\u4f5c\u610f\u4e49\u3002
    3. \u7edd\u4e0d\u5fd8\u8bb0\u6982\u5ff5\u548c\u5bf9\u8c61\u7684\u533a\u522b\u3002

    \u4e24\u4e2a\u601d\u7ef4\u5b9e\u9a8c\uff1a

    1. \u6307\u79f0\u76f8\u540c\u800c\u610f\u4e49\u4e0d\u540c\u7684\u8bcd 

      \u201c\u542f\u660e\u661f\u201d\u548c\u201c\u957f\u5e9a\u661f\u201d\u662f\u540c\u4e00\u9897\u884c\u661f\u2014\u2014\u2014\u2014\u91d1\u661f\u3002\n\u4f46\u662f\u4e24\u4e2a\u540d\u8bcd\u7684\u610f\u4e49\u4e0d\u540c\uff0c\u5927\u591a\u6570\u65f6\u5019\u4e0d\u80fd\u66ff\u6362\u3002\n\u201c\u4ed6\u5929\u8fd8\u6ca1\u4eae\u5c31\u8d77\u8eab\uff0c\u8fce\u7740\u542f\u660e\u661f\u5411\u4e1c\u8d70\u53bb\u3002\u201d\n

    2. \u51fd\u5f0f\u7406\u8bba 

      \uff08 \uff09\u662f\u4e2d\u56fd\u7684\u9996\u90fd\n\uff08 \uff09= \"\u4f26\u6566\"\u3001\"\u5317\u4eac\"\n\u53ea\u6709\u586b\u5165\u5317\u4eac\u7684\u65f6\u5019\u624d\u662f\u771f\u547d\u9898\n

    \u7f57\u7d20\uff1a\u903b\u8f91

    \u6df1\u5165\u4e13\u540d\u548c\u901a\u540d\u3001\u6096\u8bba\u3001\u6392\u4e2d\u5f8b\u3002

    \u7ef4\u7279\u6839\u65af\u5766\uff1a

    \u524d\u671f\u601d\u60f3\u300a\u903b\u8f91\u54f2\u5b66\u8bba\u300b

    \u201c\u4e16\u754c\u662f\u4e8b\u5b9e\u7684\u7efc\u5408\u201d\uff1a\u201c\u53f8\u9a6c\u5149\u662f\u5510\u671d\u4eba\u201d\u7b26\u5408\u903b\u8f91\uff0c\u4f46\u4e0d\u7b26\u5408\u4e8b\u5b9e\u3002

    \u56fe\u50cf\u8bba

    \u8bed\u8a00\u662f\u547d\u9898\u7684\u603b\u548c\u800c\u4e0d\u662f\u540d\u79f0\u7684\u603b\u548c\u3002

    \u4eba\u5728\u4ea4\u6d41\u601d\u60f3/\u547d\u9898\u65f6\uff0c\u4ea4\u6d41\u7684\u662f\u8111\u4e2d\u7684\u56fe\u50cf\u3002

    \u4ed6\u7684\u524d\u671f\u601d\u60f3\u542f\u53d1\u4e86\u7ef4\u4e5f\u7eb3\u5b66\u6d3e\uff1a\u4eba\u5de5\u8bed\u8a00\uff0c\u903b\u8f91\u8bed\u8a00

    \u5341\u4e5d\u4e16\u7eaa\u672b\u4ee5\u6765\u4eba\u5de5\u8bed\u8a00\u7684\u5c1d\u8bd5\uff1a\u201c\u4e16\u754c\u8bed\uff08Esperanto\uff09\u201d\uff0c\u4e18\u5409\u5c14\u63a8\u5d07\u7684\u57fa\u672c\u82f1\u8bed\uff0c\u81ea\u7136\u8bed\u8a00\u4e2d\u5bf9\u201c\u5973\u4eba\u201d\u201c\u5973\u6027\u201d\u201c\u5973\u58eb\u201d\u201c\u5987\u5973\u201d\u8fd9\u6837\u7684\u6307\u79f0\u7684\u89c4\u8303\u5c1d\u8bd5\u3002

    \u540e\u671f\u601d\u60f3\u300a\u54f2\u5b66\u7814\u7a76\u300b

    \u8bed\u8a00\u6e38\u620f\uff08Sprachspiel\uff09

    \u8bed\u8a00\u7684\u529f\u80fd\u7684\u672c\u8d28\uff1a\u4e00\u65b9\u558a\u51fa\u8bed\u8bcd\uff0c\u53e6\u4e00\u65b9\u4f9d\u7167\u8fd9\u4e9b\u8bed\u8bcd\u6765\u884c\u52a8\u3002

    \u8001\u5e08\u6307\u7740\u77f3\u5934\u8bf4\u201c\u77f3\u5934\u201d\uff0c\u5b66\u751f\u8ddf\u7740\u8bf4\u201c\u77f3\u5934\u201d\u3002\n
    \u4e22\u624b\u7ee2\u65f6\u5531\u7740\u201c\u8f7b\u8f7b\u5730\u653e\u5728\u5c0f\u670b\u53cb\u7684\u8eab\u540e\u201d\uff0c\u628a\u624b\u7ee2\u653e\u5728\u5c0f\u670b\u53cb\u7684\u8eab\u540e\n

    \u4e0e\u524d\u671f\u56fe\u50cf\u7406\u8bba\u7684\u5bf9\u6bd4\uff1a\u5728\u56fe\u50cf\u7406\u8bba\u4e2d\uff0c\u8bed\u8a00\u4ece\u6839\u672c\u4e0a\u662f\u4e00\u79cd\u53cd\u6620\uff1b\u5728\u8bed\u8a00\u6e38\u620f\u8bf4\u4e2d\uff0c\u8bed\u8a00\u9996\u5148\u662f\u4e00\u79cd\u6d3b\u52a8\u3002

    \u610f\u4e49\u6765\u6e90\u4e8e\u4f7f\u7528\u3002

    \u6211\u4eec\u5173\u5fc3\u201c\u9524\u5b50\u201d\u662f\u4ec0\u4e48\u65f6\uff0c\n\u5173\u5fc3\u7684\u662f\u201c\u4f7f\u7528\u4e00\u628a\u9524\u5b50\u201d\uff0c\n\u800c\u4e0d\u662f\u201c\u9524\u5b50\u610f\u5473\u7740\u2026\u2026\u201d\n\u4e8b\u5b9e\u4e0a\uff0c\u6211\u4eec\u4e5f\u6b63\u662f\u4ece\u201c\u4f7f\u7528\u4e00\u628a\u9524\u5b50\u201d\u6765\u5b9a\u4e49\u9524\u5b50\n
    \u5982\u4f55\u533a\u5206\u201c\u4f7f\u7528\u201d\u201c\u6709\u7528\u201d\u201c\u5229\u7528\u201d\uff1f\n\u5728\u4e00\u4e9b\u60c5\u5883\u4e2d\u80fd\u7528\uff0c\u5728\u4e00\u4e9b\u60c5\u5883\u4e2d\u4e0d\u80fd\u7528\u3002\n

    \u8bed\u8a00\u6e38\u620f\u7684\u7c7b\u522b

    \u5bb6\u65cf\u76f8\u4f3c\u7406\u8bba\uff08Familien\u00e4hnlichkeiten\uff09

    \u201c\u4e00\u4e2a\u5bb6\u65cf\u7684\u6709\u4e9b\u6210\u5458\u6709\u4e00\u6837\u7684\u9f3b\u5b50\uff0c\u53e6\u4e00\u4e9b\u6709\u4e00\u6837\u7684\u7709\u6bdb\uff0c\u8fd8\u6709\u4e00\u4e9b\u6709\u4e00\u6837\u7684\u6b65\u6001\uff1b\u8fd9\u4e9b\u76f8\u4f3c\u4e4b\u5904\u4ea4\u53c9\u91cd\u53e0\u3002\u201c

    \u5185\u6db5\uff1a\u4e00\u4e2a\u6982\u5ff5\u7684\u5b9a\u4e49

    \u5916\u5ef6\uff1a\u4e00\u4e2a\u6982\u5ff5\u5305\u542b\u7684\u4e0b\u5c5e\u6982\u5ff5\u7684\u8303\u56f4

    \u901a\u540d\u7684\u4e0b\u5c5e\u8bcd\uff0c\u5404\u79cd\u4e13\u540d\u4e4b\u95f4\u5e76\u6ca1\u6709\u4e25\u683c\u7684\u754c\u9650\uff0c\u4e00\u4e2a\u76f8\u4f3c\u53e6\u4e00\u4e2a\uff0c\u5206\u4eab\u4e0d\u540c\u7684\u5171\u540c\u7279\u5f81\u3002

    \u751f\u6d3b\u5f62\u5f0f\uff08Lebens Form\uff09\uff1a\u5e38\u8bc6\u7684\u91cd\u8981\u6027

    \u201c\u626b\u5e1a\u5728\u90a3\u91cc\u201d\u5df2\u7ecf\u8db3\u591f\u6e05\u6670\u3002\n\u201c\u626b\u5e1a\u628a\u548c\u626b\u5e1a\u5934\u5728\u90a3\u91cc\u201d\uff0c\u867d\u7136\u5206\u6790\u5f97\u66f4\u6e05\u695a\uff0c\u4f46\u5728\u4ea4\u9645\u4e2d\u8ba9\u4eba\u8d39\u89e3\u3002\n

    \u4eff\u4f5b\u6211\u4eec\u53ea\u8981\u66f4\u591a\u8bf4\u4e00\u70b9\uff0c\u591a\u5206\u6790\u4e00\u70b9\uff0c\u4e8b\u60c5\u5c31\u4f1a\u66f4\u6e05\u695a\uff0c\u4eff\u4f5b\u6ca1\u6709\u4e00\u53e5\u8bdd\u672c\u8eab\u5c31\u662f\u8db3\u591f\u6e05\u695a\u7684\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#conclusion-of-agreements","title":"Conclusion of Agreements","text":"
    1. \u8bed\u8a00\u7684\u610f\u4e49\u4f9d\u8d56\u4e8e\u7b26\u53f7\u4e0e\u7b26\u53f7\u4e4b\u95f4\u76f8\u4e92\u5b9a\u4e49\uff0c\u4e0e\u771f\u5b9e\u4e16\u754c\u7684\u5bf9\u8c61\u6ca1\u6709\u7edd\u5bf9\u7684\u4e00\u4e00\u5bf9\u5e94\u5173\u7cfb\u3002
    2. \u8bed\u8a00\u7684\u529f\u80fd\u5728\u4e8e\u53d1\u51fa\u548c\u5b8c\u6210\u547d\u4ee4\u3002
    3. \u81ea\u7136\u8bed\u8a00\u771f\u5b9e\u73b0\u8c61\u6bd4\u4eba\u9020\u8bed\u8a00\u89c4\u5219/\u903b\u8f91\u8868\u8fbe\u5f0f\u66f4\u80fd\u53cd\u5e94\u4eba\u8111\u7684\u8ba4\u77e5\u3001\u66f4\u503c\u5f97\u7814\u7a76\u3002
    "},{"location":"docs/2-ling/philosophy/pol_zh/#history-of-nlp","title":"History of NLP","text":"
    1. \u57fa\u4e8e\u89c4\u5219\u7684 \u2192 \u7ef4\u7279\u6839\u65af\u5766\u524d\u671f\u53ca\u4ee5\u524d\u7684\u7eaf\u903b\u8f91\u8bed\u8a00\uff0c\u4eba\u9020\u8bed\u8a00\u3002
    2. \u57fa\u4e8e\u7edf\u8ba1\u7684\u548c\u6df1\u5ea6\u5b66\u4e60 \u2192 \u7ef4\u7279\u6839\u65af\u5766\u540e\u671f\u7684\u8bed\u8a00\u610f\u4e49\u5728\u4f7f\u7528\u4e2d\u3002
    3. \u548c\u7ed3\u5408\u8bed\u8a00\u5b66\u3001\u8ba4\u77e5\u77e5\u8bc6 \u2192 \u4e54\u59c6\u65af\u57fa\u7684\u8bed\u8a00\u7684\u610f\u4e49\u5728\u521b\u9020\u4e2d\u3002
    "},{"location":"docs/2-ling/philosophy/pol_zh/#pol_1","title":"PoL\u7684\u5176\u5b83\u95ee\u9898","text":"

    \u963f\u4f69\u5c14\u603b\u7ed3\u897f\u65b9\u54f2\u5b66\u7684\u53d1\u5c55\uff1a

    \u53e4\u4ee3\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u672c\u4f53\u8bba\uff0c\u4ece\u8fd1\u4ee3\u5f00\u59cb\uff0c\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u8ba4\u8bc6\u8bba\uff0c\u523020\u4e16\u7eaa\uff0c\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u8bed\u8a00\u3002

    \u672c\u4f53\u8bba\u7684\u95ee\u9898\uff1a\u4ec0\u4e48\u4e1c\u897f\u5b58\u5728\uff0c\u4ec0\u4e48\u662f\u5b9e\u5728\u7684\u57fa\u672c\u5b58\u5728\u5f62\u5f0f\u3002

    \u8ba4\u8bc6\u8bba\u7684\u95ee\u9898\uff1a\u54ea\u4e9b\u4e1c\u897f\u662f\u6211\u4eec\u80fd\u8ba4\u8bc6\u7684\uff0c\u6211\u4eec\u662f\u600e\u6837\u8ba4\u8bc6\u8fd9\u4e9b\u4e1c\u897f\u7684\u3002

    \u8bed\u8a00\u7684\u95ee\u9898\uff1a\u6211\u4eec\u5728\u4f55\u79cd\u610f\u4e49\u4e0a\u80fd\u591f\u8ba4\u8bc6\u5b58\u5728\u2014\u2014\u800c\u610f\u4e49\u7684\u9996\u8981\u8f7d\u4f53\u662f\u8bed\u8a00\u3002\u2192 Linguistic Turn

    PoL\u7684\u5176\u5b83topic\uff1a 1. \u6307\u79f0\u4e0e\u5b9e\u4f53\uff0c\u8bed\u8a00\u4e0e\u610f\u4e49\u7684\u5173\u7cfb 2. \u901a\u540d\u4e0e\u4e13\u540d\uff0c\u8bcd\u4e49\u7684\u8303\u56f4 3. \u771f\u7406\u7406\u8bba 4. \u300a\u6211\u4eec\u8d56\u4ee5\u751f\u5b58\u7684\u9690\u55bb\u300b\uff1a\u9690\u55bb\u65e0\u5904\u4e0d\u5728\uff0c\u4e0d\u4ec5\u5b9a\u4e49\u4e2d\u7684\u201cxx\u662fxx\u201d\u662f\u9690\u55bb\uff0c\u6709\u65f6\u5355\u4e2a\u8bcd\u5c31\u662f\u4e00\u4e2a\u9690\u55bb\u3002

    \u52a8\u8bcd\u662f\u9690\u55bb 

    \u65f6\u95f4\u5728\u6d41\u901d\u3002\n

    \u4ecb\u8bcd\u662f\u9690\u55bb 

    I\u2019m feeling up today.\nHe is down.\n\u9ad8\u5174\u4e3a\u4e0a\uff0c\u60b2\u4f24\u4e3a\u4e0b\u3002\nWake up.\nHe fell asleep.\n\u6709\u610f\u8bc6\u4e3a\u4e0a\uff0c\u65e0\u610f\u8bc6\u4e3a\u4e0b\u3002\nHe fell ill.\nShe dropped dead.\n\u5065\u5eb7\u548c\u751f\u547d\u4e3a\u4e0a\uff0c\u75be\u75c5\u548c\u6b7b\u4ea1\u4e3a\u4e0b\u3002\nI have controlled over her.\nHe fell from power.\n\u63a7\u5236\u6216\u5f3a\u8feb\u4e3a\u4e0a\uff0c\u88ab\u63a7\u5236\u6216\u88ab\u5f3a\u8feb\u4e3a\u4e0b\u3002\nMy income rose last year.\nThe number of errors is low.\n\u66f4\u591a\u4e3a\u4e0a\uff0c\u66f4\u5c11\u4e3a\u4e0b\u3002\n

    \u4e54\u59c6\u65af\u57fa\uff1a

    \u7ed3\u6784\u4e3b\u4e49\u8bed\u8a00\u5b66\u5230\u8f6c\u6362\u751f\u6210\u8bed\u6cd5\u3002

    1. \u8bed\u8a00\u80fd\u529b/\u8bed\u8a00\u8868\u73b0\uff1a\u8bed\u8a00\u80fd\u529b\u662f\u4eba\u5148\u5929\u5177\u6709\u7684\u72ec\u7acb\u80fd\u529b\uff0c\u5b83\u901a\u8fc7\u5b66\u4e60\u67d0\u79cd\u6216\u67d0\u4e9b\u7279\u5b9a\u8bed\u8a00\u5c55\u73b0\u51fa\u6765\u3002
    2. \u6df1\u5c42\u7ed3\u6784/\u8868\u5c42\u7ed3\u6784\uff1a\u6df1\u5c42\u7ed3\u6784\u901a\u8fc7\u8f6c\u6362\u89c4\u5219\u751f\u6210\u8868\u5c42\u7ed3\u6784\u3002

    \u8bed\u8a00\u5b66\u7684\u5de5\u4f5c\u4e0d\u5e94\u5f53\u662f\u641c\u96c6\u8bed\u8a00\u7d20\u6750\u52a0\u4ee5\u5f52\u7eb3\uff0c\u800c\u662f\u8981\u89e3\u91ca\u8bed\u8a00\u7684\u521b\u9020\u6027\u3002

    CNF 

    S -> AB\nA -> AA | a\nB -> b | e\n

    \u8f6c\u6362\u751f\u6210\u8bed\u6cd5\u89c4\u5219 \\(\\Sigma = \\{NP, Vp, T, N, Npsing, NPpl, Aux, V, C, M, En, S, Past, Af\\}\\) 

    S -> NP + VP\nVP -> Verb + NP\nNP -> Det + N\nVerb -> Aux + V\nDet -> the, a...\nN -> man, ball...\nAux -> will, can...\nV -> hit, see...\n

    \u4f20\u7edf\uff08\u6210\u5206\uff09\u8bed\u6cd5\u89c4\u5219 

    1. \u4e3b + \u8c13\n2. \u4e3b + \u8c13 + \u5bbe\n3. \u4e3b + \u7cfb + \u8868\n4. \u4e3b + \u8c13 + \u5bbe + \u53cc\u5bbe\n5. \u4e3b + \u8c13 + \u5bbe + \u5bbe\u8865\n6. \u4e3b + \u8c13 + \u5e76\u5217\u5bbe\n\n...\n

    \u300a\u53e5\u6cd5\u7ed3\u6784\u300b\uff081957\uff09\u6838\u5fc3\u53e5\u548c\u8f6c\u6362\u6982\u5ff5\u3002

    \u751f\u6210\u6b65\u9aa4 1. \u751f\u6210\u6838\u5fc3\u53e5\u3002 

    S -> X1 | X2 | ... Xn\n

    1. \u8f6c\u6362\u7ed3\u6784\uff08\u66ff\u6362\u3001\u7701\u7565\u3001\u6dfb\u52a0\u3001\u6362\u4f4d\uff09\u3002 

      X1 -> Y1Z1 | ...\n...\n

    2. \u6dfb\u52a0\u5f62\u6001\u97f3\u4f4d\u89c4\u5219\u3002 

      Z1 -> W1\n...\nZn -> Wn\n

    \u8f6c\u6362\uff1a\u6574\u4e2a\u8f6c\u6362\u751f\u6210\u8fc7\u7a0b\u53ef\u4ee5\u5206\u4e3a\u4e09\u4e2a\u6b65\u9aa4

    1. \u901a\u8fc7\u77ed\u8bed\u7ed3\u6784\u6539\u5199\u89c4\u5219\uff0c\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_c\\)\uff0c\\(R_c\\)\u7531\u975e\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u662f\u6df1\u5c42\u7ed3\u6784\u3002
    2. \u901a\u8fc7\u8bcd\u6c47\u63d2\u5165\u89c4\u5219\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_1\\)\uff0c\\(R_1\\)\u7531\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u4f46\u4ecd\u662f\u6df1\u5c42\u7ed3\u6784\u3002
    3. \u901a\u8fc7\u8f6c\u6362\u89c4\u5219\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_1\\)\uff0c\\(R_1\\)\u5f53\u7136\u8fd8\u662f\u7531\u975e\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u4f46\u5b83\u662f\u8868\u5c42\u7ed3\u6784\u3002

    \u6df1\u5c42\u7ed3\u6784\u548c\u8868\u5c42\u7ed3\u6784

    \u4e54\u59c6\u65af\u57fa\u8bed\u6cd5\u4f53\u7cfb\u4e2d\uff0c\u6307\u53e5\u5b50\u751f\u6210\u8fc7\u7a0b\u4e2d\u7279\u5b9a\u9636\u6bb5\u6240\u91c7\u7528\u7684\u4e00\u79cd\u7279\u6b8a\u64cd\u4f5c\u624b\u6bb5\u6216\u89c4\u5219\u3002\u6df1\u5c42\u7ed3\u6784\u662f\u5b83\u7684\u8f93\u5165\uff0c\u8868\u5c42\u7ed3\u6784\u662f\u5b83\u7684\u8f93\u51fa\u3002

    \u6709\u7684\u53e5\u5b50\u8868\u5c42\u7ed3\u6784\u4e0d\u540c\uff0c\u6df1\u5c42\u7ed3\u6784\u76f8\u4f3c\u3002\u901a\u8fc7\u8f6c\u6362\u64cd\u4f5c\u53ef\u4ee5\u76f8\u4e92\u8f6c\u5316\u3002

    \u6709\u7684\u53e5\u5b50\u6df1\u5c42\u7ed3\u6784\u4e0d\u540c\uff0c\u8868\u5c42\u7ed3\u6784\u76f8\u4f3c\u3002\u901a\u8fc7\u8f6c\u6362\u64cd\u4f5c\u4e0d\u80fd\u76f8\u4e92\u8f6c\u5316\u3002

    \u4e3a\u4ec0\u4e48\u4eca\u5929\u6211\u4eec\u8981\u8c08\u8bed\u8a00\u54f2\u5b66\uff1f

    \u9648\u5609\u6620\u8001\u5e08\uff1a\u79d1\u5b66\u662f\u4e00\u4e2a\u4e25\u5bc6\u7684\u6574\u6d01\u7684\u4f53\u7cfb\uff0c\u539f\u56e0\u662f\u5b83\u628a\u6240\u6709\u6df7\u6c8c\u7684\u65e0\u6cd5\u89e3\u51b3\u7684\u95ee\u9898\u629b\u5728\u4e86\u8fd9\u4e2a\u4f53\u7cfb\u4e4b\u5916\u3002[\u300a\u8d70\u51fa\u552f\u4e00\u771f\u7406\u89c2\u300b\uff0c2020]

    \u6240\u4ee5\u54f2\u5b66\u7684\u95ee\u9898\u662f\u7814\u7a76\u88ab\u79d1\u5b66\u6254\u51fa\u53bb\u7684\u6df7\u6c8c\u3002

    \u8bed\u8a00\u54f2\u5b66\u5c31\u50cf\u201c\u5165\u4fb5\u7684\u5b9e\u5728\u754c\u201d\uff0c\u201c\u8fb9\u754c\u7684\u6d4b\u8bd5\u70b9\u201d\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#recommended-reading","title":"Recommended Reading","text":"

    \u300a\u8bed\u8a00\u54f2\u5b66\u300b\u9648\u5609\u6620

    \u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u7d22\u7eea\u5c14

    \u300a\u903b\u8f91\u54f2\u5b66\u8bba\u300b\u7ef4\u7279\u6839\u65af\u5766

    \u300a\u54f2\u5b66\u7814\u7a76\u300b\u7ef4\u7279\u6839\u65af\u5766

    \u300a\u6211\u4eec\u8d56\u4ee5\u751f\u5b58\u7684\u9690\u55bb\u300b\u4e54\u6cbb\u00b7\u83b1\u8003\u592b

    \u300a\u5fc3\u667a\u3001\u8bed\u8a00\u548c\u673a\u5668\u300b\u5f90\u82f1\u747e

    "},{"location":"docs/2-ling/philosophy/pol_zh/#_1","title":"\u8ba8\u8bba","text":"

    \u662f\u5426\u6240\u6709\u6ca1\u6709\u7528\u8bed\u8a00\u8868\u8fbe\u7684\u77e5\u8bc6\uff0c\u90fd\u53ef\u4ee5\u88ab\u7528\u8bed\u8a00\u8868\u8fbe\uff1f\uff08not NP or NP-hard\uff09

    \u53ea\u5b66\u4e60\u8bed\u8a00\u662f\u5426\u80fd\u6a21\u62df\u4eba\u7684\u667a\u80fd\u6c34\u5e73\uff1f

    \u6a21\u578b\u662f\u5426\u9700\u8981\u5e94\u5bf9\u6240\u6709\u7684\u5f02\u5e38\u60c5\u51b5/\u673a\u5668\u8bed\u8a00\u7684\u76ee\u6807\u672c\u8eab\u8981\u4e0e\u4eba\u7c7b\u8bed\u8a00\u6709\u6240\u533a\u522b

    "},{"location":"docs/2-ling/philosophy/saussure/","title":"Reading Notes of Cours de linguistique g\u00e9n\u00e9rale, Ferdinand de Saussure","text":"

    :material-circle-edit-outline: \u7ea6 685 \u4e2a\u5b57 :fontawesome-solid-code: 5 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    \u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u7d22\u7eea\u5c14 \u8bfb\u4e66\u7b14\u8bb0

    \u7b2c\u96f6\u7f16\uff1a\u7eea\u8bba

    \u7b2c\u4e09\u7ae0\uff1a\u8bed\u8a00\u5b66\u7684\u5bf9\u8c61

    \u8bed\u97f3\u4e0e\u8bed\u4e49\u7684\u8054\u7cfb 

        _______________________\n   |                       |\n   |                       \u2228\nc <-> i                 i <-> i \n  \u542c\u97f3                    \u53d1\u97f3\n   \u2227                       |\n   |_______________________|\n
    c\uff1a\u6982\u5ff5

    i\uff1a\u97f3\u54cd\u5f62\u8c61

    \u8bed\u8a00\u7814\u7a76\u7684\u5bf9\u8c61

    \u7b2c\u516d\u7ae0\uff1a\u6587\u5b57\u8868\u73b0\u8bed\u8a00

    \u8bed\u97f3\u7684\u53d1\u5c55\u662f\u5386\u53f2\u6027\u7684\u3002

    \u7b2c\u4e03\u7ae0\uff1a\u97f3\u4f4d\u5b66 phonetics

    \u7b2c\u4e00\u7f16\uff1a\u4e00\u822c\u539f\u5219

    \u7b2c\u4e00\u7ae0\uff1a\u8bed\u8a00\u7b26\u53f7\u7684\u6027\u8d28

    \u7b26\u53f7\u7684\u7ed3\u6784\uff1a\n     ________________   \u4e0a\n    |   \u6982\u5ff5 -> \u6240\u6307  |\n    -----------------\n    | \u97f3\u54cd\u5f62\u8c61 -> \u80fd\u6307 |   \n    |________________|  \u4e0b\n

    \u80fd\u6307\u7684\u5c5e\u6027

    \u7b26\u53f7\u5728\u65f6\u95f4\u4e0a\u7684\u8fde\u7eed\u6027\u548c\u65f6\u95f4\u4e0a\u7684\u53d8\u5316\u76f8\u8fde\uff0c\u7b26\u53f7\u7684\u4efb\u610f\u6027\u4f7f\u5176\u65e0\u6cd5\u62b5\u5fa1\u4f7f\u80fd\u6307\u5728\u6240\u6307\u4e0a\u6ed1\u52a8\u7684\u56e0\u7d20\u3002

    \u4e00\u5207\u79d1\u5b66 

            C\n        |\n        |\nA ------------- B  \u540c\u65f6\u8f74\u7ebf\n        |\n        |\n        D\n      \u8fde\u7eed\u8f74\u7ebf\n

    \u8bed\u8a00\u5b66 

            C\n        |\n        |\nA ------------- B  \u9759\u6001\u8bed\u8a00\u5b66\uff08\u5171\u65f6\uff09\n        |\n        |\n        D\n    \u6f14\u5316\u8bed\u8a00\u5b66\uff08\u5386\u65f6\uff09\n

    \u5185\u5728\u4e8c\u91cd\u6027\u4f8b\u8bc1

            -> \u5171\u65f6\n       \u00b7<--------->\u00b7  \u7532\u65f6\u671f\n  |    |           |\n  \u2228    \u2228           \u2228\n \u5386\u65f6   \u00b7<--------->\u00b7  \u4e59\u65f6\u671f\n

    \u53ef\u4ee5\u6bd4\u4f5c\u4e0b\u68cb\uff1a\u8861\u5b9a\u7684\u89c4\u5219\u548c\u53d8\u52a8\u7684\u5c40\u52bf

    \u7b2c\u4e8c\u7f16\uff1a\u5171\u65f6\u8bed\u8a00\u5b66

    \u540c\u4e00\u6027\uff1a\u5171\u65f6 - \u97f3\u6bb5 -> \u610f\u4e49

    \u666e\u904d\u4ef7\u503c\uff1a

    \u8bed\u8a00\u4e4b\u4e2d\u53ea\u6709\u5dee\u522b -\u2014\u2014 \u6ca1\u6709\u79ef\u6781\u8981\u7d20\u7684\u5dee\u522b\u3002\u8bed\u8a00\u662f\u5f62\u5f0f\u800c\u4e0d\u662f\u5b9e\u8d28\u3002

    \u7b2c\u4e94\u7ae0

    \u7b2c\u516d\u7ae0\uff1a\u8bed\u8a00\u7684\u673a\u6784

    \u53e5\u6bb5\u7684\u8fde\u5e26\u5173\u7cfb\uff1a\u6574\u4f53\u7684\u4ef7\u503c\u53d6\u51b3\u4e8e\u5b83\u7684\u90e8\u5206\uff0c\u90e8\u5206\u7684\u4ef7\u503c\u51b3\u5b9a\u4e86\u5b83\u4eec\u5728\u6574\u4f53\u4e2d\u7684\u5730\u4f4d\u3002

           ----------\n        d\u00e9-faire\n       ----------\n         /    \\\n    d\u00e9coller  faire\n       /         \\\n    d\u00e9lancer    refaire\n     /             \\\n d\u00e9cendre        contrefaire\n

    \u6b63\u662f\u8fd9\u4e9b\u4e0d\u540c\u7684\u5f62\u5f0f\u6f02\u6d6e\u5728\u5468\u56f4\uff0c\u8fd9\u4e24\u4e2a\u8bcd\u624d\u80fd\u5206\u89e3\u6210\u5355\u4f4d\uff0c\u6216\u6210\u4e3a\u53e5\u6bb5\u3002

    \u53ea\u6709\u4e00\u90e8\u5206\u7b26\u53f7\u662f\u7edd\u5bf9\u4efb\u610f\u7684\uff0c\u4efb\u610f\u6027\u4e0d\u80fd\u53d6\u6d88\uff0c\u90fd\u6709\u7a0b\u5ea6\u5dee\u522b\uff0c\u7b26\u53f7\u53ef\u80fd\u662f\u76f8\u5bf9\u5730\u53ef\u4ee5\u8bba\u8bc1\u7684\u3002

    \u6574\u4f53 > \u90e8\u5206\u4e4b\u548c\u3002poirexier > poiretier

                     ------\n               /        \\\n    \u8bcd\u6c47     -             -   \u8bed\u6cd5\n\u4e0d\u80fd\u8bba\u8bc1\u7684\u6781\u7aef   \\        /    \u53ef\u4ee5\u8bba\u8bc1\u7684\u6781\u7aef\n    \u7b26\u53f7         -------       \u7ed3\u6784\n

    \u7b2c\u4e03\u7ae0\uff1a\u8bed\u6cd5\u548c\u533a\u5206

    \u62bd\u8c61\u5b9e\u4f53\uff0c\u6700\u540e\u5206\u6790\u8d77\u6765\uff0c\u603b\u662f\u4ee5\u5177\u4f53\u5b9e\u73b0\u4e3a\u57fa\u7840\u7684\u3002

    \u7b2c\u4e09\u7f16\uff1a\u5386\u65f6\u8bed\u8a00\u5b66

    \u7b2c\u4e09\u7ae0\uff1a\u8bed\u97f3\u6f14\u5316\u5728\u8bed\u6cd5\u4e0a\u7684\u540e\u679c

    \u7b2c\u56db\u7ae0\uff1a\u7c7b\u6bd4

    \u7b2c\u4e94\u7ae0\uff1a\u7c7b\u6bd4 -> \u6f14\u5316

    viendre, monru, traisait

    \u7b2c\u516d\u7ae0\uff1a\u6d41\u4fd7\u8bcd\u6e90

    "},{"location":"docs/2-ling/pragmatics/ca_da/","title":"Research Methods: Conversation Analysis and Discourse Analysis","text":"

    :material-circle-edit-outline: \u7ea6 275 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/ca_da/#discourse-analysis","title":"Discourse Analysis","text":"

    Some discourse analysis are taught in linguistic departments (Johnstone, 2018)

    Foucault (1972, 1980) use 'discourse' to refer to the ways of talking and thinking constitute ideologies (set of interrelated ideas) and serve to circulate power in society, and in the sense involved patterns of belief and habitual actions as well as patterns of language.

    Johnstone, Barbara. 2018. Discourse Analysis (3rd ed.). UK: Wiley-Blackwell.

    "},{"location":"docs/2-ling/pragmatics/ca_da/#conversational-analysis","title":"Conversational Analysis","text":"

    Definition

    Conversation analysis is the study of interactional activities. The object being studied involves at least two persons.

    Unit

    conversation > sequence > adjacency pair > turn

    types of adjacency pairs

    turn-taking feature

    One involved in a conversation is supposed to give floor to the other party (parties) at a proper point of time. to keep the balance between the time one spends talking and the time the others spend talking.

    pre-sequence

    insertion sequence

    A: Are you coming tonight?\nB: Can I bring a guest?\nA: Male or female?\nB: What difference does that make?\nA: An issue of balance.\nB: Female.\nA: Sure.\nB: Yeah, I\u2019ll be there.\n

    preference organization

    first part second part preferred dispreferred assessment agree disagree invitation accept refuse offer accept decline proposal agree disagree request acccept refuse"},{"location":"docs/2-ling/pragmatics/intro/","title":"Introduction and Concepts","text":"

    :material-circle-edit-outline: \u7ea6 1923 \u4e2a\u5b57 :fontawesome-solid-code: 11 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/intro/#what-is-pragmatics","title":"What is Pragmatics","text":""},{"location":"docs/2-ling/pragmatics/intro/#how-pragmatics-differ-from-other-linguistics-branches","title":"How pragmatics differ from other linguistics branches?","text":"

    Charles W. Morris (1901-1979) American semiotician and philosopher. supervised by Charles S. Pierce. In his Foundations of the Theory of Signs (1938), Morris proposed that semiotics should have three divisions:

    syntax  -------------> semantics -------------> pragmatics\n              \u2b06\ufe0f\u00a0                        \u2b06\ufe0f\u00a0           \n                        decoding              use in context\n

    During the course of everyday communication, human beings as social animals convey more than the literal, propositional meaning (i.e. we don\u2019t always mean what we say literally).

    There is more to the literal meaning of a sentence when we consider the sentence in relation to the context, i.e., the situation of uttering the sentence.

    Sentence that cannot be considered in isolation \u2192 utterance

    Pragmatics looks beyond truth-conditional meanings, and explores non-literal, implicit, context-related meanings.

    Thus both semantics and pragmatics deal with meaning, yet there is a division of labour: semantics deals with meaning in context.

    "},{"location":"docs/2-ling/pragmatics/intro/#levels","title":"Levels","text":""},{"location":"docs/2-ling/pragmatics/intro/#context-deixis-and-reference","title":"Context, Deixis and Reference \u8bed\u5883\uff0c\u6307\u793a\u4e0e\u6307\u79f0","text":""},{"location":"docs/2-ling/pragmatics/intro/#deixis","title":"Deixis","text":"

    Definition

    Deixis and context: Deictic does not have concrete meanings. Deictic words depend on context for meaning.

    Types of deixis

    defined in relation to the deictic center (person, time, place, discourse, social)

    The deictic cycle. Harman, 1990.

    "},{"location":"docs/2-ling/pragmatics/intro/#reference","title":"Reference","text":"

    Definition: The act of using a word/phrase to pick out something in the world.

    Types of referring expressions (\u6307\u793a\u8bed)

    Choice of referring expressions: based on the speaker\u2019s assumption about what the listener knows.

    Conditions for successful reference: must be collaborative

    "},{"location":"docs/2-ling/pragmatics/intro/#presupposition","title":"Presupposition","text":"

    Differences between semantic and pragmatic presuppositions

    for pragmatic presupposition

    cancellation of presuppositions

    Presuppositions are cancellable or defeasible by changing the words to alter the previous proposition.

    F: \u6709\u4e9b\u4eba\u517b\u732b\u4e86\n~F: \u6709\u4e9b\u4eba\u6ca1\u517b\u732b\n

    projection problem

    presupposition may not survive when simple sentences are projected into complex ones.

    Mary didnt manage to find a job.\nMary didnt manage to find a job. In fact, she didnt even try.\n
    Mike didnt date Mary again.\nMike didnt date Mary gain, if indeed he ever did.\n

    presupposition triggers (\u89e6\u53d1\u8bed): how to determine speakers\u2019 presupposition in the course of verbal communication?

    "},{"location":"docs/2-ling/pragmatics/intro/#conversational-implicature","title":"Conversational Implicature","text":"

    Implicature

    Grice\u2019s theory of conversational implicature, Logic and Conversation.

    An outline of a systematic theory of language use, which can account for the way people read between the lines when understanding everyday language.

    meaning of a sentence

    Grice\u2019s new terms

    Grice draws a distinction

    - Smith doesn't seem to have a girlfriend these days.\n\n- He has been paying a lot of visits to New York lately.\n\n=> entailment: he visits New York recently\n=> implicature: Smith may be having a girlfriend in New York.\n

    features

    Grice\u2019s cooperative principle

    common purpose/common direction: Conversational partners normally recognize a common purpose or a common direction in their conversation.

    common objectives (~= joint project): At any point of a conversation, certain \u201cconversational moves\u201d are judged suitable or unsuitable for accomplishing their common objectives.

    How the cooperative principle is applied:

    How to follow the maxims:

    How to break the maxims:

    The cooperative maxims are guidelines instead of rules. They can be creatively infringed/violated.

    The Horn scales & scalar implicature

    When any form on a scale (most, some, always, often, must, may\u2026) is used or asserted, the negative of all forms higher on the scale is implicated.

    types of implicature

    graph TD\nimplicatures --> conventional/lexical\nimplicatures --> conversational\nconversational --> generalized\nconversational --> particularized\n
    "},{"location":"docs/2-ling/pragmatics/intro/#lexical-pragmatics","title":"Lexical Pragmatics","text":"

    Criticism of relevance theory

    To calculate the processing cost,

    Lexical pragmatics

    pragmatic enrichment

    graph TD\n\npragmatic_enrichment --> pragmatic_narrowing\npragmatic_enrichment --> pragmatic_broadening\npragmatic_broadening --> approximation\npragmatic_broadening --> metaphorical_extension\n
    "},{"location":"docs/2-ling/pragmatics/socio/","title":"Sociopragmatics","text":"

    :material-circle-edit-outline: \u7ea6 129 \u4e2a\u5b57

    \u8fd9\u5757\u5185\u5bb9\u4f3c\u4e4e\u6ca1\u6709\u8bb2\u5f88\u591a\u4e1c\u897f. \u7c98\u4e00\u70b9ppt\u539f\u8bdd

    Intercultural Pragmatics

    Intercultural Pragmatics has the potential to help establish a \u201charmonious\u201d interaction and relationship between people from different cultures.

    IP aims to study how to deal with the differences arising from cross-cultural communication and how they may affect the universality of pragmatic principles (theory of speech acts, co-

    operative principle, politeness principle, etc.)

    intercultural pragmatics\u2019 two way perspective

    sociopragmatics

    "},{"location":"docs/2-ling/pragmatics/theories/","title":"Theories and Hypothesis","text":"

    :material-circle-edit-outline: \u7ea6 810 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/theories/#speech-act-theory","title":"Speech Act Theory \u8a00\u8bed\u884c\u4e3a\u7406\u8bba","text":"

    Speech action definition:

    Speech act theory:

    A speech act = locutionary act + illocutionary act + perlocutionary act

    Illocutionary force \u8bed\u529b: communicative purposes or social functions

    Classification of speech act

    Funtion-based classification system:

    by John Searle, UCB philosopher

    Structure-based classification system:

    "},{"location":"docs/2-ling/pragmatics/theories/#politeness-theory","title":"Politeness Theory","text":"

    Development of Gricean theory

    Definition of politeness theory

    Conversationalists work together, each trying to maintain his/her own face and the face of his/her counterpart.

    type of face

    Acts involved

    Leech\u2019s six Politeness Principle: extension of Gricean theory

    (Note that the term \u2018neo-Gricean\u2019 is most often used to describe the works of Laurence Horn, Stephen Levinson, etc. not other theories e.g. relevance theory)

    "},{"location":"docs/2-ling/pragmatics/theories/#relevance-theory","title":"Relevance Theory","text":"

    Only preserving the maxim of relation in Gricean theory

    Definition of relevance theory

    its investigates how aspects of meaning are generated in context and in relation to the speakers intentions.

    R(relevance) = E(#contextual effects)/C(cost of efforts in obtaining E)

    Relevance is higher when cognitive effects are higher, but it is lower when more processing efforts is required.

    Two aspects of relevance principle

    Application of RT

    "},{"location":"docs/2-ling/semantics/","title":"Index","text":""},{"location":"docs/2-ling/semantics/#contents","title":"Contents","text":"

    1 - Definition Clearification

    This chapter provides a brief introduction to the terminologies involved in semantics.\n

    2 - Logics & Formal Semantics

    This chapter first introduces the semiotics in formal semantics (which adopts a similar system with that in the logics). It then discusses about the semantics in two perspectives: the propositional logic and the predicate logic. It also introduces several basic rules in logic inference.\n

    3 - Scope Ambiguity

    This chapter discusses on the unsolved questions in scope ambiguity.\n
    "},{"location":"docs/2-ling/semantics/#grading","title":"Grading","text":"

    mid-term: 35%

    final: 50%

    participation: 15%

    "},{"location":"docs/2-ling/semantics/#two-tests","title":"Two tests","text":"

    Two tests will be given during the term, one in the middle and one at the end of the term, covering all the material covered up to that point in the course. The tests will be a combination of various types of questions, including true/false and short essay.

    "},{"location":"docs/2-ling/semantics/#final-review-for-fun","title":"Final Review & For Fun","text":"

    :material-circle-edit-outline: \u7ea6 629 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    The following parts are written in preparation for the final review but I upload it as well for you to read for fun.

    "},{"location":"docs/2-ling/semantics/#noble-semanticians","title":"Noble Semanticians","text":"Name Field Contribution Live Nation Institution Fun facts Noam Chomsky mainly in syntax generative grammar, transformational grammar, government and binding theory, minimalist program, productivity of language, recursivity of language 1928- USA MIT Most prominent linguist alive Ferdinand de Saussure linguist and semiotician founder of semiotics. concepts: sign, signifier vs. signified, diachronic vs. synchronic, language vs. parole, paradigmatic vs. syntagmatic 1857-1913 Switzerland University of Geneva, Switzerland Charles Sanders Peirce philosopher, mathematician, logician founder of semiotics. concepts: index, icon, symbol. 1839-1914 Milford Pennsylvania JHU Michel Br\u00e9al comparative grammar coined the term \u201csemantics\u201d, diachronic focus 1832-1915 born in Rheinlan (Germany), studied in Paris and Berlin in Paris Leonard Bloomfield structural linguistics structural linguistics, language as a self-regulating system, behaviorism(stimulus-response testing) 1887-1949 Yale University reject introspection Aristotle polymath term logic, initiator of western scientific tradition 384-322 BC Stagira, Greece tutor of Alexander the Great Gottlob Freg philosopher, logician, mathematician predicate logic, sense(sentence\u2019s proposition) vs. reference (its truth value) 1848-1925 German University of Jena extreme right-wing views Peter Geach philosopher, professor of logic donkey sentence (1962) 1916-2013 England Oxford Richard Montegue semanticist Montegue grammar: syntax and semantics go together 1930-1971 student of Alfred Tarski, gay man, killed in his apartment, four influential papers Gareth Evans philosopher philosophy of mind, work on reference, e-type anaphora 1946-1980 England Oxford Irene Heim semanticist definite and indefinite pronouns 1954- German, Munich MIT, phd 1982 advisor: Barbara Partee Hans Kamp philosopher and linguist discourse representation theory (DRT) 1954- Dutch Bertrand Russell philosopher, logician logic, philosophy of mathematician 1872-1970 Wales, Britain Cambridge Henri\u00ebtte de Swart linguist tense and aspect, negation, bare nominals and indefinite noun phrases. She has also investigated the role of semantics in language evolution, and was involved in the development of bidirectional optimality theory. 1961- Dutch director of Netherlands Graduate School of Linguistics and Utrecht Institute of Linguistics"},{"location":"docs/2-ling/semantics/#example-questions","title":"Example questions","text":"

    What is a donkey pronoun?

    A donkey sentence is such that an expected existential is interpreted as universal taking wide scope.\n

    What is a discourse pronoun:

    outside the scope of existing quantifier\ne.g. No student studies semantics. He is outside.\n

    The scope of a quantifier is always bound in the clause it appears.

     True\n

    What is quantifier raising?

    Chmosky and May.\nLF, \n

    What are De Morgan\u2019s laws?

    ~(p or q) <=> (~p) and (~q)\n~(p and q) <=> (~p) or (~q)\n

    What are conditional laws

    p -> q <=> ~p or q\n

    When is the indefinite \u201ca\u201d not an existential quantifier?

    1. donkey sentence\n2. generic noun phrase. A woman is difficult to please. \\forall x(Wx -> Dx)\n3. John is a plumber.pj\n

    2 readings: Some boy smiled at Jane and some boy kissed Molly.

    \\exist x(Bx and Sx,j and Kx,m)\n\\exist x(Bx and Sx,j) and \\forall y(By and Ky,m)\n

    2 Types of Recursion

    embedding and coordination\n
    "},{"location":"docs/2-ling/semantics/ambiguity/","title":"Ambiguity","text":""},{"location":"docs/2-ling/semantics/ambiguity/#scope-ambiguity","title":"Scope Ambiguity","text":""},{"location":"docs/2-ling/semantics/ambiguity/#scope-and-anaphora","title":"Scope and Anaphora","text":"

    antecedent vs. postcedent

    anaphor vs. cataphor

    Predicate logic is suited to capture natural language meaning

    allow recursion = recursivity

    two sources of recursion

    some boy kissed every girl.\n\nEvery girl was kissed by some boy.\n
    Someone mentioned tehy called everyone.\n\n\\forall x: Px\\forall y(M(x, Cxy))\n

    linear order: negative polarity item

    graph TD\n  DS -.Transformation.-> SS\n    SS -.send off.-> PF\n    SS -.send off.-> LF\n    PF -.acoustic representation.-> SS\n    LF -.semantic interpretation.-> SS\n

    Transformation:

    CALLOUT: annotation, connotation and denotation

    "},{"location":"docs/2-ling/semantics/ambiguity/#solution-for-scope-ambiguity","title":"Solution for scope ambiguity","text":"

    Quantifier-raising - NC RM - syntactic structure comes before the semantic structure - The movement we make in SS to remove ambiguity in DS is called quantifier-raising. - take the quantifier to the higher position to show the scope

    Quantifier-in - Montague grammar - The derivational illustration is called quantifier-in. - each predicate take an argument once a time

    Quantifier storage - Cooper storage - semantic ambiguity not represented in syntactic structure - semantic representation in which scope ambiguities are obtained without special syntactic rules

    "},{"location":"docs/2-ling/semantics/ambiguity/#quantifier-in","title":"Quantifier-in","text":"

    interrogative: asking a question 

    which woman does every man love?\n

    which scopes over every.

    "},{"location":"docs/2-ling/semantics/ambiguity/#scope-ambiguity_1","title":"Scope ambiguity","text":"

    e.g. some boy did not laugh. 

    \\exist x (Boy(x) and ~Laugh(x))\n~\\exist x (Boy(x) and Laugh(x))\n

    some boy kissed no girl. 

    \\exist x (Boy(x) and ~\\exist y (Girl(y) and Kiss(x, y)))\n~\\exist y (Girl(y) and \\exist x (Boy(x) and Kiss(x, y))): there was no girl kissed by a boy\n

    every boy kissed no girl. 

    \\forall x (Boy(x) and ~\\forall y(Girl(y) and Kiss(x, y)))\n

    "},{"location":"docs/2-ling/semantics/ambiguity/#deictic","title":"Deictic","text":"

    No boy said he was hungry.

    No boy was present. He was outside instead.: \u201che\u201d is trying to refer to \u201dno boy\u201d but outside the scope.

    pronoun \\(\\sub\\) anaphora

    "},{"location":"docs/2-ling/semantics/ambiguity/#discourse-anaphora","title":"Discourse Anaphora","text":"

    e.g. 

    Every student was present and she was interested.\n

    every: scopes over \u201cEvery student was present\u201d

    every: an indefinite quantifier. \u201cshe\u201d\u2019s antecedent is not clear

    \u201cshe\u201d is hardly bound by the antecedent. \u201cshe\u201d is free * ungrammatical: \u4e0d\u5408\u8bed\u6cd5\u7684, syntactic

    "},{"location":"docs/2-ling/semantics/ambiguity/#infelicitous-semantic-fit-the-context","title":"infelicitous: \u4e0d\u5408\u9002\u7684, semantic, fit the context","text":"

    :material-circle-edit-outline: \u7ea6 1349 \u4e2a\u5b57 :fontawesome-solid-code: 15 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 5 \u5206\u949f

    So we may conclude the following rules for e-type anaphora. BUT this part has NOT been verified with any authority. Do NOT take them as given truths during exams.

    e.g. No boy thinks that he has a chance. 

    ~\\exist x(Boy(x) and Think(x, Has-a-chance(x)))\n

    A particular boy said he wanted to kiss every girl. He then did it. 

    \\exist !x(Bx and  W(x, K(x, \\forall y(Gy -> K(x, y))))) and K(x, y)\n

    "},{"location":"docs/2-ling/semantics/ambiguity/#donkey-anaphora","title":"Donkey anaphora","text":"

    if a farmer owns a donkey, he beats it. 

    * \\exist x (Fx and \\exist y (Dy and O(x, y))) -> B(x, y)\n\\forall x \\forall y (Fx and Dy and O(x, y) -> B(x, y))\n

    = every farmer who owns a donkey beats it. 

    \\exist x(Fx and \\exist y (Dy and O(x, y)) -> B(x, y))  // y is free\n

    \u2757\u2757\u2757

    A donkey sentence is such that an expected existential is interpreted as universal taking wide scope.

    donkey pronoun can be: it, him, they (can also be plural forms)

    \u201ca\u201d: generic indefinite 

    A woman is a difficult thing to please.\n

    [Every farmer [who owns a donkey] beats it.]

    universal wide scope: it scopes more over the relative clause

    The problem - Existential with narrow scope - interpreted as universal with wide scope - in conditional clauses - in restriction of every

    Conclusion - the machinery of predicate logic is broken - cannot capture meaning of natural language

    If a student tries, she passes the exam. 

    (\\exist x(Sx and Tx)) -> Py   ; y is free\n\\exist x((Sx and Tx)) -> Py)\n

    interpretation 

    \\forall x((Sx and Tx) -> px)\n

    Solutions for donkey anaphora:

    Reference: Unselective Binding

    "},{"location":"docs/2-ling/semantics/ambiguity/#chapter-6-in-short-discoursedonkey-anaphora","title":"Chapter 6 in short: Discourse/Donkey Anaphora","text":"

    (\u52a0\u7c97\u7684\u662fDonkey anaphora\u548cE-type anaphora\u7684\u533a\u522b)

    Discourse: basic unit of interpretation

    Anaphoric relations in sentence and discourse - E-type anaphora: pronoun outside the scope of binder, not bound, content of pronoun reconstructed, reconstruction based on context - in separate sentences

        ```\n    A student came in. *She*(the student came in) had a question about the exam.\n    ```\n\n- in the same sentence but outside the scope\n    ```\n    If a student likes Copenhagen, *she*(for every case we examine, the student in question who likes Copenhagen) is happy.\n    ```\n\n- problem of compound: antecedent must appear as a noun?\n    ```\n    Bill owns a cat. Max takes care of it.\n    Bill is a cat-owner. # Max takes care of it.\n    ```\n

    Anaphora resolution - TODO

    "},{"location":"docs/2-ling/semantics/definitions/","title":"Definition Clarification","text":"

    :material-circle-edit-outline: \u7ea6 1068 \u4e2a\u5b57 :fontawesome-solid-code: 53 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/2-ling/semantics/definitions/#what-is-semantics","title":"What is semantics?","text":""},{"location":"docs/2-ling/semantics/definitions/#the-topics-involving","title":"The topics involving:","text":""},{"location":"docs/2-ling/semantics/definitions/#meaning-capturing-metalanguage-tools","title":"Meaning capturing: metalanguage tools","text":""},{"location":"docs/2-ling/semantics/definitions/#ways-to-capture-meaning-henriette-de-swart","title":"Ways to capture meaning: (Henri\u00ebtte de Swart)","text":""},{"location":"docs/2-ling/semantics/definitions/#predicatepredicate-calculusfirst-order-predicate-logic","title":"Predicate/Predicate Calculus/First-order Predicate Logic","text":""},{"location":"docs/2-ling/semantics/definitions/#map-of-linguistics-theory","title":"Map of Linguistics Theory","text":"
    graph TD\n  Language_Ability --> Competence\n  Language_Ability --> Performance\n  Competence --> Grammar\n  Competence --> Lexicon\n  Grammar --> Semantics\n  Grammar --> Phonology\n  Grammar --> Syntax\n  Grammar --> Pragmantics\n
    "},{"location":"docs/2-ling/semantics/definitions/#semantics-syntax","title":"Semantics & Syntax","text":""},{"location":"docs/2-ling/semantics/definitions/#syntax-needs-semantics","title":"Syntax needs semantics","text":""},{"location":"docs/2-ling/semantics/definitions/#semantics-needs-syntax","title":"Semantics needs Syntax","text":""},{"location":"docs/2-ling/semantics/definitions/#semantics-pragmatics","title":"Semantics & Pragmatics","text":""},{"location":"docs/2-ling/semantics/definitions/#context-and-deixis","title":"Context and Deixis","text":""},{"location":"docs/2-ling/semantics/definitions/#deixis-needs-context","title":"Deixis needs context","text":"

    Deixis is how objects, events and situations relate to the here and now of the speakers. It shows that utterance meaning cannot be fully determined by sentence meaning.

    (Last week) (I) play(ed) tennis with Chris.\n
    "},{"location":"docs/2-ling/semantics/definitions/#deictic-vs-anaphoric-use-of-pronouns","title":"Deictic vs. Anaphoric use of pronouns","text":"

    Deictic: pointing context Anaphoric: linguistic expression context. pronoun resolution: antecedent - pronoun

    \ud83d\udcad index - indices (higher register) / indexes \ud83d\udcad Desiderata (high-register way to say Goal, desideratum. sl.)"},{"location":"docs/2-ling/semantics/definitions/#map-of-semantics-taxomony","title":"Map of Semantics / Taxomony","text":"

    Semantics - lexical semantics - meaning of lexical items - smaller unites - mainly words - morphemes - compositional semantics - meaning of larger units - phrases and sentences - word combination

    "},{"location":"docs/2-ling/semantics/definitions/#utterance-sentence-proposition","title":"Utterance / Sentence / Proposition","text":""},{"location":"docs/2-ling/semantics/definitions/#lexical-semantics","title":"lexical semantics","text":" 
    abiguity: bank, punch, pitcher\nsynonymy: beautiful-lovely, antonymy: male-female\nhyponymy: set -> superset\ntaxonomy: set -> subset\nsymmetric relation: marry. mutually entail each other\nconverse relation: send, sell\nmeronomy:
    "},{"location":"docs/2-ling/semantics/definitions/#1-homonymy","title":"1) homonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#2-polysemy","title":"2) polysemy","text":""},{"location":"docs/2-ling/semantics/definitions/#3-synonymy","title":"3) synonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#4-antonymy","title":"4) antonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#5-hyponymy","title":"5) hyponymy","text":""},{"location":"docs/2-ling/semantics/definitions/#6-meronymy","title":"6) meronymy","text":"

    part-whole relationship

    subtypes of meronymy

    pistachio - almond taxonymy\nlaugh - cry move in - move out\ncry - weep\nRMB - monetary unit\ngrilfriend - wife\nsit - stand\njump - hop\ngood - bad\nbeat - beet\nrise - fall reverse\ncigarette - cigar taxonymy\nkid - goat dragon - monster\n
    "},{"location":"docs/2-ling/semantics/definitions/#compositional-semantics","title":"Compositional semantics","text":""},{"location":"docs/2-ling/semantics/definitions/#inventory-of-components","title":"Inventory of components","text":""},{"location":"docs/2-ling/semantics/definitions/#important-linguistics","title":"Important linguistics","text":"

    Michel Br\u00e9al: coined semantics

    Ferdinand de Saussure: semiotician, diachronic vs. synchronic.

    Leonard Bloomfield: structural linguistics, Language, behaviorism(stimulus-response testing). reject introspection(theorize about language learning by thinking about on ones own experience)

    "},{"location":"docs/2-ling/semantics/definitions/#diachronic-synchronic","title":"Diachronic & Synchronic","text":""},{"location":"docs/2-ling/semantics/definitions/#signifier-signified-referent","title":"Signifier & Signified & Referent","text":""},{"location":"docs/2-ling/semantics/definitions/#langue-parole","title":"Langue & Parole","text":""},{"location":"docs/2-ling/semantics/definitions/#paradigmatic-syntagmatic","title":"Paradigmatic & Syntagmatic","text":"

    Noam Chomsky Syntax

    "},{"location":"docs/2-ling/semantics/definitions/#generative-grammar","title":"Generative Grammar","text":""},{"location":"docs/2-ling/semantics/definitions/#ambiguity","title":"Ambiguity","text":"

    e.g. Flying planes can be dangerous.

    graph TD\n  are --> planes\n    planes --> flying\n    are --> dangerous\n
    graph TD\n    is --> flying\n    flying --> planes\n    is --> dangerous\n
    "},{"location":"docs/2-ling/semantics/definitions/#pronoun-resolution","title":"pronoun resolution","text":""},{"location":"docs/2-ling/semantics/definitions/#inference","title":"Inference","text":"

    notes: cf. compare, e.g. for example

    graph TD\n  Inference --> Entailment\n  Inference --> Presuppositions\n  Inference --> Implicature\n

    any conclusion drawn from a set of propositions, from something someone has said and so on.

    "},{"location":"docs/2-ling/semantics/definitions/#entailment","title":"Entailment","text":" 
    Three girls were present. -> More than two girls were present.\nThree girls were not present. kills More than two girls were present.\n

    Cannot be cancelled

    # Three girls were present, but actually two girls come.\n#: semantically wrong\n
    "},{"location":"docs/2-ling/semantics/definitions/#presupposition","title":"Presupposition","text":" 
    Jim regrets ignoring the first problem. -> Jim has the first problem.\nJim does not regret ignoring the first problem. -> Jim has the first problem.\n

    cannot be cancelled

    # Jim regrets ignoring the first problem, but he does not have the first problem.\n
    "},{"location":"docs/2-ling/semantics/definitions/#implicature","title":"Implicature","text":" 
    Susan blushes when Jim looks at her, but she does not have a crush on him.\n
    "},{"location":"docs/2-ling/semantics/definitions/#compositionality","title":"Compositionality","text":"

    Proposed by Noam Chomsky, the term compositionality entails three dimension.

    "},{"location":"docs/2-ling/semantics/definitions/#principle-of-compositionally-of-meaning","title":"Principle of compositionally of meaning","text":"

    The meaning of the whole is a function of the meaning of its parts and the way they are put together.: \u2026 is determined by\u2026

    "},{"location":"docs/2-ling/semantics/formal_semantics/","title":"Logics & Formal Semantics","text":"

    :material-circle-edit-outline: \u7ea6 2560 \u4e2a\u5b57 :fontawesome-solid-code: 24 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 9 \u5206\u949f

    "},{"location":"docs/2-ling/semantics/formal_semantics/#metalanguage","title":"Metalanguage","text":" 
    a. January has 31 days.\nb. *******January******* has 7 letters.\nb*. 'January' has 7 letters.\n

    Liar sentence

    (31) Sentence (31) is false.\n

    solutions: (\u4e0d\u8003)

    "},{"location":"docs/2-ling/semantics/formal_semantics/#connectives-truth-and-truth-conditions","title":"Connectives, truth, and truth conditions","text":"

    logic overview

    graph TD\n  Logic --> Logic_from_antiquity\n    Logic --> Predicate_Logic\n    Logic_from_antiquity --> Term_Logic\n    Logic_from_antiquity --> Propositional_Logic\n

    logic from antiquity: older

    predicate logic: newer

    Aristotle: term logic

    Gottlob Frege: predicate logic

    "},{"location":"docs/2-ling/semantics/formal_semantics/#history-of-logics","title":"History of Logics","text":"

    Not applied for - question (?) - exclamation - modal: modal logic

    \ud83d\udcad ergo: therefore"},{"location":"docs/2-ling/semantics/formal_semantics/#term-logic","title":"Term logic","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#modus-ponens","title":"Modus Ponens","text":"

    Means of putting, MP syllogism, affirming the antecedent

    P(conditional statement): If it rain, I do not go to school.\nH: It rains.\nC: I do not go to class.\n

    Formal fallacy: affirming the consequent. Abductive reasoning. 

    P: If it rains, I will not go to class.\nH: I do not go to class.\nC: * It rains.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#modus-tollens","title":"Modus Tollens","text":"

    Means of carrying, MT syllogism, denying the consequent. 

    P: If it has not been cloudy, it does not rain.\nH: It rains.\nC: It has been cloudy.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#hypothetical-syllogism","title":"Hypothetical syllogism","text":"

    principle of transitivity 

    P: If it rains, the soils goes wet. If the soil goes wet, the plants grow.\nH: It rains.\nC: The plants grow.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#disjunctive-syllogism","title":"Disjunctive syllogism","text":"

    two premises and a conclusion 

    P: It either rains or its sunny.\nH: It rains.\nC: It is not sunny.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#three-types-of-reasoning","title":"Three types of reasoning","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#propositional-logic","title":"Propositional logic","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#conditional-material-implication","title":"conditional, material implication","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#biconditional","title":"biconditional","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#de-swarts-formalizations","title":"De Swarts formalizations","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#well-formed-formula","title":"Well-formed formula","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#propositional-practice","title":"Propositional practice","text":"John is happy. p John is not happy. ~p John is happy or sad. p or q exlusive John is happy, not sad. p and ~q If John has eaten, John is happy. p -> q If John has not eaten, John is not happy. ~p -> ~q John is hungry or thirsty. p or q inclusive. John left before you did. p John is not hungry or thirsty. ~(p or q inclusive) <-> ~p and ~q John is not hungry and thirsty. ~(p and q) <-> ~p or ~q inclusive If John did not laugh, then John cried. ~p \u2192 q \u2194 p or q If John laughed, then John also cried. p \u2192 q \u2194 ~p or q inclusive John did not laugh, or John cried. ~p or q \u2194 p \u2192 q John laughed, or John cried and beat on the table. p and (q or r) \u2194 (p and q) or (p and r) John is not happy, but rather sad. (scope of \u201cnot\u201d) ~p and q. * ~(p and q) John is not happy, or sad. ~(p and q) John is not happy, or John is sad. ~p or q John did not help us or hinder us. ~(p or q) \u2194 ~p and ~q John did not help us or John hinders us. ~p or q 
    John is friendly or John is not friendly.\n
    p V_e ~p T T F F T T 
    John is friendly and John is not friendly.\n
    p and ~p T F F F F T 
    It is not the case that John is not friendly.\n
    ~ ~ p T F T F T F

    contingent.

    It is not the case that John is hungry or John is not grumpy.\n
    ~( p or ~q F T T T F T T F F F T T T F F F"},{"location":"docs/2-ling/semantics/formal_semantics/#material-implication","title":"Material implication \u2192","text":"

    converse: q\u2192p. affirming the consequent

    inverse: ~p\u2192~q. denying the antecedent

    contrapositive: ~q\u2192~p. modus tollens

    given p\u2192q.

    Although it was extremely cold, Sally did not stay indoors.

    ~q->p\np and ~q\n

    We get a holiday, or we protest.

    ~p->q\np or q\n

    Jone said that Jane helped him.

    p\np and q\n

    John\u2019s sister burped

    p: John has a sister. presupposition, assume it true\nq: This sister burped.\np\np and q\n

    John arrives before Jane left

    p before q\n

    John did not arrive before Jane left.

    ~p before q\np ~before q\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#predication-and-quantification","title":"Predication and Quantification","text":"

    universal quantifier: every, each, all, any, only

    existential quantifier: a, some, there is \\(\\exist\\), for all \\(\\forall\\)

    predicate, argument

    John may like Sally.

    predicate: may like\n

    John has a crush on Sally.

    predicate: has a crush on\n

    Frank is the father of Susan.

    predicate: is the father of\n

    Frank is Susan\u2019s father.

    predicate: is...'s father\n

    Adjunct: if, probably, means, of course, early

    Valent, empty place holder: formal subject

    "},{"location":"docs/2-ling/semantics/formal_semantics/#collective-and-distributive-readings","title":"Collective and distributive readings","text":"
    Jogn and Molly ate a pizza.\np: one pizza, ate one together.   distributive\np and q: two pizzas, each ate a pizza.  collective\n
    Cinthia and Sam have saved 100 dollars.\np: together 100 dollars\np and q: 200 dollars\n

    Content verb is a predicate, but functional verbs are not

    John obviously spoke with Jane because he had to.

    predicate: spoke with\nargument: John, Jane\nadjuncts: obviously, because he had to.\n

    If I get a chance, I will probably try to avoid the mistake.

    predicate: will try to \nargument: I, avoid the mistake\nadjuncts: If I get a chance, probably\n

    John performed Jill\u2019s operation first.

    \n

    The person who talk loudly is Jim\u2019s father.

    predicate: is someone's father\nargument: the person who talk loudly, Jim\nadjunct: \n

    the talking loudly person

    predicate: talking\nargument: person\nadjunct: loudly\n

    predicate: the nodes that are connected in SUD parsing tree

    universal dependency (UD)

    syntactic-universal dependency (SUD)

    graph TD\n  Primitive_units_within_propositions --> Predicates\n  Primitive_units_within_propositions --> Arguments\n    Arguments --> individuals_Terms\n    individuals_Terms --> constants\n    individuals_Terms --> variables\n

    lexical predicates vs. syntactic predicates

    individual constants vs. individual variables

    e.g. We think John likes Susan.

    T(w, Lj,s)\n

    Types of predicates:

    e.g. Monica hid her bicycle.

    x hide y: Hx,y\nMonica: m\nher bicycle: b\nHm,b\n

    e.g. Monica did not hide her bicycle.

    x hide y: Hx,y\nMonica: m\nher bicycle: b\n~Hm,b\n

    e.g. Monica laughed and cried.

    Monica: m\nlaugh: L()\ncry: C()\nLm and Cm\n

    e.g. Jim sent Monica his dog.

    Sj,m,d\n

    e.g. William did not help or hinder Mike.

    ~ (H1w,m or H2w,m) \n

    e.g. Jennifer promise to help.

    P(j, Hj)\n

    e.g. Jennifer did not promise to help.

    ~P(j,Hj)\n

    e.g. Jennifer promise to not laugh.

    P(j,~Lj)\n

    e.g. Mike claimed he wanted to help.

    C(m, W(m/x, Hm/x))\n\nm: Mike\nx: maybe some other\n

    e.g. John asked Mandy to stop laughing.

    A(j, m, S(m, Lm))\n

    e.g. John and Larry called Molly.

    Cj,m and Cl,m\nC(j and l, m)\n

    e.g. Molly did not call John and Larry.

    ~C(m, j) and ~C(m, l)\n~C(m, j and l)\n~C(m, j) or ~C(m, l)\n

    entailment: (universal instantiation)

    every dog barks \u2192 if something is a dog, then it is a dog.

    Universal quantification

    \\(\\forall\\)x (Dx \u2192 Bx)

    D = (d1, d2, d3,\u2026)

    \\(\\forall\\)x (Dx \u2192 Bx)= (Bd1 and Bd2 and Bd3, \u2026.)

    Existential quantification

    \\(\\exist\\)x (Dx and Bx)

    D = (d1, d2, d3,\u2026)

    \\(\\exist\\)x (Dx and Bx) = (Bd1 or Bd2 or Bd3, \u2026.)

    e.g. Every cat barfed.

    \\forall x (Cx -> Bx)\n

    e.g. The cat barfed.

    Bc\n

    e.g. Bill fed cat.

    \\forall x (Cx -> Fb,x)\n

    e.g. Some dog barked at Fred.

    \\exist x (Dx and Bx,f)\n

    e.g. Fred scolded some dog.

    \\exist x (Dx and Sf,x)\n

    e.g. Fred and Susan avoid some dog.

    \\exist x (Dx and Af,x and As,x)\n\\exits x (Dx and Af,x) and \\exist y (Dy and Af,s)\n

    e.g. No dog barks.

    \\forall x (Dx -> ~Bx)\n~\\exist x (Dx and Bx)\n

    e.g. Bill fed no dog.

    ~\\exist x (Dx and Fb,x)\n\\forall x (Dx -> ~Fb,x)\n

    e.g. No dog barked at Susan or chased Fred.

    ~\\exist x ((Dx and (Bx,s or Cx,f))\n\\forall x ((Dx -> (~Bx,s and ~Cx,f))\n\\forall x ((Dx -> ~(Bx,s or Cx,f))\n

    Scope ambiguity

    e.g. Some boy kissed every girl.

    \\exist x \\forall y (Bx and (Gy -> Kx,y)) = \\exist x(Bx and \\forall y (Gy -> Kx,y))\n\\forall y \\exist x (Gy -> (Bx and Kx,y)) = \\forall y (Gy -> \\exist x (Bx and Kx,y))\n

    Every boy kissed some girl.

    \\forall x (Bx -> \\exist (Gy and Kxy)) <=> \\forall x \\exist y (Gy and Kxy)\n

    Every students did not laugh.

    \\forall x (Sx -> ~Lx) <=> ! \\exist x (Sx and Lx)\n~\\forall x (Sx -> Lx) <=> \\exist (Sx and ~Lx)\n

    Not every student laughs.

    ~\\forall x (Sx -> Lx) <=> \\exist (Sx and ~Lx)\n
    graph TD\n  laughed --> student\n    student --> /every\n    /every --> not\n

    each studnet did not laugh.

    \\forall x (Sx -> ~Lx) \n~\\forall x (Sx -> Lx)\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#polarity-item","title":"Polarity item","text":"

    any: negative polarity item

    John did not pass every exam.

    ~\\forall x (Ex -> Pj,x) <=> \\exist x (Ex and Pj,x)\n\\forall x (Ex -> ~Pj,x)\n

    John did not pass any exam.

    \\forall x (Ex -> ~Pj,x)\n

    e.g.

    Jack saw a rat.

    \\exist x (Rx and Sj,x) \n

    Jack is a rat.

    the quantifier is in the predicate but not the argument. here rat is a constant.

    Rj\n

    Jack knows no genius.

    use not exist to render \u201cno\u201d

    ~\\exist x (Gx and Kj,x)  <=> \\forall x (Gx -> ~Kj,x)\n

    Jack is no genius. <=> Jack is not a genius.

    ~Gj\n

    These problems are difficult.

    Dp\n

    These problems are difficult ones.

    Dp\n

    All the problems are difficult.

    \\forall x (Px -> Dx)\n

    These problems are all the problems.

    Ap\n

    These problems are not all the problems.

    ~Ap\n

    Jack is our plumber.

    Pj\n

    Our plumer is Jack. (has presupposition)

    Pj\n

    Everything counts.

    whether thing includes animate and inanimate.

    \\forall x (Cx)\n\\forall x (Tx -> Cx)\n

    Everybody counts.

    *\\forall x (Cx)\n\\forall x (Px -> Cx)\n

    predicates

    common nouns

    content verbs are the core of syntactic predicates

    adjectives are most always the core of syntactic predicates.

    e.g. Mike\u2019s wife thinks Mikes if lazy.

    predicates inside individual constants are presuppositional

    A thin man was present.

    predicates inside \u2026 .are propositional

    e.g. Every barking is harmless

    has true or false impact on the truth

    \\forall x ((Dx and Bx) -> Hx)\n

    this proposition has to show up in the predicate

    The barking dog is harmless.

    Hd\n

    the presupposition does not show in the predicate

    John avoids every dog he sees.

    \\forall x ((Dx and Sj,x) -> Aj,x)\n

    John said every dog barks.

    intensional

    Sj\nS(j,\\forall x (Dx -> Bx)) \nSj,I  ; I for intensional argument predicate\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#adjunct-predicates","title":"Adjunct predicates","text":"

    Jane probably teased Sam last night

    John arrived drunk.

    Jim burped twice.

    twice: propositional or presuppositional

    Susan did not cheat yesterday.

    Mary stayed because John stayed.

    Mary did not stay because John stayed

    "},{"location":"docs/2-ling/semantics/formal_semantics/#restricted-quantification","title":"restricted quantification","text":"

    Every boy was hungry

    \\forall x: Bx(Hx)\n

    Some boy was hungry.

    \\exist x: Bx(Hx)\n

    Every cat barfed.

    \\forall x: Cx(Bx)\n

    Bill fed every cat.

    \\forall x (Cx, Fb,x)\n\\forall x: Cx(Fb,x)\n

    Some dog barked at Fred.

    \\exist x (Dx, Bx,f)\n\\exist x: Dx(Bx,f)\n

    Fred and Susan avoid some dog.

    \\exist x(Dx and (Af,x and As,x))\n\\exist x: Dx (Af,x and Af,x)\n

    No dog barks.

    ~\\exist x (Dx and Bx) <=> ~\\exist x: Dx (Bx)\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#formal-predicate-semantics","title":"Formal Predicate Semantics","text":"
    graph TD\n  Semantic_Rules --> Model\n  Semantic_Rules --> Valuation_Function\n    Model --> Universe_of_Discourse\n    Model --> Interpretation_Function\n    Universe_of_Discourse --> entities\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#relation","title":"Relation","text":""},{"location":"docs/2-ling/syntax/","title":"Syntax","text":"

    :material-circle-edit-outline: \u7ea6 23 \u4e2a\u5b57

    \u4e0d\u597d\u8bf4 \u65bd\u5de5\u4e2d

    \u76ee\u5f55

    "},{"location":"docs/2-ling/syntax/conv_gen/","title":"\u8f6c\u6362\u751f\u6210\u53e5\u6cd5","text":"

    :material-circle-edit-outline: \u7ea6 599 \u4e2a\u5b57 :fontawesome-solid-code: 30 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    "},{"location":"docs/2-ling/syntax/conv_gen/#x-bar-theory","title":"X-bar theory","text":"

    \u751f\u6210\u53e5\u6cd5\u548c\u6210\u5206\u53e5\u6cd5\u4e4b\u95f4\u7684\u533a\u522b

    [The big book of poems with the blue cover] is on the table.\n

    \u6210\u5206\u53e5\u6cd5\u505a\u51fa\u6765\uff0csubject\u662f\u4e00\u4e2a\u9ad8\u5ea6\u4e3a1\u7684\u6811

    \u53e5\u5b50\u4e4b\u95f4\u7684\u6210\u5206\u901a\u8fc7\u4e24\u4e24\u7ec4\u5408\u8fd8\u80fd\u505a\u51fa\u65b0\u7684\u9ad8\u5ea6

    one-replacement

    \u7528one-replacement\u63a2\u6d4b\u9650\u5b9a\u8bcd\u4e4b\u95f4\u7684\u8ddd\u79bb\u5173\u7cfb\uff08\u52a8\u8bcd\u7528did so/did too\uff09

    Mika loved the policeman intensively.\nSusan did so half-heartedly.\n*Susan did so the baker.\n
    graph TD\n  NP --> D\n    D --> the\n    NP --> N1\n    N1 --> AdjP\n    AdjP --> big\n    N1 --> N2\n    N2 --> N3\n    N2 --> PP1\n    N3 --> N\n    N --> book\n    N3 --> PP2\n    PP2 --> of_poems\n    PP1 --> with_the_blue_cover\n

    \u52a0\u5165\u4e86bar level\uff0cbook\u4e0eof poems\u6784\u6210\u4e00\u4e2a\u4e2d\u95f4\u6295\u5c04X-bar\uff0c\u6784\u6210\u4e00\u4e2aconstituent\u3002\u4f7f\u5f97\u6bcf\u4e2a\u53e5\u5b50\u90fd\u80fd\u88ab\u753b\u6210\u4e00\u4e2a\u4e8c\u53c9\u6811\u5f62\u5f0f

    \u751f\u6210\u53e5\u6cd5\u5b66\u6d3e\uff1a\u4e0a\u4e16\u7eaa\u4e94\u5341\u5e74\u4ee3\u3002classical theory and standard theory\u30021988\u5e74\u63d0\u51fa\u4e86government and binding theory\u3002lexicon, D-S, S-S, PF, LF

    "},{"location":"docs/2-ling/syntax/conv_gen/#n-bar","title":"N-bar","text":"

    \u539f\u672cNP\u6839\u636e\u4e00\u7cfb\u5217\u89c4\u5219\u4e0d\u662f\u4e8c\u53c9\u6811\uff0c\u6bd4\u5982N\u2192

    N-bar theory\u8ba4\u4e3a\u53ef\u4ee5\u90fd\u53d8\u6210\u4e8c\u53c9\u6811

    \u89c4\u5219\u6bd4\u5982

    NP -> Det N'\nN' -> AP N'\nN' -> N PP\n

    \u7b2c\u4e00\u6761\u79f0\u4e3a\u4e00\u4e2a\u6700\u5927\u6295\u5c04

    "},{"location":"docs/2-ling/syntax/conv_gen/#v-bar","title":"V-bar","text":"
    VP -> V'   // \u9884\u7559\u4e00\u4e2a\u4f4d\u7f6e\u7ed9\u6f5c\u5728\u7684specifier\uff0c\u5373\u4f7f\u6ca1\u6709\nV' -> AdvP V' | V' PP | V' AdvP\nV' -> V(NP)\n
    "},{"location":"docs/2-ling/syntax/conv_gen/#abj-bar","title":"Abj-bar","text":"
    AdjP -> Adj'\nAdj' -> (AdvP) Adj' | Adj' (AdvP)\nAdj' -> Adj(PP)\n
    "},{"location":"docs/2-ling/syntax/conv_gen/#p-bar","title":"P-bar","text":"
    PP -> P'\nP' -> P'(PP) | (AdvP)P'\nP' -> P(NP)\n

    \u4e2d\u5fc3\u8bcdX \u2192 \u4e2d\u95f4\u6295\u5c04X\u2019 \u2192 \u6700\u5927\u6295\u5c04XP\u3002\u4e0d\u80fd\u76f4\u63a5\u5230XP\uff0c\u4e00\u5b9a\u8981\u6709\u4e2d\u95f4\u6295\u5c04

    "},{"location":"docs/2-ling/syntax/conv_gen/#parameter-of-word-orders","title":"Parameter of Word Orders \u7ba1\u7ea6\u8bba\uff0c \u539f\u5219\u4e0e\u53c2\u6570\u7406\u8bba","text":"

    \u6839\u636eX-bar\u7406\u8bba\uff0c\u53ef\u4ee5\u5bf9\u4e00\u4e9b\u8bed\u8a00\u7684\u4e0d\u540c\u8bed\u5e8f\uff08\u5982SVO\uff0cSOV\u7b49\uff09\u7ed9\u51fa\u8bed\u6cd5\u53c2\u6570\u5316\u89e3\u91ca

    specifier\u548ccomplement\u53ef\u4ee5\u51fa\u73b0\u5728\u5176sister\u7684\u4e24\u4fa7\uff0c\u8fd9\u79cd\u6295\u5c04\u7684\u5de6\u53f3\u533a\u522b\u88ab\u79f0\u4e3aparameter setting

    "},{"location":"docs/2-ling/syntax/conv_gen/#_2","title":"\u753b\u6811\u7684","text":""},{"location":"docs/2-ling/syntax/conv_gen/#head-movement","title":"Head Movement \u4e2d\u5fc3\u8bed\u79fb\u4f4d","text":"

    head movement: movement from a head to another head position

    \u53e5\u5b50\u53ef\u4ee5\u53d1\u751fmovement\u7684\u6807\u5fd7

    "},{"location":"docs/2-ling/syntax/conv_gen/#-reading","title":"- \u4e00\u4e2a\u53e5\u6cd5\u7ed3\u6784\u5177\u6709\u4e24\u79cdreading","text":"

    shortest movement

    shortest: let the path of a movement be the set of nodes that dominate the original position of the moved item, and do not dominate the leading site.

    "},{"location":"docs/2-ling/syntax/ud_sud/","title":"\u4f9d\u5b58\u53e5\u6cd5 UD & SUD","text":"

    :material-circle-edit-outline: \u7ea6 381 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    In full spelling, Universal Dependency gammar and Surface Syntax Universal Dependency grammar.

    "},{"location":"docs/2-ling/syntax/ud_sud/#tools","title":"Tools","text":"

    AllenNLP Demo CoreNLP Tool

    "},{"location":"docs/2-ling/syntax/ud_sud/#concepts","title":"Concepts","text":""},{"location":"docs/2-ling/syntax/ud_sud/#ud","title":"UD","text":"

    Dependency grammar\u00a0(DG) is an approach to the study of the syntax and grammar of natural languages that is quite distinct from\u00a0phrase structure grammar\u00a0(PSG), which is also known as\u00a0constituency grammar. The modern history of DG begins with\u00a0Lucien Tesni\u00e8re's major oeuvre (1959), whereas the modern history of PSG begins arguably with\u00a0Noam Chomsky's first prominent work (1957).

    DG views linguistic structures in terms of a\u00a0one-to-one mapping\u00a0of atomic linguistic units to the nodes in structure, whereas PSG assumes a\u00a0one-to-one-or-more mapping. The distinction is clearly visible when one compares the tree structures. The next trees are taken from the\u00a0Wikipedia article on DG:

    "},{"location":"docs/2-ling/syntax/ud_sud/#sud","title":"SUD","text":"

    [Surface Syntactic Universal Dependencies (SUD) | SUD](https://surfacesyntacticud.github.io/ SUD is an annotation scheme for syntactic dependency treebanks, and has a nearly perfect degree of two-way convertibility with the Universal Dependencies scheme (UD). Contrary to UD, it is based on syntactic criteria (favoring functional heads) and the relations are defined on distributional and functional bases.

    "},{"location":"docs/2-ling/syntax/ud_sud/#general-principles-of-sud","title":"General principles of SUD","text":""},{"location":"docs/2-ling/syntax/ud_sud/#specific-sud-relations","title":"Specific SUD relations","text":"

    SUD has 4 specific syntactic relations and a few extended relations: - subj - udep - comp - comp:aux - comp:cleft - comp:obj - comp:obl - comp:pred - mod

    "},{"location":"docs/2-ling/syntax/uni_gram/","title":"\u666e\u904d\u8bed\u6cd5 Universal Grammar","text":"

    :material-circle-edit-outline: \u7ea6 260 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/2-ling/syntax/uni_gram/#introduction","title":"Introduction","text":"

    Syntax\u7684\u610f\u4e49\u5728\u4e8e\u627e\u5230\u4e00\u79cdgrammar\uff0c\u80fd\u591f\u751f\u6210\u67d0\u79cd\u8bed\u8a00\u4e2d\u7684\u6240\u6709\u53e5\u5b50\u3002

    Grammar\u662f\u57fa\u4e8e\u89c4\u5219\u7684\uff0c\u4e0d\u80fd\u7528high order of statistical approximation to English\u6765\u66ff\u4ee3\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#basic-linguistics","title":"Basic Linguistics","text":"

    DFA & Regular language

    \u8c13\u8bcd\u903b\u8f91\u3002\u4f46\u6211\u4eec\u4e0d\u5173\u5fc3\u5176\u4e2d\u7684\u8bed\u4e49\uff0c\u53ea\u9700\u5173\u5fc3CFG\u7684\u5f62\u5f0f\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#phrase-structure-limitation","title":"Phrase Structure & Limitation","text":"

    \u81ea\u7136\u8bed\u8a00\u7684CFG\uff08\u4ee5\u82f1\u8bed\u4e3a\u4f8b\uff09\u6784\u6210\u8bed\u6cd5\u7684\u57fa\u7840\u90e8\u5206\u3002

    \u4f46\u8fd9\u6837\u63cf\u8ff0\u81ea\u7136\u8bed\u8a00\u7684\u5de5\u5177\u8fd8\u662f\u4e0d\u80fd\u751f\u6210\u6240\u6709\u5408\u7406\u7684\u53e5\u5b50\uff0c\u6545\u5f15\u5165a more powerful model combining phrase structure and grammatical transformation\uff0c\u5f97\u5230\u8f6c\u6362-\u751f\u6210\u6587\u6cd5\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#on-the-goals-of-linguistic-theory","title":"On the Goals of Linguistic Theory","text":"

    \u4ece\u4e00\u822c\u8bed\u6cd5\u4e2d\u5f52\u7eb3\u51faUG\u7406\u8bba\uff0c\u5bf9UG\u7684\u671f\u671b\u7531\u5f3a\u81f3\u5f31\u4e3a\uff1a

    "},{"location":"docs/2-ling/syntax/uni_gram/#the-explanatory-power-of-linguistic-theory","title":"The Explanatory Power of Linguistic Theory","text":"

    \u5e94\u8be5\u7814\u7a76competence\uff0c\u800c\u975eperformance

    "},{"location":"docs/3-dl/","title":"Deep Learning","text":"

    :material-circle-edit-outline: \u7ea6 26 \u4e2a\u5b57

    "},{"location":"docs/3-dl/#contents","title":"Contents","text":""},{"location":"docs/3-dl/#todo","title":"TODO","text":""},{"location":"docs/3-dl/#references","title":"References","text":"

    AI\u5185\u5bb9\u751f\u6210\uff08ai-gc\uff09

    "},{"location":"docs/3-dl/basics/","title":"Index","text":"

    :material-circle-edit-outline: \u7ea6 0 \u4e2a\u5b57

    "},{"location":"docs/3-dl/basics/bpe/","title":"Byte pair encoding (BPE)","text":"

    :material-circle-edit-outline: \u7ea6 144 \u4e2a\u5b57

    The original version of this algorithem focuses on compression. It replaces the highest-frequency pair of bytes with a new byte that was not contained in the initial dataset. A lookup table of the replacement is required to rebuild the initial dataset. The modified version builds tokens that match varying amount of source text from single characters to whole words.

    Example

    Suppose the sentence to be 

    aaabbaaabac\n

    Since the byte pair (each alphabet as a byte) 'aa' occurs the most often, it is replaced by a byte 'Z' (first match).

    ZabbZabac\n

    Then 'ab' with 'Y'

    ZYbZYac\n

    Then 'ZY' with X

    XbXac\n

    Then this sequence can not be further compressed since there are no byte pair appearing more than once.

    This algorithm is effective for tokenization because it has low computational overhead and remains consistent and reliable.

    References

    Wikipedia - Byte Pair Encoding

    "},{"location":"docs/3-dl/basics/elmo/","title":"ELMo","text":"

    :material-circle-edit-outline: \u7ea6 207 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    ELMo (embeddings from language model) is a word embedding method for representing a sequence of words as a corresponding sequence of vectors. Its essence is a bidirectional LSTM which takes character-level as inputs and produces word-level embeddings.

    According to its original paper (?), it requires training on a corpus of about 30 million sentences and a billion words.

    Contributions:

    e.g., for sentence 

    She went to the bank to withdraw money.\n

    References

    Wikipedia ELMo

    "},{"location":"docs/3-dl/efficient-train/","title":"Efficient Training","text":"

    :material-circle-edit-outline: \u7ea6 7 \u4e2a\u5b57

    "},{"location":"docs/3-dl/efficient-train/#intro","title":"Intro","text":""},{"location":"docs/3-dl/efficient-train/#contents","title":"Contents","text":""},{"location":"docs/3-dl/efficient-train/hardware/","title":"Hardware","text":"

    :material-circle-edit-outline: \u7ea6 1101 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/3-dl/efficient-train/hardware/#gpu","title":"GPU","text":"

    A graphic processing unit (GPU) is an electronic circuit designed for accelerating computer graphics. It is now widely adopted for non-graphic calculations such as the training of neural networks.

    GPU Parameters that are most cared about

    In a table:

    GPU GPU Memory Memory Bandwidth NVLINK CUDA Cores Turning Tensor cores RT cores T4 16GB 320GB/s No 2,560 320 40 A40 48GB 696GB/s Yes 10,752 336 84 RTX 6000 48GB 960GB/s No 18,176 568 142"},{"location":"docs/3-dl/efficient-train/hardware/#a-taxonomy-of-parallelism","title":"A Taxonomy of Parallelism","text":""},{"location":"docs/3-dl/efficient-train/hardware/#data-parallelism","title":"Data Parallelism","text":"

    Data Parallelism replicates the model across multiple GPUs, usually with two specific techniques: (1) fully shared data parallelism (FSDP), and (2) distributed data parallelism (DDP).

    We denote the training dataset as \\(D\\), the shared model parameters as \\(W\\), the model's operation on the dataset as \\(f(D_i, W)\\), the \\(i\\)th processor as \\(p_i\\), the number of processors as \\(P\\), the \\(i\\)th machine which may be mapped to multiple processors as \\(m_i\\), and the number of machines as \\(M\\). In FSDP, the dataset \\(D\\), ignoring its original division of batches, is further divided into \\(P\\) smaller batches \\(D = {D_1, D_2, ..., D_P}\\). Each processor \\(p_i\\) performs a \\(f(D_i, W)\\) on its small batch. Meanwhile, DDP extends the data parallelism technique across multiple machines. The dataset \\(D\\) is first divided into \\(M\\) subsets \\(D = {D_1, D_2, ..., D_M}\\) for each machine, and each subset on \\(m_i\\) is further divided into \\(P_i\\) subsets according to the number of processors on each machine. After each processor performs the processing \\(f(D_{i,j}, W_k)\\), synchronization will be taken across all machines to aggregate and update the model weights \\(W_k \\leftarrow Aggregate(W_1, W_2, ..., W_M)\\).

    While the computation workload is efficiently distributed across GPUs, inter-GPU communication is required to keep the model replicas consistent between training steps.

    "},{"location":"docs/3-dl/efficient-train/hardware/#model-parallelism","title":"Model Parallelism","text":"

    Model parallelism is a distributed model deployment method that partitions the model parameters across GPUs to reduce the need for per-GPU memory. Common techniques of model parallelism include (1) tensor parallelism, (2) pipeline parallelism, and (3) expert parallelism.

    We denote the input data tensor as \\(W\\), the model parameters as \\(W\\), the function representing the model's operations as \\(f(X, W)\\), and the \\(i\\)th processor as \\(p_i\\), the number of processors as \\(P\\).

    Tensor Parallelism distributes the parameter tensor of an individual layer across GPUs. The model weights are divided along specific dimensions into \\(W = {W_1, W_2, ..., W_P}\\), and thus each processor \\(p_i\\) processes part of the model weights \\(f(X, W_i)\\).

    Pipeline Parallelism involves partitioning the computation graph of a model into several stages and assigning each stage to a different processor or machine, making it an analogy to the CPU's pipelining technique. The input tensor \\(X\\) sequentially passes through each processor in each time step until the processing steps finish. This allows for overlapping execution of different stages, increasing the throughput.

    Expert Parallelism, also known as Mixture of Experts (MoE), involves dynamically selecting a subset of model parameters, to reach the original performance using the entire model. Additionally, MoE models require a gating network \\(g(X)\\) to select the expert to output, which selects a subset of networks from the total \\(E\\) sub-networks, as $ \\epsilon =g(X), \\epsilon \\subseteq E $. Only the selected networks will be involved in the generation of the output \\(\\sum_{k \\in \\epsilon} f(X, W_k)\\).

    "},{"location":"docs/3-dl/efficient-train/hardware/#activition-partitioning","title":"Activition Partitioning","text":"

    In large language model training, a large memory space is needed to store the input activation of the network layers. The activation partitioning techniques, which involves efficiently distributing the activations to ensure GPU usage, is another crucial technique for efficient training. Commonly used activation partitioning techniques involve (1) sequence parallelism and (2) context parallelism. We denote the input sequence as \\(X\\), the context of this training, including the batches and environments, as \\(C\\), the processing function as \\(f(X, C, W)\\), and \\(P\\) the number of processors.

    Sequence Parallelism suggests that partitions are made by distributing computing load and activation memory across multiple GPUs along the sequence dimension of transformer layers. The input sequence \\(X\\) is divided into sub-sequences \\(X = [X_1, X_2, ..., X_P]\\). Each sub-sequence is sent into a processor with inner tensor forwarding techniques from the previous sub-sequence, denoted as \\(f(X_i, C, W_{i-1})\\).

    Context Parallelism distributes different contexts, usually including batches and environments, across multiple processors. It is useful in multi-task learning and reinforcement learning scenarios. The context \\(C\\) is divided among processors \\(C = [C_1, C_2, ..., C_P]\\), and each processor processes the context with the entire input sequence, denoted as \\(f(X, C_i, W_i)\\).

    "},{"location":"docs/3-dl/efficient-train/hardware/#multi-gpu-training","title":"Multi-GPU Training","text":"

    TODO

    Reference: \ud83e\udd17 Efficient Training on Multiple GPUs

    "},{"location":"docs/3-dl/efficient-train/parameter/","title":"Parameter","text":"

    :material-circle-edit-outline: \u7ea6 664 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    "},{"location":"docs/3-dl/efficient-train/parameter/#parameter-level","title":"Parameter-level","text":"

    Huggingface's efficient training guide discusses a number of parameters and their effect on training efficiency.

    Relevant table:

    Method/tool Improves training speed? Optimizes memory utilization? Batch size choice True True Gradient accumulation False True Gradient checkpointing False True Mixed precision training True Maybe Torch empty cache steps False True Optimizer choice True True Data preloading True False DeepSpeed Zero False True torch.compile True False Parameter-efficient Tuning (PEFT) False True"},{"location":"docs/3-dl/formal-language/","title":"Introduction to Formal Languages","text":"

    :material-circle-edit-outline: \u7ea6 4 \u4e2a\u5b57

    "},{"location":"docs/3-dl/formal-language/lecture/","title":"Lectures","text":"

    :material-circle-edit-outline: \u7ea6 411 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/3-dl/formal-language/lecture/#language-model-and-formal-language","title":"Language Model and Formal Language","text":"

    ACL tutorial 4

    big promises

    neural language models - expressiblity - formal language

    useful tools - RNN: sequntial automata - Transformer: circuits

    Definition

    a language model p is a distribution on *\\Sigma.

    Two language models are equal if p(y) = q(y) for all y on *\\Sigma.

    Any language model can be written as an autogressive one.

    tightness: for arbituary language model, the sum of all p(y) < 1 can happen. If the sum of all p(y) = 1, it is tight.

    A minimum non-tight example: To set the probablity of EOS as 0, thus the generation might never stop.

    special features of automaton: parity, hierachy detection

    simplist RNN: Elman RNN

    RNNs can be both as language models / recognizors (to classify grammatical or not)

    RNNs work like language model (TODO: photo)

    infinite state automata - with unbounded precision and computation time

    a turing machine is equivalent to a two-stack pushdown automaton. (tape = two-stacks)

    Theorem: an infinite-precision RNNs with unbounded computation time are Turing complete.

    implies: - TODO: photo - we need the hidden states to encode the stacks

    stack = neuron

    drawbacks: - numbers are in finite precision - RNNs stop within finite time

    "},{"location":"docs/3-dl/formal-language/lecture/#improvement-theoretical-model-rnns-with-bounded-computation-time-and-finite-precision","title":"improvement theoretical model: RNNS with bounded computation time and finite precision","text":"

    Theorem: Finite-precision real-time RNNs are equivalent to FSAs (without stacks, taking the training and inference procedure apart. )

    clear: - any finite-precision RNN will define a finite number of states - it can thus be represented by a FSA - an upper bound RNNs can do at most what finite-state automata can

    => Elman RNNs can simulate deterministic FSAs (any non-deterministic FSA can be => deterministic ones)

    main differences: - automaton: tabular rules - RNNs: matrix multiplications

    Any simple family of automata can efficient simulation of RNNs?

    TODO: photo

    Some FSA with |Q| states can be compressed into an RNN with O(log|Q|) hidden states.

    Takeaways:

    an RNN can end up in any rung of the NC hierarchy depending on - whether allowing unbounded processing time - whether allowing unbounded precision

    QAs:

    "},{"location":"docs/3-dl/formal-language/lecture/#how-to-turn-an-rnn-into-a-classifier","title":"How to turn an RNN into a classifier","text":"

    the missing bit:

    probablistic finite-state automata also compute probalisties

    Beyond Binary States: LSTMs and counting

    Counter machine:

    TODO: photo, position on NC hierarchy

    no model currently reach the computation ability of Turing machine. Some advanced models (e.g. ChatGPT) happen to recognize some programs.

    LSTM as a counter machine, the memory cell works as the counter. set (TODO: some parameters) as 1 and the updating function of mem cells are as the counter.

    "},{"location":"docs/3-dl/formal-language/lecture/#transformers-and-formal-language-theory-part-on-encoder","title":"Transformers and formal language theory, part on encoder","text":"

    bolean circuits, definition:

    runtime without parallelism

    definition (depth): longest path from input to output runtime with parallelism (?)

    need sth dependent on input time

    formal models: Boolean circuits

    (what is ACC here)

    formal models: first order logic (how did this appear)

    TODO: photo, NC hierarchy interact with language classes

    does circuits recognize parity?

    decisions to make: attention, softmax

    uniformity:

    dependence on - number of parameters

    unique hard attention:

    linear temporal logic

    TODO: photo on example of L=\\Sigma*ab\\Sigma*

    "},{"location":"docs/3-dl/formal-language/lecture/#adding-sequentiality-to-transformers-chain-of-thought-part-of-decoder","title":"adding sequentiality to Transformers, chain-of-thought, part of decoder","text":"

    so far, only deterministic automata

    non-deterministic

    "},{"location":"docs/3-dl/formal-language/lecture/#takeaways","title":"takeaways","text":"

    QAs - the Turing machines can move head left-to-right and right-to-left. if taking that into account, we might

    Reference

    "},{"location":"docs/3-dl/survey/","title":"Misc Survey","text":"

    :material-circle-edit-outline: \u7ea6 32 \u4e2a\u5b57

    If I have written about some topics that I don't read anymore, they will be thrown into this section.

    "},{"location":"docs/3-dl/survey/#contents","title":"Contents","text":""},{"location":"docs/3-dl/survey/explainable-nlp/","title":"Explainable NLP Survey","text":"

    :material-circle-edit-outline: \u7ea6 1084 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    TODO

    "},{"location":"docs/3-dl/survey/explainable-nlp/#survey","title":"Survey","text":""},{"location":"docs/3-dl/survey/explainable-nlp/#a-survey-of-the-state-of-explainable-ai-for-natural-language-processing","title":"A Survey of the State of Explainable AI for Natural Language Processing","text":"

    This survey thoroughly explains the state of explainable NLP. The Introduction discusses two distinguishing criteria for explanability models (1) whether the explanation is for each prediction individually or the model\u2019s prediction process as a whole, and (2) determining whether generating the explanation requires post-processing or not. In Categorization of Explanations, this paper categorizes the explanation models into local (provides information or justification for the model's prediction on a specific input) vs. global (provides similar justification by revealing how the model's predictive process works, independently of any particular input), and self-explaining (also directly interpretable, generates the explanation at the same time as the prediction, e.g. decision trees, rule-based models, and feature saliency models like attention models) vs. post-hoc (an additional operation is performed after the predictions are made). This section also states that the different categories of models can overlap. In section Aspects of Explanations, this paper introduces three types of explanation techniques: (1) explainability techniques (feature importance, surrogate model, example-driven, provenance-based, declarative induction), (2) operations to enable explainability (first-derivation saliency, layer-wise relevance propagation, and input perturbations, attention, LSTM gating signals, explainability-aware architecture design) and (3) visualization techniques (saliency, raw declarative representations, natural language explanation). The section Evaluation introduces several evaluating metrices.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#opinion-papers","title":"Opinion Papers","text":""},{"location":"docs/3-dl/survey/explainable-nlp/#climbing-towards-nlu-on-meaning-form-and-understanding-in-the-age-of-data-2020","title":"Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (2020)","text":"

    This paper argues that the modern NLP models trained on form has no abilities in understanding natural languages based on both the science and philosophy theories. It is structured as follows. In section Large LMs: Hype and analysis, this paper samples example pieces from news and academic literature that exaggerate the understanding abilities in using words including \"understand\"\"comprehension\"\"recall factual knowledge\", and argues that the current LMs have the ability no other than learning the surface linguistic forms of language rather than understanding them. In section What is meaning?, this paper clarifies the meaning of language as the communicative intent that a parole intends to express, and distinguishes the concept \"meaning\" and \"truth\" as the truth is the meaning that is \"grounded\" to the real world. In section The octopus test, this paper detailedly tells a thought experiment of a super intelligent octopus who can mimic the human response by never receiving the knowledge of the grounded real world of the language meaning, by which this paper argues that it might be that how the language receiver decodes the communicative intends affects the conventional meaning of language. In section More constrained thought experiments, two more thought experiments are provided, training the JAVA and training the English LMs without providing the executing methods the communicative intends, and the paper argues that such tasks are impossible. In section Human language acquisition, this paper supports its idea by providing the example of human children's acquiring knowledge is not only grounded on the world image, but also in the interaction with other people. In section Distributional semantics, this paper argues that in NLP, two methods based on the instincts above are training distributional models on corpora augmented with perceptual data, and looking to interaction data (according to Wittgenstein's \"meaning in use\").

    "},{"location":"docs/3-dl/survey/explainable-nlp/#information-theory-based-compositional-distributional-semantics-2021","title":"Information Theory-based Compositional Distributional Semantics (2021)","text":"

    According to the abstract, the contribution of this paper can be concluded as proposing the notion of Information Theory-based Compositional Distributional Semantics (ICDS): (i) We first establish formal properties for embedding, composition, and similarity functions based on Shannon\u2019s Information Theory; (ii) we analyze the existing approaches under this prism, checking whether or not they comply with the established desirable properties; (iii) we propose two parameterizable composition and similarity functions that generalize traditional approaches while fulfilling the formal properties; and finally (iv) we perform an empirical study on several textual similarity datasets that include sentences with a high and low lexical overlap, and on the similarity between words and their description. In section Introduction, the author introduces Frege's concepts of compositionality and contextuality, which respectively refers to that \"the meaning of the whole is a function of the meaning of its parts and the syntactic way in which they are combined\", and that \"the meaning of words and utterances is determined by their context\". This section also introduces the main concern of lacking systematicity by the linguists to the NLP, where systematicity is defined as \"A system is said to exhibit systematicity if, whenever it can process a sentence, it can process systematic variants, where systematic variation is understood in terms of permuting constituents or (more strongly) substituting constituents of the same grammatical category.\" Thus, this section introduces that this paper aims to propose a novel system called Information Theory-based Compositional Distributional Semantics (ICDS). In section Related Work, the author introduces a set of properties in selective proper text representation paradigms which includes \"systematicity\", \"usage context\", \"continuity\", and \"information measurbility\", and introduces a series of previous work under this standard. In section Theoretical Framework, this paper first establishes a geometric interpretation of ICDS, that \"The direction of an embedding represents the pragmatic meaning, and the vector norm of embedding represents how much information the literal utterance provides about its meaning in the pragmatic context\", and then proposes the concept of ICDS as \"there are minimal linguistic units whose semantics are determined by their use and whose amount of information is determined by their specificity. On the other hand, the systematicity of language can be captured by compositional mechanisms while preserving the amount of information of the composite utterance\". Section Formal Definition and Properties formally defines the concepts involved in ICDS, where (\\(\\pi\\),\\(\\delta\\), \\(\\bigodot\\)) stand for \"embedding\", \"semantic similarity\", and \"composition function\" respectively. This section points out the embedding function properties (information measurability and angular isometry), composition function properties (composition neutral element, composition norm monotonicity, and sensitivity to stricture), and similarity function properties (angular distance simialrity monotonicity, orthogonal embedding similarity monotonicity, and equidistant embedding simialrity monotonicity). In section Function Analysis and Generalization, this research evaluates several current embedding vector with the proposed framework, while in section Experiment, the semantic representation abilities of several prevailing LLMs including BERT and GPT are evaluated.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#contrastive-explanations-for-model-interpretability-2021","title":"Contrastive Explanations for Model Interpretability (2021)","text":"

    This paper proposes a data augmentation method to generate counterexample on the bases of NLI datasets, and proves that by training on patterns \"why A rather than B\" with contrastive learning methods, the model performs better than the previous NLI baselines.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#using-counterfactual-contrast-to-improve-compositional-generalization-for-multi-step-quantitative-reasoning-2023","title":"Using counterfactual contrast to improve compositional generalization for multi-step quantitative reasoning (2023)","text":""},{"location":"docs/3-dl/survey/llama3_405b/","title":"Llama-3.1-405B \u6280\u672f\u62a5\u544a","text":"

    :material-circle-edit-outline: \u7ea6 3436 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 11 \u5206\u949f

    "},{"location":"docs/3-dl/survey/llama3_405b/#_1","title":"\u7b80\u4ecb","text":"

    \u8fd9\u7bc7\u6280\u672f\u62a5\u544a\u662f MetaAI \u5728 2024 \u5e74 7 \u6708 23 \u65e5\u968f 405B \u6a21\u578b\u53d1\u5e03\u7684\u3002\u5148\u524d Llama 3 \u7cfb\u5217\u5df2\u7ecf\u53d1\u5e03\u8fc7 8B \u548c 70B \u4e24\u4e2a\u5927\u5c0f\u7684\u6a21\u578b\uff0c\u672c\u6b21\u53d1\u5e03\u7684\u6a21\u578b\u5728\u89c4\u6a21\u4e0a\u589e\u91cf\u975e\u5e38\u5927\u3002\u5c3d\u7ba1\u89c4\u6a21\u7684\u63d0\u5347\u4f7f\u5176\u6210\u4e3a\u6700\u5f3a\u7684\u5f00\u6e90\u5927\u8bed\u8a00\u5bf9\u8bdd\u6a21\u578b\uff08\u5728\u672c\u6587\u5199\u6210\u65f6\uff0c2024 \u5e74 8 \u6708 1 \u65e5\uff0c\u6839\u636e\u516c\u8ba4\u6bd4\u8f83\u53ef\u4fe1\u7684\u8bc4\u4ef7\u6307\u6807 Chatbot Arena\uff0c\u622a\u56fe\u5982\u4e0b\uff09\uff0c\u4f46\u672c\u6587\u5728 benchmark \u4e0a\u5c55\u73b0\u51fa\u6765\u7684\u6027\u80fd\u6570\u503c\uff0c\u76f8\u6bd4 70B \u63d0\u5347\u4e0d\u5927\uff0c\u666e\u904d\u5728 1-3 \u4e2a\u70b9\u3002\u4e14\u8003\u8651\u5230\u6a21\u578b\u5360\u7528\u7684 GPU \u6210\u672c\uff0c\u5bf9\u4e8e\u666e\u901a\u4eba\u65e5\u5e38\u7528\u9014\uff0c405B \u53ef\u80fd\u6027\u4ef7\u6bd4\u4e0d\u5982 70B \u9ad8\u3002

    \u62a5\u544a\u7684\u539f\u6587\u89c1\u6587\u672b ArXiv \u94fe\u63a5\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_2","title":"\u6587\u7ae0\u7ed3\u6784","text":"

    Llama-3.1-405B \u6709\u6587\u5b57\u3001\u89c6\u9891/\u56fe\u50cf\u548c\u8bed\u97f3\u7b49\u591a\u4e2a\u6a21\u6001\u7684\u80fd\u529b\u3002\u672c\u6587\u7684\u67b6\u6784\u5206\u4e3a\u591a\u4e2a\u7ae0\u8282\uff0c\u5148\u8bb2\u6587\u5b57\u80fd\u529b\u7684\u9884\u8bad\u7ec3\uff08pre-training\uff09\u3001\u5fae\u8c03\uff08post-training\uff09\u3001\u5b9a\u6027\u80fd\u529b\u3001\u5b9a\u91cf\u80fd\u529b\u3001\u5c40\u9650\u6027\u7b49\uff0c\u518d\u8bb2\u89c6\u9891/\u56fe\u50cf\u548c\u8bed\u97f3\u7684\u8bad\u7ec3\u8fc7\u7a0b\u548c\u6027\u80fd\u6570\u503c\u3002

    \u6280\u672f\u62a5\u544a\u539f\u6587\u7684\u7ed3\u6784\u5982\u4e0b\uff1a

    "},{"location":"docs/3-dl/survey/llama3_405b/#n","title":"n \u53e5\u8bdd\u4eae\u70b9","text":""},{"location":"docs/3-dl/survey/llama3_405b/#_3","title":"\u6027\u80fd","text":""},{"location":"docs/3-dl/survey/llama3_405b/#benchmarks","title":"Benchmarks \u9884\u89c8","text":"

    \u5728\u591a\u4e2a benchmark \u4e0a\u6d4b\u8bd5 Llama-3.1-405B \u7684\u6027\u80fd\u3002\u6b64\u5904\u60f3\u5bf9\u672c\u6587\u7528\u5230\u7684 benchmark \u8fdb\u884c\u4e00\u70b9\u6982\u8ff0\u3002

    pre-train \u9636\u6bb5\u7ed3\u675f\u540e\uff0c\u7528\u4e8e\u6d4b\u8bd5\u7684 benchmark \u6709\uff1a

    post-train \u9636\u6bb5\u7ed3\u675f\u65f6\uff0c\u6d4b\u8bd5\u7528\u7684 benchmark \u5982\u4e0b\uff1a

    "},{"location":"docs/3-dl/survey/llama3_405b/#_4","title":"\u6027\u80fd\u6570\u503c","text":"

    \u5728\u8fd9\u4e9b benchmark \u4e0a\u6d4b\u8bd5\u65f6\uff0c\u7531\u4e8e\u5355\u6b21\u7ed3\u679c\u4e0d\u7a33\u5b9a\uff08\u5148\u524d\u6211\u4eec\u666e\u904d\u7684\u505a\u6cd5\u5e38\u5e38\u662f\u591a\u6b21\u7ed3\u679c\u6c42\u5e73\u5747\u503c\u7b49\uff09\uff0c\u672c\u6280\u672f\u62a5\u544a\u91c7\u7528 Maddan et al.(2024) \u63d0\u51fa\u7684 95% confidence interval (CIs) \u65b9\u6cd5\uff0c\u901a\u8fc7\u8ba1\u7b97\u7f6e\u4fe1\u533a\u95f4\u6765\u4f30\u8ba1\u65b9\u5dee\u3002\u8fd9\u4e2a\u65b9\u6cd5\u5047\u8bbe\u6d4b\u8bd5\u5f97\u5230\u7684\u6570\u503c\u670d\u4ece\u6b63\u6001\u5206\u5e03\uff0c\u5982\u679c\u5355\u6b21\u6d4b\u8bd5\u5f97\u5230\u7684\u6570\u503c\u4e3a S\uff0c\u6570\u636e\u96c6\u5927\u5c0f\u4e3a N\uff0c\u90a3\u4e48\u7f6e\u4fe1\u533a\u95f4\u4e3a

    \\[ CI(S) = 1.96 \\times \\sqrt{\\frac{S \\times (1 - S)}{N}} \\]

    \u7531\u7f6e\u4fe1\u533a\u95f4\u5bbd\u5ea6\u9664\u4ee5\u4e34\u754c\u503c 1.96 \u53ef\u4ee5\u5f97\u5230\u6807\u51c6\u5dee -> \u65b9\u5dee\u3002

    post-train \u5b8c\u6210\u540e\uff0c\u7ed3\u679c\u7684\u603b\u8868\u5982\u4e0b

    \u53ef\u4ee5\u770b\u51fa\u5176\u5b9e Llama-3.1-405B \u5728 70B \u4e0a\u6709\u63d0\u5347\uff0c\u4f46\u76f8\u6bd4\u53c2\u6570\u91cf\u7684\u63d0\u5347\uff0c\u6027\u80fd\u63d0\u5347\u5e76\u4e0d\u662f\u5f88\u5927\uff0c\u5f88\u591a benchmark \u4e0a\u90fd\u5728 2-3 \u4e2a\u70b9\u3002\u8003\u8651\u5230\u524d\u9762\u63d0\u5230\u53ef\u80fd 405B \u53ef\u80fd\u8bad\u7ec3\u4e86 MoE \u548c dense Transformer \u4e24\u4e2a\u6a21\u578b\u4f46\u662f\u540e\u8005\u6ca1\u8bad\u6210\u529f\uff0c\u4e0d\u77e5\u9053\u53d1\u5e03\u7248 405B \u6027\u80fd\u6bd4\u9884\u671f\u4f4e\u662f\u4e0d\u662f\u4e5f\u662f\u8fd9\u4e2a\u539f\u56e0\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_5","title":"\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/llama3_405b/#pre-train","title":"Pre-train \u9884\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/llama3_405b/#_6","title":"\u6574\u4f53\u95ee\u9898","text":"

    \u9884\u8bad\u7ec3\u7275\u626f\u5230\u7684\u95ee\u9898\u6709\u56db\u5757\uff1a

    1. \u600e\u4e48\u628a\u6bd4\u8f83\u5927\u7684\u6570\u636e\u96c6\u5f04\u51fa\u6765
    2. \u600e\u4e48\u628a scaling law \u4f53\u73b0\u51fa\u6765\uff0c\u4f1a\u51b3\u5b9a\u7528\u591a\u5c11\u6570\u636e\u548c\u6a21\u578b\u53c2\u6570\u91cf\u662f\u591a\u5c11
    3. \u600e\u4e48\u6709\u6548\u5728 pre-train \u9636\u6bb5\u8bad\u7ec3\u8fd9\u4e48\u591a\u53c2\u6570
    4. \u600e\u4e48\u505a pre-train

    \u9884\u8bad\u7ec3\u5927\u7ea6\u7528\u4e86\u534a\u5e74\uff0c\u8c03\u53c2\u662f\u5e74\u521d\u5f00\u59cb\u7684\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_7","title":"\u6570\u636e\u6e05\u6d17","text":"

    \u7528\u5230\u7684\u6570\u636e\u662f\u5728\u4e92\u8054\u7f51\u4e0a common crawl \u4e0b\u6765\u7684\u622a\u81f3 2023 \u5e74\u7684\u6570\u636e\uff0c\u4e4b\u540e\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3002\u6570\u636e\u7684\u9009\u7528\u4e00\u822c\u5c5e\u4e8e\u516c\u53f8\u79d8\u5bc6\uff0c\u4e0d\u80fd\u8bb2\u592a\u6e05\u695a\u3002\u6e05\u6d17\u7684\u6b65\u9aa4\u867d\u7136\u4e5f\u6ca1\u6709\u8bb2\uff0c\u4e0d\u8fc7\u5927\u81f4\u9075\u5faa\uff081\uff09\u627e\u4e00\u6279\u6570\u636e\u89c2\u5bdf\u5927\u591a\u662f\u5982\u4f55\u810f\u7684 -> \uff082\uff09\u5199\u811a\u672c\u6d17\u6389\u8fd9\u79cd\u7279\u70b9 -> \uff083\uff09\u8fd4\u56de\uff081\uff09\u5faa\u73af\u3002\u6709\u660e\u786e\u8bb2\u7684\u6570\u636e\u6e05\u6d17\u539f\u5219/\u7c7b\u522b\u6709\u4ee5\u4e0b\u51e0\u6761\uff1a

    1. \u6d17\u6389 personally identifiable information (PII) \u5373\u4e00\u4e9b\u4e2a\u4eba\u59d3\u540d\u3001\u90ae\u7bb1\u3001url\uff0c\u548c\u6210\u4eba\u5185\u5bb9\uff1b\u4f46\u674e\u6c90\u8868\u793a\u8fd9\u4e24\u79cd\u4e1c\u897f\u4e5f\u4e0d\u4f1a\u6d17\u592a\u5e72\u51c0\uff0c\u524d\u8005\u6d17\u592a\u5e72\u51c0\u4e86\u53ef\u80fd\u4f1a\u4f7f\u8bad\u7ec3\u6587\u6863\u672c\u8eab\u7684\u610f\u601d\u6709\u53d8\u5316\uff0c\u540e\u8005\u592a\u5e72\u51c0\u4e86\u53ef\u80fd\u6a21\u578b\u5728\u4e00\u4e9b\u6253\u64e6\u8fb9\u7403\u5e94\u7528\u4e0a\u6548\u679c\u4e0d\u592a\u597d\uff0c\u6240\u4ee5\u505a\u6cd5\u53ef\u80fd\u662f\u5bf9\u6587\u6863\u9274\u5b9a\u4e00\u4e2a\u767e\u5206\u6bd4\uff0c\u5982\u679c\u5176\u4e2d\u9700\u8981\u6d17\u6389\u7684\u5185\u5bb9\u5360\u6bd4\u592a\u591a\uff0c\u5219\u4e0d\u8981\u4e86\u3002

    2. \u5728\u7ed3\u6784\u5316\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\uff0c\u6bd4\u5982\u53bb\u6389 html \u548c markdown \u7684\u6807\u7b7e\uff0c\u53ea\u4fdd\u7559\u6587\u672c\u3002

    3. \u5206\u522b\u505a\u4e86 url\u3001\u6587\u6863\u548c\u884c\u7ea7\u522b\u7684\u53bb\u91cd\u3002\u5728 url \u7ea7\u522b\uff0c\u4fdd\u7559\u4e86\u6240\u6709\u9875\u9762\u6700\u65b0\u7684\u7248\u672c\uff1b\u5728\u6587\u6863\u7ea7\u522b\uff0c\u4f7f\u7528\u4e86 MinHash \u7b97\u6cd5\uff1b\u5728\u884c\u7ea7\u522b\uff0c\u5c06\u6bcf 30M \u91cc\u8d85\u8fc7 6 \u6b21\u7684\u884c\u53bb\u9664\u6389\u4e86\uff0c\u8fd9\u663e\u8457\u63d0\u5347\u4e86\u8bc4\u6d4b\u8868\u73b0\u3002

    \u5176\u4e2d MinHash \u7b97\u6cd5\u662f\u4e00\u79cd\u5feb\u901f\u6bd4\u8f83\u4e24\u4e2a\u96c6\u5408\u76f8\u4f3c\u5ea6\u7684\u7b97\u6cd5\uff0c\u53ef\u4ee5\u901a\u8fc7\u6bd4\u8f83\u5355\u8bcd\u76f8\u4f3c\u5ea6\u6765\u5b9e\u73b0\u6587\u672c\u805a\u7c7b\u3002\u5b83\u9884\u8bbe\u4e24\u4e2a\u6587\u672c\u7684\u76f8\u4f3c\u5ea6\u662f\u901a\u8fc7\u8ba1\u7b97\u8bcd\u96c6 A \u548c\u8bcd\u96c6 B \u7684 Jaccard \u76f8\u4f3c\u5ea6 $ J(A, B) = \\frac{| A \\cap B |}{| A \\cup B |} $\u3002\u76ee\u7684\u662f\u4e0d\u9700\u8981\u5b9e\u9645\u8ba1\u7b97\u4e24\u4e2a\u96c6\u5408\u7684\u4ea4\u548c\u5e76\u3002\u5177\u4f53\u6211\u8ba4\u4e3a\u8fd9\u7bc7\u5e16\u5b50\u8bb2\u5f97\u5f88\u6e05\u6670 LSH\u7cfb\u52172\uff1aMinHash&LSH\u2014\u2014\u6587\u6863\uff08\u96c6\u5408\uff09\u76f8\u4f3c\u6027\u3002

    1. \u542f\u53d1\u5f0f\u8fc7\u6ee4\uff0c\u8fc7\u6ee4\u4e86\u4ee5\u4e0b\u4e09\u79cd\u5185\u5bb9\uff1a\u7528 n-gram \u8fc7\u6ee4\u4e86\u4e00\u4e9b\u884c\u91cd\u590d\u6ca1\u53bb\u6389\u7684\u5185\u5bb9\uff0c\u7528\u810f\u8bcd\u8868\u8fc7\u6ee4\u810f\u8bcd\uff0c\u7528 K-L \u6563\u5ea6\u8fc7\u6ee4\u5206\u5e03\u592a\u7279\u6b8a\u7684 token\u3002

    2. \u4ee3\u7801\u548c\u63a8\u7406\u6570\u636e\u3002\u4ece\u722c\u7684\u6570\u636e\u91cc\uff0c\u7528 fasttext \u6216 Llama 2 \u6765\u5224\u522b\u51fa\u4e00\u4e9b\u4ee3\u7801\u3001\u6570\u5b66\u7b49 STEM \u6587\u7ae0\u3002\u8fd9\u4e9b\u6587\u7ae0\u8fdb\u4e00\u6b65\u7528 DistlRoberta \u9009\u51fa\u4e86\u9ad8\u8d28\u91cf\u7684\u8bad\u7ec3\u6570\u636e\u3002

    3. \u591a\u8bed\u8a00\u6570\u636e\u3002\u7528 fasttext \u4ece\u722c\u4e0b\u6765\u7684\u6570\u636e\u4e2d\u8bc6\u522b\u51fa\u4e86 176 \u79cd\u8bed\u8a00\uff0c\u8fd9\u4e9b\u591a\u8bed\u8a00\u6570\u636e\u4e5f\u8fdb\u884c\u4e86\u53bb\u91cd\u3001\u7b5b\u9009\u7b49\u6e05\u6d17\u6b65\u9aa4\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_8","title":"\u6570\u636e\u6df7\u5408","text":"

    \u5982\u4f55\u51b3\u5b9a\u8bad\u7ec3\u6570\u636e\u7684\u5206\u5e03\u6bd4\u4f8b\uff1a

    \u8bad\u7ec3\u6570\u636e\u6df7\u5408\u6bd4\u4f8b\u7684\u603b\u7ed3\uff1a

    \u53ef\u89c1\u591a\u8bed\u8a00\u6570\u636e\u4e0d\u9700\u8981\u592a\u591a\uff0c\u4e3b\u8981\u77e5\u8bc6\u7528\u82f1\u8bed\u5b66\u8fc7\u540e\u53ef\u4ee5\u6cdb\u5316\u5230\u5176\u5b83\u8bed\u8a00\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_9","title":"\u9000\u706b","text":"

    \u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u968f\u7740\u6a21\u578b\u9010\u6e10\u63a5\u8fd1\u8bad\u7ec3\u5b8c\u6210\uff0c\u9010\u6e10\u964d\u4f4e\u5bf9\u65b0\u6570\u636e\u7684\u6743\u91cd\uff0c\u53ef\u4ee5\u8ba9\u6a21\u578b\u66f4\u52a0\u7a33\u5b9a\u5730\u9002\u5e94\u65b0\u6570\u636e\uff0c\u800c\u4e0d\u4f1a\u5bfc\u81f4\u6a21\u578b\u53c2\u6570\u5267\u70c8\u6ce2\u52a8\u3002\u968f\u7740\u5b66\u4e60\u7387\u964d\u4f4e\uff0c\u53ea\u6709\u9ad8\u8d28\u91cf\u7684\u6570\u636e\u624d\u80fd\u663e\u8457\u63d0\u5347\u6a21\u578b\u7684\u6027\u80fd\u3002\u56e0\u6b64\u9000\u706b\u63d0\u4f9b\u4e86\u4e00\u79cd\u66f4\u6709\u6548\u7684\u65b9\u6cd5\u6765\u8bc4\u4f30\u5c0f\u578b\u7279\u5b9a\u9886\u57df\u6570\u636e\u96c6\u7684\u4ef7\u503c\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#model-architecture","title":"Model Architecture \u6a21\u578b\u67b6\u6784","text":"

    \u6027\u80fd\u7684\u63d0\u5347\u4e3b\u8981\u6765\u6e90\u4e8e\u6570\u636e\u8d28\u91cf\u7684\u63d0\u9ad8\u548c\u6a21\u578b\u66f4\u5927\u4e86\u3002

    \u6a21\u578b\u4e0e\u4e4b\u524d\u7684\u533a\u522b\uff1agroup query attention (GQA) \u53ef\u4ee5\u5e26\u6765\u5185\u5b58\u7684\u8282\u7701\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#post-train","title":"Post-train \u5fae\u8c03","text":"

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_10","title":"\u591a\u6a21\u6001\u80fd\u529b","text":"

    \u89c6\u9891/\u56fe\u50cf\u80fd\u529b\u7684\u8bad\u7ec3\u5728\u6587\u5b57\u80fd\u529b\u8bad\u7ec3\u7ed3\u675f\u4e4b\u540e\uff0c\u6709\u989d\u5916\u7684 encoder \u548c decoder\uff0c\u8bad\u7ec3\u65f6\u5c06\u6587\u5b57\u80fd\u529b\u7684\u6743\u91cd\u51bb\u7ed3\uff0c\u53ea\u8c03\u5176\u5b83\u6a21\u6001\u7684\u53c2\u6570\u3002

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_11","title":"\u76f8\u5173\u5de5\u4f5c","text":"

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_12","title":"\u53c2\u8003\u8d44\u6599","text":""},{"location":"docs/3-dl/survey/math-word-problem/","title":"Math Word Problem Survey","text":"

    :material-circle-edit-outline: \u7ea6 1080 \u4e2a\u5b57 :fontawesome-solid-code: 15 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/3-dl/survey/math-word-problem/#an-introduction-to-math-word-problems","title":"An Introduction to Math Word Problems","text":"

    The math word problem (MWP) aims to solve simple primary school math problems (in plain-text format) with deep learning methods. The problems usually consists of numbers no larger than 100 and only 5 operators (+, -, *, / and =). This blog is structured as follows. The Dataset part will introduce two main types, one indicating the locations of variables, and the other simply embedding the math formula within the natural language texts. The Methods parts will introduce several prevailing methods in solving this task, including both the models and workflows that improves the accuracy of models.

    "},{"location":"docs/3-dl/survey/math-word-problem/#surveys","title":"Surveys","text":""},{"location":"docs/3-dl/survey/math-word-problem/#the-gap-of-semantic-parsing-a-survey-on-automatic-math-word-problem-solvers-2019","title":"The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers (2019)","text":"

    This survey provides a comprehensive introduction to the MWP datasets and methods prior to 2019. This survey defines three stages of MWP solving, the Rule-based matching stage (1960-2010), Semantic parsing, feature engineering and statistical learning stage (2011-2017), and Deep learning and reinforcement learning stage (2017-2019).

    "},{"location":"docs/3-dl/survey/math-word-problem/#towards-tractable-mathematical-reasoning-challenges-strategies-and-opportunities-for-solving-math-word-problems-2021","title":"Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problems (2021)","text":"

    This survey introduces the contemporary MWP datasets til 2021, and methods including rule-based, and neural network encoder-decoder structures. Specifically, this paper concludes three strategies for math word solving, (i) direct answer generation, (ii) expression tree generation for inferring answers, and (iii) template retrieval for answer computation. Considering the type of problem solving method, this paper concludes two classes. The first class is non-neural approaches (rule-base or pattern matching approaches, semantic parsing, and statistical machine learning approaches), within which a particular strategy of applying domain knowledge in classifying the problems (e.g. into change, part-whole and compare classes). The second class is neural approaches, including intuitions of (i) predicting the answer directly (ii) generating a set of equations or mathematical expressions and inferring answers from the by executing them (iii) retrieving the templates from a pool of templates derived from training data and augmenting numerical quantities to compute the answer. These neural approaches generally follow encoder-decoder architectures, which fall in four types (i) seq-to-seq (ii) Transformer-to-tree (iii) seq-to-tree (iv) graph-to-tree. Among the four methods, the tree-structured decoder attend both parents and siblings to generate the next token, while the bottom-up representation of sub-tree of a sibling could further help to derive better outcomes. The graph-based encoder aims to learn different types of relationships among the constituents of MWPs. This section also mentions that \"Data augmentation is a popular preprocessing technique to increase the size of training data\" (reverse operation-based augmentation techniques, different traversal orders of expression trees, and weak supervision). In section Math Reasoning in Neural Approaches, this paper mentions several further topics under math reasoning, interpretability and explainability, infusing explicit and definitive knowledge, and reinforcement learning.

    "},{"location":"docs/3-dl/survey/math-word-problem/#datasets","title":"Datasets","text":""},{"location":"docs/3-dl/survey/math-word-problem/#mawps-a-math-word-problem-repository-2016","title":"MAWPS: A Math Word Problem Repository (2016)","text":"

    sroy9/mawps: Code for MAWPS: A Math Word Problem Repository (github.com) The data format is as follows. 

    [\n{\n\"iIndex\": 1,\n\"sQuestion\": \"Joan found 70.0 seashells on the beach. She gave Sam some of her seashells . She has 27.0 seashells . How many seashells did she give to Sam ?\",\n\"lEquations\": [\"X=(70.0-27.0)\"],\n\"lSolutions\": [43.0]\n},\n]\n

    "},{"location":"docs/3-dl/survey/math-word-problem/#math23k-deep-neural-solver-for-math-word-problems-2017","title":"Math23k: Deep Neural Solver for Math Word Problems (2017)","text":"

    Deep Neural Solver for Math Word Problems (aclanthology.org) This dataset is in Chinese. 

    Problem: Dan have 2 pens, Jessica have 4 pens. How many pens do they have in total ? \nEquation: x = 4+2 \nSolution: 6\n

    "},{"location":"docs/3-dl/survey/math-word-problem/#mathqa-2019","title":"MathQA (2019)","text":"

    MathQA-Dataset (math-qa.github.io) This paper proposes a math dataset which enhances the AQuA dataset by providing fully-specified operational programs. This dataset has a diverse range of operators.

    "},{"location":"docs/3-dl/survey/math-word-problem/#math-2021","title":"MATH (2021)","text":"

    arxiv.org/pdf/2103.03874.pdf MATH is a LaTeX format dataset, with its answer highlighted in a square block.

    "},{"location":"docs/3-dl/survey/math-word-problem/#svmap","title":"SVMAP","text":"

    arkilpatel/SVAMP: NAACL 2021: Are NLP Models really able to Solve Simple Math Word Problems? (github.com) This dataset does not distinguish the data with the texts. An example data is as follows.

    "},{"location":"docs/3-dl/survey/math-word-problem/#gsm8k-grade-school-math-2021","title":"GSM8k: grade school math (2021)","text":"

    Collected by OpenAI, this dataset consists of math problems in natural language descriptions, with the math formulas highlighted with special notes.The numbers are not explicitly highlighted with special symbols. Several examples of the data format are as follows.

    "},{"location":"docs/3-dl/survey/math-word-problem/#draw","title":"DRAW","text":"

    Providing 1000 grounded word problems.

    "},{"location":"docs/3-dl/survey/math-word-problem/#algebra","title":"Algebra","text":""},{"location":"docs/3-dl/survey/math-word-problem/#asdiv","title":"AsDiv","text":""},{"location":"docs/3-dl/survey/math-word-problem/#multiarith","title":"MultiArith","text":""},{"location":"docs/3-dl/survey/math-word-problem/#singleeq","title":"SingleEq","text":""},{"location":"docs/3-dl/survey/math-word-problem/#methods","title":"Methods","text":""},{"location":"docs/3-dl/survey/math-word-problem/#models","title":"Models","text":"

    Prior to 2017, the models for solving MWP are mainly concerning with neural networks. After Transformer has been released in 2017, attention-based models have been thriving. The novel models based on Transformer are mainly modifying the encoder and decoder structures, among which there are graph-encoder and tree-decoders.

    "},{"location":"docs/3-dl/survey/math-word-problem/#graph-to-tree-learning-for-solving-math-word-problems-2020","title":"Graph-to-Tree Learning for Solving Math Word Problems (2020)","text":"

    This paper proposes a attention-based model Graph2Tree, consisting of graph-based encoder and a tree-based decoder. The math word problems are constructed into Quantity Comparison Graph.

    "},{"location":"docs/3-dl/survey/math-word-problem/#math-word-problem-solving-with-explicit-numerical-values-2021","title":"Math Word Problem Solving with Explicit Numerical Values (2021)","text":"

    A novel approach called NumS2T is proposed to solve MWP. NumS2T is constructed with (a) an attention-based seq2seq model to generate its math expressions, (b) a numerical value encoder to obtain the number-aware problem state which are then concatenated with the problem hidden state in (a) to obtain number-aware problem representation, and (c) a numerical properties prediction mechanism for comparing the paired numerical values, determining the category of each numeral and measuring whether they should appear in the target expression.!

    "},{"location":"docs/3-dl/survey/math-word-problem/#learning-to-reason-deductively-math-word-problem-solving-as-complex-relation-extraction-2022","title":"Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction (2022)","text":"

    This paper proposes a novel approach

    "},{"location":"docs/3-dl/survey/math-word-problem/#workflows","title":"Workflows","text":"

    Most of the recent works follow the method of knowledge distilling, which means to generate high quality data with LLMs and then train a small model with the generated (and sometimes then augmented) data. The workflow of such tasks mainly assembles that of the following paper.

    "},{"location":"docs/3-dl/survey/math-word-problem/#large-language-models-are-reasoning-teachers","title":"Large Language Models Are Reasoning Teachers","text":"

    This paper proposes a knowledge distilling method in solving math reasoning problems.

    "},{"location":"docs/3-dl/survey/math-word-problem/#solving-math-word-problems-via-cooperative-reasoning-induced-language-models-acl-2023","title":"Solving Math Word Problems via Cooperative Reasoning induced Language Models (ACL 2023)","text":"

    This paper develops a cooperative reasoning-induced PLM for solving MWPs called Cooperative Reasoning (CoRe), with a generator to generate reasoning paths and a verifier to supervise the evaluation.

    "},{"location":"docs/3-dl/survey/math-word-problem/#scaling-relationship-on-learning-mathematical-reasoning-with-large-language-models-2023","title":"Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023)","text":"

    This paper mainly focus on the following two questions: (i) Which is a better performance indicator of LLMs? (pre-training loss amount/model size) (ii) How to improve small model's performance by data augmentation? To answer the second question, this paper proposes a novel methods in data augmentation in the LLM data generation step which is called Rejection Finetuning (RFT). The algorithm of sampling data in RFT mainly adopts the thought of rejection sampling, which is expressed in the following pseudo-code. This paper assumes such an algorithm will yield as many as possible diverse reasoning paths. The workflow of the RFT method is illustrated as follows, where the SFT stands for supervised finetuning. With the novel method RFT, small models such as Llama-7b yields an accuracy of at most 49.7% on GSM8k, 14% higher than the previous SOTA method SFT.

    "},{"location":"docs/3-dl/survey/math-word-problem/#pal","title":"PAL","text":"

    This work is a prompt engineering work. 

    Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now? \nA: Roger started with 5 tennis balls. tennis_balls = 5 2 cans of 3 tennis balls each is bought_balls = 2 * 3 tennis balls. The answer is answer = tennis_balls + bought_balls \nQ: The bakers at the Beverly Hills Bakery baked 200 loaves of bread on Monday morning. They sold 93 loaves in the morning and 39 loaves in the afternoon. A grocery store returned 6 unsold loaves. How many loaves of bread did they have left?\n

    A: The bakers started with 200 loaves loaves_baked = 200 They sold 93 in the morning and 39 in the afternoon loaves_sold_morning = 93 loaves_sold_afternoon = 39 The grocery store returned 6 loaves. loaves_returned = 6 The answer is answer = loaves_baked - loaves_sold_morning - loaves_sold_afternoon + loaves_returned\n
    "},{"location":"docs/3-dl/survey/math-word-problem/#preview","title":"Preview","text":""},{"location":"docs/3-dl/survey/multilingual/","title":"Multilingual Task Survey","text":"

    :material-circle-edit-outline: \u7ea6 768 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/3-dl/survey/multilingual/#introduction","title":"Introduction","text":"

    \u591a\u8bed\u8a00\u6a21\u578b multilingual models \u5c31\u662f\u80fd\u89e3\u51b3\u591a\u8bed\u8a00\u4efb\u52a1\u7684\u6a21\u578b\u3002\u5728\u4e3b\u6d41\u8bad\u7ec3\u6570\u636e\u662f\u82f1\u8bed\u3001\u7a00\u6709\u8bed\u8a00\u6570\u636e\u7a00\u7f3a\u7684\u80cc\u666f\u4e0b\uff0c\u5982\u4f55\u5c06\u6a21\u578b\u80fd\u529b\u6cdb\u5316\u5230\u7a00\u6709\u8bed\u8a00\u662f\u91cd\u8981\u7684\u95ee\u9898\u3002\u9664\u4e86\u6700\u8fd1\u7684\u5927\u8bed\u8a00\u6a21\u578b\u5916\uff0c\u8fd8\u4f1a\u4ecb\u7ecd\u4f20\u7edf\u65b9\u6cd5\u548c\u4f20\u7edf\u6a21\u578b\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#survey","title":"Survey","text":""},{"location":"docs/3-dl/survey/multilingual/#a-survey-on-large-language-models-with-multilingualism-recent-advances-and-new-frontiers-2024","title":"A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers (2024)","text":""},{"location":"docs/3-dl/survey/multilingual/#_1","title":"\u7b80\u4ecb","text":"

    \u672c\u6587\u4ecb\u7ecd\u591a\u8bed\u8a00\u5927\u8bed\u8a00\u6a21\u578b\u7684\u8bad\u7ec3\u3001\u4f7f\u7528\u3001\u6311\u6218\u3001\u672a\u6765\u7814\u7a76\u65b9\u5411\u7b49\u3002\u7531 Beijing Jiaotong University, University of Montreal \u548c Tsinghua University \u53d1\u5e03\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_2","title":"\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/multilingual/#_3","title":"\u6709\u591a\u8bed\u8a00\u80fd\u529b\u7684\u5927\u8bed\u8a00\u6a21\u578b\u6982\u89c8","text":""},{"location":"docs/3-dl/survey/multilingual/#_4","title":"\u591a\u8bed\u8a00\u63a8\u7406\u7b56\u7565","text":""},{"location":"docs/3-dl/survey/multilingual/#_5","title":"\u5b89\u5168\u6027","text":""},{"location":"docs/3-dl/survey/multilingual/#_6","title":"\u591a\u9886\u57df\u591a\u8bed\u8a00\u5927\u8bed\u8a00\u6a21\u578b","text":""},{"location":"docs/3-dl/survey/multilingual/#_7","title":"\u591a\u8bed\u8a00\u6570\u636e\u8d44\u6e90","text":""},{"location":"docs/3-dl/survey/multilingual/#_8","title":"\u591a\u8bed\u8a00\u8bc4\u6d4b","text":""},{"location":"docs/3-dl/survey/multilingual/#_9","title":"\u504f\u89c1\u548c\u516c\u5e73\u6027","text":""},{"location":"docs/3-dl/survey/multilingual/#models","title":"Models","text":""},{"location":"docs/3-dl/survey/multilingual/#datasets","title":"Datasets","text":""},{"location":"docs/3-dl/survey/multilingual/#studies","title":"Studies","text":""},{"location":"docs/3-dl/survey/multilingual/#do-llamas-work-in-english-2024-epfl","title":"Do Llamas Work in English? (2024, EPFL)","text":"

    \u731c\u60f3\uff1a\u591a\u8bed\u8a00\u6a21\u578b\uff08\u6bd4\u5982 Llama\uff09\u5728\u4f7f\u7528\u4ee5\u82f1\u8bed\u4e3a\u4e3b\u7684\u8bed\u6599\u8fdb\u884c\u8bad\u7ec3\u65f6\uff0c\u4f1a\u5c06\u82f1\u8bed\u4f5c\u4e3a\u4e00\u79cd\u601d\u8003\u7684\u4e2d\u95f4\u6b65\u9aa4 pivot language\u3002

    \u5b9e\u9a8c\u65b9\u6cd5\uff1a\u5bf9 Llama-2 \u7cfb\u5217\u6a21\u578b\uff0c\u8bbe\u8ba1\u6570\u636e\u5bf9 (\u975e\u82f1\u8bed\u63d0\u793a\u8bcd\uff0cnext token)\u3002\u4ece\u9876\u5c42\u5411\u91cf\u7a7a\u95f4 high-dimensional space \u63a2\u7d22\u4e2d\u95f4\u5d4c\u5165 intermediate embeddings \u5982\u4f55\u8ba1\u7b97\u4e0b\u4e00\u4e2a\u5355\u8bcd\u7684\u89c4\u5f8b\u3002

    \u53d1\u73b0\u4e09\u4e2a\u9636\u6bb5\uff1a

    \u4e00\u53e5\u8bdd\u603b\u7ed3\uff1aimtermediate embedding \u6240\u4ee3\u8868\u7684\u62bd\u8c61\u6982\u5ff5\u7a7a\u95f4 concept space \u66f4\u63a5\u8fd1\u82f1\u8bed\uff0c\u53ef\u80fd\u5bfc\u81f4\u591a\u8bed\u8a00\u6a21\u578b\u4e2d\u7684\u504f\u89c1\u95ee\u9898\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#language-specific-neurons-the-key-to-multilingual-capability-in-large-language-models-2024-ruc","title":"Language-Specific Neurons: The Key to Multilingual Capability in Large Language Models (2024, RUC)","text":""},{"location":"docs/3-dl/survey/multilingual/#_10","title":"\u80cc\u666f","text":"

    \u8bc6\u522b\u591a\u8bed\u8a00\u5927\u6a21\u578b\u91cc\uff0c\u4ea7\u751f\u7279\u5b9a\u8bed\u8a00\u80fd\u529b\u7684\u795e\u7ecf\u5143\u4ecd\u7136\u975e\u5e38 challenging\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_11","title":"\u65b9\u6cd5","text":"

    \u63d0\u51fa\u4e86 language activation probability entropy (LAPE) \u6765\u68c0\u6d4b\u5927\u8bed\u8a00\u6a21\u578b\u4e0d\u540c\u8bed\u8a00\u5bf9\u5e94\u7684\u795e\u7ecf\u5143\u3002

    LAPE: \u4e3a\u4e86\u51cf\u5c11 RLHF \u53ef\u80fd\u5e26\u6765\u7684\u5bf9\u8bed\u8a00\u504f\u597d\u7684\u7684\u5f71\u54cd\uff0c\u4e3b\u8981\u5173\u6ce8\u9884\u8bad\u7ec3\u8fc7\u7684\u6a21\u578b\uff0c\u800c\u4e0d\u662f\u5fae\u8c03\u540e\u7684\u6a21\u578b\u3002

    \u5bf9\u4e8e\u5728\u7b2c i \u5c42\u7684\u7b2c j \u4e2a neuron\uff0c\u5b9a\u4e49\u5728\u8bed\u8a00 k \u4e0a\u7684\u6fc0\u6d3b\u6982\u7387 activation probability

    \\[ p_{i,j}^k = E(I(act_fn(\\tilde{h}^iW_1^i)_j \\lt 0 | language\\spacek)) \\]

    I \u662f indicator function\uff08\u5f53\u7ed9\u5b9a\u6761\u4ef6\u4e3a\u771f\u65f6\uff0c\u6307\u793a\u51fd\u6570\u7684\u503c\u4e3a 1\uff1b\u5f53\u7ed9\u5b9a\u6761\u4ef6\u4e3a\u5047\u65f6\uff0c\u6307\u793a\u51fd\u6570\u7684\u503c\u4e3a 0\uff09\u3002

    \u4ee5\u6b64\u53ef\u4ee5\u83b7\u5f97\u6bcf\u4e2a\u795e\u7ecf\u5143\u5bf9\u8bed\u8a00\u7684\u5206\u5e03

    \\[ p_{i,j} = (p_{i,j}^1, ... , p_{i,j}^k, ... , p_{i,j}^l) \\]

    \u5b9a\u4e49\u4e0a\u8ff0\u5206\u5e03\u7684\u71b5\u4e3a language activation probability entropy (LAPE) \u3002

    \\[ LAPE_{i,j} = -\\sum^{l}_{k=1} p^{\\prime k}_{i,j} log(p^{\\prime k}_{i,j}) \\]

    \u4f7f\u7528 Llama-2, BLOOM, Mistral \u548c Phi-2 \u8fdb\u884c\u5b9e\u9a8c\uff0c\u53d1\u73b0\u8fd9\u4e9b\u795e\u7ecf\u5143\u4e3b\u8981\u5728\u9876\u5c42\u548c\u5e95\u5c42 embedding \u4e0a\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_12","title":"\u53d1\u73b0","text":""},{"location":"docs/3-dl/tools/","title":"Tools","text":"

    :material-circle-edit-outline: \u7ea6 13 \u4e2a\u5b57

    Any tool recommendations, or any tutorial or tutorial remmondations.

    "},{"location":"docs/3-dl/tools/#contents","title":"Contents","text":""},{"location":"docs/3-dl/tools/codabench/","title":"Codabench \u6bd4\u8d5b\u521b\u5efa\u6559\u7a0b","text":"

    :material-circle-edit-outline: \u7ea6 2098 \u4e2a\u5b57 :fontawesome-solid-code: 82 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f

    "},{"location":"docs/3-dl/tools/codabench/#_1","title":"\u7b80\u4ecb","text":"

    Codabench \u662f\u4e00\u4e2a\u4e3a\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u6bd4\u8d5b\u8bbe\u8ba1\u7684\u4f4e\u4ee3\u7801\u6a21\u578b\u6d4b\u8bd5\u5e73\u53f0\u3002\u5e73\u53f0\u63d0\u4f9b CPU\uff0c\u5141\u8bb8\u6bd4\u8d5b\u521b\u529e\u8005\u901a\u8fc7\u4e0a\u4f20\u811a\u672c\u548c\u6570\u636e\u7684\u65b9\u5f0f\u521b\u529e\u6bd4\u8d5b\uff0c\u5e76\u5141\u8bb8\u5176\u5b83\u7528\u6237\u4f7f\u7528\u5e73\u53f0 CPU \u6765\u8fd0\u884c\u4ee3\u7801\u5f97\u5230\u7ed3\u679c\u3002\u524d\u5e8f\u5de5\u4f5c\u662f CodaLab\uff0c2023 \u5e74 Codabench \u56e2\u961f\u4eff\u7167 CodaLab \u6539\u8fdb\u51fa\u4e86 Codabench\u3002

    Codabench \u7684\u4f18\u70b9\u662f\u63d0\u4f9b\u516c\u5171 CPU\uff0c\u4f7f\u6bd4\u8d5b\u521b\u529e\u65b9\u5728\u5c06\u6b63\u786e\u7b54\u6848\u4fdd\u5bc6\u7684\u60c5\u51b5\u4e0b\uff0c\u4e0d\u5fc5\u4eb2\u624b\u6536\u96c6\u53c2\u8d5b\u8005\u7684\u7b54\u6848\u5e76\u4e00\u4e00\u4eb2\u624b\u6d4b\u8bd5\uff0c\u800c\u662f\u5141\u8bb8\u7528\u6237\u81ea\u884c\u901a\u8fc7\u5e73\u53f0\u6d4b\u8bd5\u5e76\u5f97\u5230\u7ed3\u679c\uff0c\u51cf\u8f7b\u8d1f\u62c5\u3002\u800c\u7528\u6237\u4e5f\u53ef\u4ee5\u66f4\u8fc5\u901f\u77e5\u9053\u81ea\u5df1\u7684\u5206\u6570\uff0c\u4e0d\u5fc5\u7b49\u5f85\u6bd4\u8d5b\u65b9\u9a8c\u8bc1\u8fd9\u4e2a\u65f6\u95f4\u8f83\u957f\u7684\u6d41\u7a0b\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_2","title":"\u8fd0\u4f5c","text":"

    \u6bd4\u8d5b\u521b\u529e\u8005\u901a\u8fc7\u4e0a\u4f20\u6bd4\u8d5b\u914d\u7f6e\u540e\uff0c\u6bcf\u5f53\u6709\u7528\u6237\u52a0\u5165\u5e76\u63d0\u4ea4\u4e00\u4e2a\u8fd0\u884c\u8bf7\u6c42\uff0c\u5e73\u53f0\u5c06\u5728 CPU \u4e0a\u4e3a\u6bcf\u4e2a\u63d0\u4ea4\u521b\u5efa\u4e00\u4e2a Docker\uff0c\u5305\u542b\u6bd4\u8d5b\u521b\u529e\u8005\u63d0\u4f9b\u7684\u6bd4\u8d5b\u914d\u7f6e\u548c\u8be5\u7528\u6237\u63d0\u4ea4\u7684\u6570\u636e\uff0c\u5728 Docker \u4e2d\u8fd0\u884c\u6307\u5b9a\u8def\u5f84\u7684\u4ee3\u7801\uff0c\u5e76\u5c06\u7ed3\u679c\u663e\u793a\u5728\u5e73\u53f0\u5c55\u793a\u7684 terminal \u4e0a\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_3","title":"\u521b\u5efa","text":"

    \u5728 Codabench \u5b98\u7f51\u6ce8\u518c\u767b\u9646\u540e\uff0c\u70b9\u51fb\u53f3\u4e0a\u89d2 Benchmark -> Management\uff0c\u53ef\u4ee5\u9009\u62e9 Create \u6216 Upload \u6765\u521b\u5efa\u6bd4\u8d5b\u3002

    \u66f4\u63a8\u8350\u7528 Upload \u6765\u521b\u5efa\uff0c\u56e0\u4e3a UI \u7684\u7528\u6237\u63d0\u793a\u6bd4\u8f83\u6b20\u7f3a\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_4","title":"\u4e0a\u4f20\u521b\u5efa","text":"

    'bundle' \u6307\u6bd4\u8d5b\u521b\u5efa\u8005\u4e0a\u4f20\u7684\u538b\u7f29\u6587\u4ef6\u3002\u91cc\u9762\u542b\u6709\uff1a

    \u9700\u8981\u671f\u5f85\u7528\u6237\u4e0a\u4f20\uff1a

    \u4e0b\u9762\u4ecb\u7ecd\u51e0\u4e2a\u5b98\u65b9\u6587\u6863\u8bb2\u5f97\u4e0d\u592a\u6e05\u695a\u7684\u7ec6\u8282\u3002

    "},{"location":"docs/3-dl/tools/codabench/#competitionyaml","title":"competition.yaml \u6587\u4ef6","text":"

    competition.yaml \u6587\u4ef6\u4e0d\u80fd\u6539\u540d\uff0c\u4e14\u5fc5\u987b\u4f4d\u4e8e .zip \u4e2d\u7684\u6700\u9876\u5c42\uff08\u5373\u591a\u9009 competition.yaml \u548c\u5176\u5b83\u6587\u4ef6\u5939\u540e\u521b\u5efa .zip\uff0c\u800c\u975e\u628a\u542b\u6709 competition.yaml \u548c\u5176\u5b83\u6587\u4ef6\u5939\u7684\u4e0a\u5c42\u6587\u4ef6\u5939\u521b\u5efa\u4e3a .zip\uff09\u3002\u5177\u4f53\u5982\u56fe\u6240\u793a\u3002\u4e0b\u6587\u6240\u63d0\u5230\u7684\u65e0\u9876\u5c42\u6587\u4ef6\u5939 / \u6587\u4ef6\u4f4d\u4e8e\u538b\u7f29\u5305\u9876\u5c42\uff0c\u90fd\u662f\u6307\u5982\u56fe\u6240\u793a\u7684\u538b\u7f29\u5305\u7ed3\u6784\u3002

    competition.yaml \u652f\u6301\u7684\u5b57\u6bb5\u6709\uff1a

    title: # \u6bd4\u8d5b\u540d\nversion: # 1 \u6307\u662f CodaLab bundle\uff0c2 \u6307 CodaBench bundle\uff0c\u533a\u522b\u662f\u6709\u4e9b competition.yaml \u5b57\u6bb5\u4e0d\u517c\u5bb9\ndescription: # \u6bd4\u8d5b\u63cf\u8ff0\nimage: # \u6bd4\u8d5b logo.png\nregistration_auto_approve: True  # do not require approval from organizers to join\ndocker_image: codalab/codalab-legacy:py39 # the Docker image in which submissions are run\uff0c\u7528\u6b64 default \u5373\u53ef\nenable_detailed_results: True # \u4e0d\u660e\uff0c\u53ef\u4ee5 default\n# Documentation web pages\nterms: pages/terms.md # \u5fc5\u987b\u6709\u4e00\u4e2a terms\npages:  # \u53ef\u4efb\u610f\u52a0\u9875\u9762\n- title: # e.g., Overview\nfile: # e.g., pages/overview.md\n# Definition of the tasks\ntasks:\n- index: 0\nname: # e.g., Development Task\ndescription: # \u63cf\u8ff0\nis_public: true   # \u516c\u5f00\u53ef\u89c1\ninput_data: # e.g., feedback_phase/input_data, \u6b64\u5904\u53ca\u4e0b\u5217\u8def\u5f84\u9700\u8981\u586b\u5199\u6240\u4e0a\u4f20 bundle \u91cc\u7684\u8def\u5f84\uff0c\u800c\u975e\u6240\u751f\u6210 Docker \u4e2d\u7684\nreference_data: # e.g., feedback_phase/reference_data\nscoring_program: # e.g., scoring_program\ningestion_program: # e.g., ingestion_program\nsolutions: []   # \u4e0d\u660e\n# Sample code submission\nsolutions:      # \u53ef\u80fd\u4f1a\u663e\u793a\u5728\u6bd4\u8d5b\u9996\u9875\u7684 resources \u5217\u8868\n- index: 0\ntasks:\n- 0\n- 1\npath: solution/\nphases:\n- index: 0\nname:             # phase \u6807\u9898\ndescription:      # \u63cf\u8ff0\nstart: 1-1-2024   # Month / Day / Year\nend: 1-30-2024    # end \u7ed3\u675f\u65f6\u95f4\u53ef\u4ee5\u7f3a\u5931\uff0c\u8868\u793a\u6c38\u8fdc\u53ef\u63d0\u4ea4\nmax_submissions_per_day: 5    # \u6700\u5927\u4f3c\u4e4e\u662f 100\uff1f\nmax_submissions: 100          # \u6700\u5927\u4f3c\u4e4e\u662f 10000\uff1f\nexecution_time_limit: 600     # \u6bcf\u6b21\u63d0\u4ea4\u5141\u8bb8\u7684\u6700\u957f\u8fd0\u884c\u65f6\u95f4\uff0c\u8d85\u8fc7\u8fd9\u4e2a\u65f6\u95f4\u5c06\u663e\u793a run time exceed\ntasks:            # \u4e0e\u8be5 phase \u5173\u8054\u7684 tasks\n- 0\nsolutions: []\nstarting_kit: # e.g., starting_kit, \u53ef\u80fd\u4f1a\u663e\u793a\u5728\u6bd4\u8d5b\u9996\u9875\u7684 resources \u5217\u8868\npublic_data: # e.g., starting_kit, feedback_phase/input_data\n# Fact sheets to add more information in the leaderboard\nfact_sheet: {                   # \u4f3c\u4e4e\u662f\u5c55\u793a\u5728 leaderboard \u4e2d\u652f\u6301\u7528\u6237\u4fee\u6539\u7684\u66f4\u591a\u4fe1\u606f\u3002`method_name` \u8be5\u5b57\u6bb5\u5e94\u4e0e\u4e0b\u65b9 `results` \u5e73\u7ea7\u3002\n\"method_name\": {\n\"key\": \"method_name\",\n\"type\": \"text\",\n\"title\": \"Method name\",\n\"selection\": \"\",\n\"is_required\": \"false\",\n\"is_on_leaderboard\": \"true\"\n}\n}\n# Leaderboard\nleaderboards:\n- index: 0\ntitle: Results                    # leaderboard \u7684 title\nkey: Results                      # `output.json` \u4e2d\u7528\u4e8e\u5b9a\u4f4d\u7684 key\nsubmission_rule: \"Force_Last\"     # \u53ef\u4ee5\u53bb\u6389\uff0c\u9ed8\u8ba4\u4f3c\u4e4e\u662f\u5141\u8bb8\u5c55\u793a\u591a\u4e2a\u7ed3\u679c\ncolumns:\n- title: Average Accuracy     # \u5728 output.json \u4e2d\uff0c\u8bfb\u53d6\u8be5 json \u7684\u54ea\u4e2a key\nkey: avg_accuracy           # `output.json` \u4e2d\u7528\u4e8e\u5b9a\u4f4d\u7684 key\nindex: 0                    # \u5c55\u793a\u5728 leaderboard \u8868\u683c\u4e2d\u7684\u7b2c\u51e0\u5217\nsorting: desc               # \u5347\u5e8f/\u964d\u5e8f\u6392\u5217\ncomputation: avg            # \u540c\u4e00\u7528\u6237\u7684\u591a\u4e2a\u63d0\u4ea4\uff0c\u6309\u4ec0\u4e48\u8ba1\u7b97\u65b9\u6cd5\u6392\u5e8f\uff1f\ncomputation_indexes:        # \u5728\u54ea\u4e00\u5217\u4e0a\u8ba1\u7b97\n- 1\n
    "},{"location":"docs/3-dl/tools/codabench/#scoring-program","title":"scoring program \u7684\u8def\u5f84\u8bf4\u660e","text":"

    \u5947\u5f02\u7684\u662f\uff0c\u6bd4\u8d5b\u8fd0\u884c\u65f6\u6240\u521b\u5efa\u7684 Docker \u4e2d\u6587\u4ef6\u7ed3\u6784\u5e76\u4e0d\u662f bundle \u7684\u7ed3\u6784\uff0c\u6216\u8005\u793a\u4f8b competition.yml \u4e2d\u6307\u793a\u7684\u8def\u5f84\uff0c\u800c\u662f\u4f1a\u628a\u5404\u79cd\u8d44\u6e90\u7ed3\u6784\u6253\u4e71\u653e\u5728\u4e0d\u540c\u7684\u4f4d\u7f6e\u3002\u5bf9\u6211\u4eec\u5f71\u54cd\u5c31\u662f\uff0c\u5982\u679c scoring program \u9700\u8981\u8bfb\u5176\u5b83\u6587\u4ef6\uff08\u591a\u4ee3\u7801\u6587\u4ef6 / gold answer \u7b49\uff09\uff0c\u5c31\u9700\u8981\u6309\u521b\u5efa\u597d\u7684 Docker \u4e2d\u7684\u65b0\u6587\u4ef6\u8def\u5f84\u8bfb\u53d6\u3002

    \u6bd4\u5982\uff0c\u5728\u6211\u7684\u6d4b\u8bd5\u4e2d\uff0cDocker \u7684\u5b9e\u9645\u6587\u4ef6\u5939\u7ed3\u6784\u5982\u4e0b\uff1a

    .\n- app\n    - codalab           // \u4e0d\u660e\n    - data              // \u4e0d\u660e\n    - input\n        - res           // \u7528\u6237\u7ed3\u679c\n        - ref           // gold anwser\n    - shared            // \u4e0d\u660e\n    - program           // \u6240\u4e0a\u4f20\u811a\u672c\n        - score.py\n        - metadata.yaml\n    - output            // \u811a\u672c\u8f93\u51fa\uff0c\u7528\u4e8e leaderboard \u8bfb\u53d6\n        - output.json\n

    \u5982\u679c\u4e0a\u8ff0\u8def\u5f84\u5728\u4f60\u7684\u6d4b\u8bd5\u4e2d\u4e0d work\uff0c\u53ef\u4ee5\u5148\u4e0a\u4f20\u4e00\u4e2a\u542b\u6709 competition.yaml / scoring program / reference data / result data / ingestion program \u7b49\u6240\u6709\u8d44\u6e90\u7684\u6d4b\u8bd5 bundle\uff0c\u8981\u6c42 scoring program \u8f93\u51fa Docker \u7684\u6587\u4ef6\u5939\u7ed3\u6784\u6811\uff0c\u5728 terminal \u4e2d\u4f9d\u6b21\u8bb0\u4e0b\u8d44\u6e90\u7684\u8def\u5f84\u3002

    "},{"location":"docs/3-dl/tools/codabench/#scoring-program_1","title":"scoring program \u7684\u8f93\u51fa\u8bf4\u660e","text":"

    scoring program \u5728\u8fd0\u884c\u5b8c\u6210\u540e\u88ab\u671f\u5f85\u5199\u4e00\u4e2a output.json \u6587\u4ef6\uff0c\u5176\u8def\u5f84\u5728\u524d\u4e00\u8282\u6709\u8bf4\u660e\u3002\u5176\u7ed3\u6784\u636e\u63a8\u6d4b\u5e94\u5f53\u662f\uff0c

    {\n\"leaderboards_key\": {\n\"column_key1\": 0,\n\"column_key2\": 0,\n...\n}\n}\n

    \u5176\u4e2d\u51e0\u4e2a 'key' \u5206\u522b\u5bf9\u5e94\u5728 competition.yaml \u7684 leaderboards \u8bbe\u7f6e\u4e2d\u81ea\u5b9a\u4e49\u7684 key\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_5","title":"\u5e38\u89c1\u62a5\u9519","text":"

    \u5c06 bundle \u62d6\u5165 Upload \u9875\u9762\u540e\uff0c\u5982\u679c\u62a5\u9519\u663e\u793a Creation Fail\uff0c\u6b64\u65f6\u9996\u5148\u5e94\u5f53\u68c0\u67e5\u662f\u5426\u6709 competition.yaml \u6587\u4ef6\uff0c\u6587\u4ef6\u540d\u548c\u5185\u5bb9\u683c\u5f0f\u6b63\u786e\uff0c\u5e76\u4e14\u4f4d\u4e8e\u538b\u7f29\u5305\u9876\u5c42\uff08\u53c2\u7167\u4e0a\u65b9\u538b\u7f29\u56fe\u793a\uff09\u3002\u4e00\u822c\u662f\u6b64\u9519\u8bef\u3002

    "},{"location":"docs/3-dl/tools/codabench/#bundle","title":"bundle \u6a21\u677f","text":"

    codalab/competition-examples/codabench \u5b98\u65b9\u63d0\u4f9b\u7684\u51e0\u4e2a bundle \u6a21\u677f\uff0c\u53ef\u4ee5\u5bf9\u6bd4 Codabench \u4e0a\u540c\u540d\u6bd4\u8d5b\u67e5\u770b\u521b\u5efa\u7ed3\u679c\uff0c\u5728\u672c\u4ed3\u5e93\u62ff\u4e00\u4e9b\u9700\u8981\u7684\u5199\u6cd5\u3002

    "},{"location":"docs/3-dl/tools/codabench/#ui","title":"UI \u521b\u5efa","text":"

    \u8fdb\u5165 Codabench \u9996\u9875\uff0c\u70b9\u51fb\u53f3\u4e0a\u89d2 Benchmark -> Management\uff0c\u9009\u62e9 Upload \u6765\u521b\u5efa\u6bd4\u8d5b\u3002

    \u9876\u5c42\u6709 Details / Participation / Pages / Phases / Leaderboard / Administrators \u516d\u4e2a\u9875\u9762\uff0c\u5176\u5b83\u8f83\u6613\u61c2\uff0c\u4e0d\u518d\u8d58\u8ff0\uff0cPhases \u7684\u8bbe\u7f6e\u6bd4\u8f83\u590d\u6742\u3002

    Phases \u6784\u6210\u6bd4\u8d5b\u4e3b\u4f53\u3002\u4e00\u4e2a\u6bd4\u8d5b\u53ef\u4ee5\u6709\u4e00\u4e2a\u6216\u591a\u4e2a phase\uff0c\u8fd9\u6837\u8bbe\u8ba1\u53ef\u80fd\u662f\u6709\u4e9b\u6bd4\u8d5b\u5206\u6210\u5728\u591a\u4e2a\u6570\u636e\u96c6\u4e0a\u6d4b\u8bd5\uff1b\u4e00\u4e2a phase \u53c8\u53ef\u4ee5\u5305\u542b\u591a\u4e2a tasks\uff0c\u53ef\u80fd\u662f\u4e3a\u4e86\u652f\u6301\u6709\u4e9b\u6bd4\u8d5b\u6bcf\u4e2a phase \u53c8\u6709\u591a\u4e2a\u6570\u636e\u96c6\u3002phase \u4e4b\u95f4\u4e0d\u5171\u4eab\u8d44\u6e90/Docker \u73af\u5883\uff0c\u540c\u4e00\u4e2a phase \u7684\u4e0d\u540c task \u4e4b\u95f4\u5171\u4eab\u8d44\u6e90/\u73af\u5883\u3002

    \u6700\u7b80\u5355\u7684\u65b9\u5f0f\u53ef\u4ee5\u53ea\u5b9a\u4e49\u4e00\u4e2a phase\u3002\u533a\u5206\u6570\u636e\u96c6\u751a\u81f3\u53ef\u4ee5\u53ea\u901a\u8fc7 scoring program \u6765\u5b9e\u73b0\u3002

    \u5728 phase \u7684 edit \u754c\u9762\u6700\u4e0b\u65b9\uff0c\u53ef\u4ee5\u901a\u8fc7 Manage tasks \u6309\u94ae\u6253\u5f00 task \u7684 edit \u754c\u9762\u3002

    \u8be5\u754c\u9762\u4e2d Submission / Datasets and programs / Bundles \u4e09\u4e2a\u9875\u9762\u90fd\u53ef\u4ee5\u5ffd\u89c6\uff0c\u53ea\u9700\u8981\u4f7f\u7528 Tasks \u8fd9\u4e2a\u9875\u9762\u3002

    task \u7684\u672c\u8d28\u610f\u4e49\u662f scoring program \u548c reference data / ingestion program / result data \u7684\u5173\u8054\u65b9\u5f0f\u3002

    \u5982\u679c\u5b9a\u4e49\u4e00\u4e2a phase \u6709\u591a\u4e2a tasks\uff0c\u5728\u7528\u6237\u63d0\u4ea4\u65f6\uff0c\u4f1a\u663e\u793a\u9009\u62e9\u63d0\u4ea4\u54ea\u4e2a task \u7684\u590d\u9009\u6846\u3002\u5f53\u590d\u9009\u6846\u88ab\u52fe\u9009\u65f6\uff0ctask \u6240\u5173\u8054\u7684 scoring program \u88ab\u8fd0\u884c\u3002

    \u5f53\u7136\u4e5f\u6709\u4e0d\u521b\u5efa\u591a\u4e2a task\uff0c\u5c06\u591a\u4e2a\u8bc4\u6d4b\u5408\u5e76\u4e3a\u4e00\u4e2a\u811a\u672c\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728\u811a\u672c\u91cc\u68c0\u6d4b\u7528\u6237\u4e0a\u4f20\u4e86\u54ea\u4e9b\u7ed3\u679c\uff0c\u636e\u6b64\u9009\u62e9\u8fd0\u884c\u54ea\u4e9b\u8bc4\u6d4b\u3002\u8fd9\u91cc scoring program \u7684\u8bbe\u8ba1\u81ea\u7531\u5ea6\u6bd4\u8f83\u9ad8\u3002

    \u5728 task \u7684\u7f16\u8f91\u9875\u9762\u91cc\uff0c

    \u8d44\u6e90\u6587\u4ef6\u5939\u540d\u5fc5\u987b\u4e0e\u6bd4\u8d5b\u521d\u59cb\u5316\u65f6 competition.yaml \u6307\u5b9a\u7684\u6587\u4ef6\u5939\u540d\u76f8\u540c\uff0c\u538b\u7f29\u5305\u540d\u548c\u5728\u8fd9\u91cc\u586b\u5199\u7684\u8d44\u6e90\u522b\u540d\u5219\u4efb\u610f\u3002\u4f8b\u5982\uff0c\u5728 competition.yaml \u4e2d\u6307\u5b9a\u4e86 reference data \u7684\u6587\u4ef6\u5939\u540d\u662f ref_data\uff0c\u90a3\u4e48\u5728\u4e0a\u4f20\u65f6\u4e5f\u9700\u8981\u5c06\u4e00\u4e2a\u540d\u4e3a ref_data \u7684\u6587\u4ef6\u5939\u8fdb\u884c\u538b\u7f29\u3002\u4f46\u662f\u538b\u7f29\u540e\u5f97\u5230\u7684\u538b\u7f29\u5305\u540d\u5b57\u968f\u610f\uff0c\u53ef\u4ee5\u53eb AAA.zip \u7b49\uff1b\u4e0a\u4f20\u540e\u5728 UI \u5904\u4f1a\u5141\u8bb8\u4f60\u4e3a\u8fd9\u6b21\u4e0a\u4f20\u7684\u8d44\u6e90\u8d77\u4e00\u4e2a\u522b\u540d\uff0c\u4e5f\u662f\u968f\u610f\u7684\uff0c\u53ef\u4ee5\u53eb ref_data20240925 \u7b49\u3002\u5982\u9047\u5230\u8d44\u6e90\u4e0a\u4f20\u5931\u8d25\u4f46\u65e0\u62a5\u9519\uff0c\u53ef\u4ee5\u4f18\u5148\u8003\u8651\u8fd9\u4e2a\u539f\u56e0\u3002

    \u6bcf\u4e2a task \u4e2d\uff0c\u5fc5\u987b\u6dfb\u52a0\u7684\u8d44\u6e90\u662f scoring program\uff0c\u6709\u8fd9\u4e2a\u624d\u80fd\u8fd0\u884c\u3002\u53ef\u6839\u636e\u9700\u8981\u6dfb\u52a0 reference data\u3002

    \u8d44\u6e90\u53ea\u6709\u5728\u6ca1\u6709\u4e0e\u4e4b\u5173\u8054\u7684 task \u65f6\u624d\u80fd\u88ab\u4ece\u8d44\u6e90\u5217\u8868\u4e2d\u5220\u9664\u3002\u5f53\u5b58\u5728\u6ca1\u6709 task \u5173\u8054\u7684\u8d44\u6e90\u65f6\uff0c\u4e0b\u9762 Quota and Cleanup \u4e2d\u4f1a\u9ad8\u4eae Delete unused datasets/programs\uff0c\u53ef\u4ee5\u70b9\u51fb\u4e00\u952e\u6e05\u9664\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_6","title":"\u4fee\u6539","text":"

    \u53ea\u652f\u6301\u901a\u8fc7 UI \u4fee\u6539\u3002\u4e0d\u80fd\u91cd\u65b0\u4e0a\u4f20 bundle\uff0c\u6bcf\u6b21\u91cd\u65b0\u4e0a\u4f20 bundle \u5c31\u89c6\u4e3a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u6bd4\u8d5b\u3002

    \u8fdb\u5165 Codabench \u9996\u9875 -> \u53f3\u4e0a\u89d2 Benchmark -> Management -> \u9009\u62e9\u4e00\u4e2a\u5df2\u6709\u7684\u6bd4\u8d5b\u53f3\u4fa7 Edit \u6309\u94ae\u3002

    \u5176\u4f59\u6b65\u9aa4\u540c\u4e0a\u65b9 ### UI \u521b\u5efa \u4e00\u8282\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_7","title":"\u4f7f\u7528","text":"
    1. \u63d0\u4ea4\uff1a\u4e0a\u4f20\u65e0\u9876\u5c42\u6587\u4ef6\u5939\u7684\u591a\u4e2a\u7ed3\u679c\u6587\u4ef6\u5939\u538b\u7f29\u5305\u3002\u8bfb\u6761\u7ed3\u675f\u540e\u5c06\u663e\u793a\u4e00\u4e2a running xxx\uff0c\u81ea\u52a8\u8fdb\u5165\u8fd0\u884c\u3002\u5982\u672a\u663e\u793a running \u8fd9\u4e2a\u6846\uff0c\u4e00\u822c\u662f\u5e73\u53f0 CPU \u7d27\u7f3a\uff0c\u53ef\u4ee5\u7b49\u5f85\u4e00\u6bb5\u65f6\u95f4\u518d\u5c1d\u8bd5\u3002\u5982\u679c\u663e\u793a\u5219\u8bf4\u660e\u5f00\u59cb\u8fd0\u884c\u4e86\u3002
    2. \u67e5\u770b\u7ed3\u679c\uff1a\u70b9\u51fb running xxx \u53ef\u4ee5\u67e5\u770b\u8fd0\u884c\u671f\u95f4\u7684 terminal \u8f93\u51fa\uff0c\u6b64\u5904 terminal \u662f\u6b63\u5e38\u7684 terminal\uff0c\u4f1a\u663e\u793a\u6240\u6709 warning / error / \u8f93\u51fa\u3002\u8fd0\u884c\u5b8c\u6210\u540e\u5e94\u5f53\u663e\u793a Finish\u3002
    3. \u67e5\u770b\u62a5\u9519\uff1a\u5982\u679c\u72b6\u6001\u4e0d\u662f Finish\uff0c\u5982 Scoring / Running / Error\uff0c\u53ef\u4ee5\u70b9\u51fb\u5f53\u524d\u63d0\u4ea4\u5bf9\u5e94\u7684\u72b6\u6001\u680f\u3002

    Download \u4e2d\u53ef\u4ee5\u4e0b\u8f7d\u5230\u7684\u5185\u5bb9\u4e0e logs \u4e2d\u80fd\u8f93\u51fa\u7684\u5185\u5bb9\u76f8\u4f3c\uff0c\u76f4\u63a5\u67e5\u770b logs \u5373\u53ef\u3002

    terminal \u7684\u5de6\u4fa7\u5206\u4e3a prediction \u548c scoring \u4e24\u79cd\uff0c\u5f53\u6709 ingestion program \u65f6\u7b2c\u4e00\u4e2a terminal \u624d\u4f1a\u6709\u8f93\u51fa\u3002stdout \u548c stderr \u5c06 terminal \u8f93\u51fa\u5206\u5f00\u4e86\uff0cstdout \u662f\u7a0b\u5e8f\u6307\u5b9a\u7684\u6b63\u5e38\u8f93\u51fa\uff0cstderr \u662f error \u8f93\u51fa\uff0c\u6709\u65f6\u5019\u4f1a\u5b58\u5728\u5176\u4e2d\u4e00\u4e2a\u6ca1\u6709\u8f93\u51fa\u7684\u60c5\u51b5\uff0c\u53ef\u5207\u6362\u67e5\u770b\u3002

    Leaderboard \u7684\u7ed3\u679c\u4e0d\u4f1a\u81ea\u52a8\u66f4\u65b0\u5230 Leaderboard\uff0c\u9700\u8981\u7528\u6237\u540c\u610f\u3002\u70b9\u51fb\u8fd0\u884c\u7ed3\u679c\u53f3\u4fa7\u7684\u6309\u94ae\u66f4\u65b0\u5230 Leaderboard\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_8","title":"\u53c2\u8003\u8d44\u6599","text":"

    \u73b0\u6709\u5b98\u7f51\u53c2\u8003\u8d44\u6599\u4f3c\u4e4e\u90fd\u4e0d\u592a\u5168\u9762\uff0c\u4e0d\u80fd\u8986\u76d6\u5404\u79cd\u5e38\u89c1\u9519\u8bef\uff0c\u56e0\u6b64\u4e00\u4e9b\u521b\u5efa\u6b65\u9aa4\u548c\u884c\u4e3a\u662f\u901a\u8fc7\u6d4b\u8bd5\u548c\u63a8\u6d4b\u5f97\u77e5\u7684\u3002\u5982\u679c\u672c\u6587\u6709\u8bef\uff0c\u6b22\u8fce\u8054\u7cfb\u4f5c\u8005\u6539\u6b63\uff01

    "},{"location":"docs/3-dl/tools/nlp_resources/","title":"DL & NLP Resources","text":"

    :material-circle-edit-outline: \u7ea6 213 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u8fd9\u4e2a\u9875\u9762\u7528\u6765\u6536\u96c6 nlp \u5165\u95e8\u8d44\u6599\u7684 minimal closure\uff08\u6307\u8db3\u591f\u5b66\u4f1a\u7684\u6700\u5c0f\u8d44\u6e90\u96c6\u5408\uff09

    "},{"location":"docs/3-dl/tools/nlp_resources/#machine-learning-theory","title":"Machine Learning Theory","text":"

    Google\u7684\u4e00\u4e2a\u6559\u7a0b\uff0c\u91cc\u9762\u7684playground\u505a\u5f97\u6bd4\u8f83\u76f4\u89c2\uff0c\u65e0\u9700\u4ee3\u7801

    Machine Learning \u00a0|\u00a0 Google for Developers

    "},{"location":"docs/3-dl/tools/nlp_resources/#machine-learning-technology","title":"Machine Learning Technology","text":"

    TODO

    "},{"location":"docs/3-dl/tools/nlp_resources/#deep-learning-theory","title":"Deep Learning Theory","text":"

    TODO

    "},{"location":"docs/3-dl/tools/nlp_resources/#deep-learning-technology","title":"Deep Learning Technology","text":"

    Pytorch\u6559\u7a0b\uff0c\u53ef\u4ee5\u770b\u7740\u4ee3\u7801\u624b\u6284\u4e00\u4e0b

    Welcome to PyTorch Tutorials \u2014 PyTorch Tutorials 2.0.1+cu117 documentation

    numpy: numpy 100 exercise

    rougier/numpy-100: 100 numpy exercises (with solutions) (github.com)

    Pytorch

    PyTorch\u6df1\u5ea6\u5b66\u4e60\u5feb\u901f\u5165\u95e8\u6559\u7a0b\uff08\u7edd\u5bf9\u901a\u4fd7\u6613\u61c2\uff01\uff09\u3010\u5c0f\u571f\u5806\u3011_\u54d4\u54e9\u54d4\u54e9_bilibili

    Attention-based Models and Transformer

    Let's build GPT: from scratch, in code, spelled out. - YouTube

    "},{"location":"docs/3-dl/tools/nlp_resources/#natural-language-processing-theory","title":"Natural Language Processing Theory","text":"

    Stanford CS224N: NLP with Deep Learning | Winter 2021 | Lecture 1 - Intro & Word Vectors - YouTube

    "},{"location":"docs/3-dl/tools/nlp_resources/#natural-language-processing-technology","title":"Natural language processing technology","text":"

    Stanford CS 224N | Natural Language Processing with Deep Learning

    "},{"location":"docs/3-dl/tools/nlp_resources/#reinforcement-learning","title":"Reinforcement Learning","text":"

    \u8611\u83c7\u4e66EasyRL (datawhalechina.github.io)

    Codes:

    boyu-ai/Hands-on-RL: https://hrl.boyuai.com/ (github.com) datawhalechina/easy-rl: \u5f3a\u5316\u5b66\u4e60\u4e2d\u6587\u6559\u7a0b\uff08\u8611\u83c7\u4e66\uff09\uff0c\u5728\u7ebf\u9605\u8bfb\u5730\u5740\uff1ahttps://datawhalechina.github.io/easy-rl/

    "},{"location":"docs/3-dl/tools/nlp_resources/#computer-vision","title":"Computer Vision","text":"

    Computer Vision | Universit\u00e4t T\u00fcbingen (uni-tuebingen.de)

    "},{"location":"docs/4-opinion/","title":"Opinions","text":"

    :material-circle-edit-outline: \u7ea6 1 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/plan/","title":"Academic Plans \u5b66\u4e1a\u89c4\u5212","text":"

    :material-circle-edit-outline: \u7ea6 27 \u4e2a\u5b57

    !!! \u672c\u7ae0\u8282 bullshits \u548c exaggerations \u542b\u91cf 200%\uff0c\u76f8\u4fe1\u524d\u4e00\u5b9a\u8c28\u614e\u8c28\u614e\u518d\u8c28\u614e

    "},{"location":"docs/4-opinion/plan/24fall/","title":"24fall \u7533\u8bf7\u8bb0\u5f55","text":"

    :material-circle-edit-outline: \u7ea6 5341 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 18 \u5206\u949f

    \u5199\u4e8e 2024 \u5e74 3 \u6708\u5e95\uff0c\u7ed3\u679c\u5dee\u4e0d\u591a\u51fa\u4e86\uff0c\u6839\u636e\u7ed3\u679c\u53cd\u601d\u4e0b\u5728\u7533\u8bf7\u8def\u7a0b\u4e2d\u505a\u5f97\u5bf9\u4e0e\u4e0d\u5bf9\u7684\u5730\u65b9\uff0c\u5e76\u603b\u7ed3\u4e00\u4e9b\u6709\u7528\u8d44\u6e90\uff0c\u5e0c\u671b\u53ef\u4ee5\u5e2e\u5230\u548c\u6211\u4e00\u6837\u7eaf DIY \u7533\u8bf7\u7684\u540c\u5b66\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#master","title":"master \u9009\u6821","text":"

    master \u9009\u9879\u76ee\u4e3b\u8981\u7ecf\u5386\u4e86\u201c\u6dfb\u52a0\u5fc3\u613f\u5355\u201d+\u201c\u7b5b\u9009\u201d\u4e24\u4e2a\u6d41\u7a0b\u3002

    \u201c\u6dfb\u52a0\u5fc3\u613f\u5355\u201d\u4e00\u6b65\u4e3b\u8981\u53c2\u7167 zju \u5185\u90e8\u7684\u98de\u8dc3\u624b\u518c + OpenCSApp + GlobalCS + \u5370\u8c61\uff08e.g. \u5b66\u957f\u5b66\u59d0\uff0c1p3a\uff09\u7b49\uff0c\u5148\u5217\u51fa\u5927\u7ea6\u4e09\u4e94\u5341\u4e2a\u5408\u9002\u7684\u9879\u76ee\u3002

    \u201c\u7b5b\u9009\u201d\u4e00\u6b65\u4e2d\u518d\u8003\u8651\u5404\u79cd\u9650\u5236\u6761\u4ef6\uff08\u6bd4\u5982\u6211\u7684\uff1a\u5b66\u8d39\u9ad8/\u5c31\u4e1a\u5bfc\u5411\u7684/\u4e0d\u5b89\u5168\u7684/\u5f3a\u5236\u8bed\u8a00\u7684\u4e0d\u7533\uff09\uff0c\u4ee5\u53ca\u6240\u6709\u7533\u5230\u4e5f\u4e0d\u60f3\u53bb\u7684\u90a3\u79cd\u4fdd\u5e95\u9879\u76ee\u4e5f\u65e0\u9700\u7533\u8bf7\u3002 \u5b66\u8d39\u53ef\u4ee5\u53c2\u7167\u7684\u8d44\u6599\u6bd4\u5982 Compare cost of living between cities \u548c\u5404\u4e2a\u9879\u76ee\u5b98\u65b9\u62a5\u7684\u6570\u76ee\u3002

    \u53e6\u5916\u5728 UCSD CS37 \u7684\u9879\u76ee\u9875\u9762\u770b\u8fc7\u201c\u5982\u679c\u786e\u5b9a\u7533\u8bf7 PhD\uff0c\u5c31\u4e0d\u8981\u7533\u8bf7 master \u4e86\u201d\uff0c\u53ef\u80fd\u80fd\u4ee3\u8868\u4e00\u90e8\u5206\u5b66\u6821\u8fd9\u4e24\u79cd\u9879\u76ee\u7684\u5b9a\u4f4d\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#phd","title":"PhD \u9009\u5bfc","text":"

    \u6211\u9996\u5148\u9760\u8ddf\u7ec4\u91cc\u540c\u884c\u8ba4\u8bc6\u7684\u5b66\u957f\u5b66\u59d0\u4ea4\u6d41\uff0c\u88ab\u63a8\u8350\u4e86\u4e00\u4e9b\u5f53\u5e74\u6b63\u5728\u62db\u751f\u7684\u4f18\u79c0 prof\u3002\u6b64\u5916\u81ea\u5df1\u4e3b\u8981\u53c2\u8003\u4e86 CSrankings\uff0c\u6328\u4e2a\u6253\u5f00 Google Scholar \u53bb\u8bfb\u6587\u7ae0\u3002\u4e5f\u6709\u53d1\u6325\u6211\u7684\u793e\u725b\u5c5e\u6027\u53bb X(twitter) \u4e0a\u628a\u5927\u5bb6\u90fd\u5173\u6ce8\u7136\u540e\u5237\u6587\u7ae0\u8fd9\u6837\u505a\u3002\u7ecf\u5e38\u5237 Arxiv \u4e5f\u662f\u597d\u4e60\u60ef\uff0c\u53ef\u60dc\u6211\u8fd8\u6ca1\u517b\u6210\u3002\u8fd9\u4e9b\u90fd\u6709\u5229\u4e8e\u773c\u719f\u6559\u6388\uff0c\u4e00\u6bb5\u65f6\u95f4\u540e\u5c31\u53ef\u5f62\u6210\u81ea\u5df1\u7684\u9009\u62e9\u3002

    \u53e6\u5916\u9009\u5b66\u6821\u65f6\u5982\u9700\u53c2\u8003 Stipend\uff1aCSStipendRankings\u3002

    \u6700\u7ec8 master + PhD \u6211\u4e00\u5171\u7533\u8bf7\u4e86\u4f3c\u4e4e\u662f 14 \u4e2a\uff08\u542b 3 \u4e2a\u514d\u8d39\uff09\u3002\u8fd9\u4e2a\u6570\u76ee\u56e0\u4eba\u800c\u5f02\uff0c\u4e3b\u8981\u770b\u4e0e\u63a8\u8350\u4eba\u6c9f\u901a\u3002\u8eab\u8fb9\u4e5f\u6709\u670b\u53cb\u7533\u5230 50 \u4e2a\u7684\uff0c\u60ca\u4eba\u4f46\u662f\u5c0a\u91cd\u7406\u89e3\u3002

    \u6700\u65b0\u5728 24fall \u7fa4\u91cc\u770b\u5230\u7684\u9009\u5bfc\u5e08\u7684\u5176\u5b83\u5de5\u5177

    "},{"location":"docs/4-opinion/plan/24fall/#_1","title":"\u8bed\u8a00\u6210\u7ee9","text":"

    \u5982\u679c\u7533\u8bf7 PhD\uff0c\u90a3\u4e48\u5927\u5bb6\u7684\u7ecf\u9a8c\u6765\u770b\u8fc7\u7ebf\u5c31\u591f\uff0c\u4e0d\u592a\u4f1a\u4e25\u5361\uff0c\u91cd\u70b9\u65e0\u9700\u5728\u8bed\u8a00\u6210\u7ee9\u3002

    master \u5219\u5e94\u8be5\u662f\u8bed\u8a00\u6210\u7ee9\u8d8a\u9ad8\u8d8a\u597d\u4e86\uff0c\u5c24\u5176\u5982\u679c\u7ee9\u70b9 below average\uff0c\u90a3\u4e48\u8bed\u8a00\u786e\u5b9e\u9700\u8981\u8003\u9ad8\u4e00\u4e9b\u3002

    \u4ee5\u53ca\u6211\u5728\u7533\u8bf7\u5b63\u7684\u51e0\u4e2a\u6708\u91cc\u4e00\u76f4\u6ca1\u80fd\u6253\u5f00 GRE \u7684\u5b98\u7f51\uff08\u4e0d\u662f\u5bc6\u7801\u4e0d\u6b63\u786e\uff0c\u5bc6\u7801\u901a\u8fc7\u53d1\u90ae\u4ef6\u5c31\u80fd\u627e\u56de\u6765\u4e86\uff0c\u662f\u767b\u5f55\u540e\u8df3\u8f6c\u53ea\u80fd\u5230 error \u9875\u9762\uff09\uff0c\u6362\u7f51\u6362\u8bbe\u5907\u6362\ud83e\ude9c\u90fd\u8fd8\u662f\u4e00\u76f4\u5237\u65b0\u4e0d\u51fa\u6765\uff0c\u5bfc\u81f4\u8003\u4e86\u4e5f\u6ca1\u6cd5\u67e5\u5206\uff0c\u6ca1\u6cd5\u591a\u6dfb\u52a0\u9001\u5206\u3002\u56e0\u4e3a\u4e3b\u8981\u76ee\u6807\u8fd8\u662f\u7533 PhD \u4e8e\u662f\u6700\u540e\u5c31\u4e0d\u518d\u6323\u624e\u4e86\u3002GRE \u5b98\u7f51\u662f\u7ecf\u5e38\u62bd\u98ce\u7684\uff0c\u770b\u5230\u8eab\u8fb9\u4e00\u4e9b master \u7533\u8bf7\u8005\u4f1a\u9009\u62e9\u5728\u5927\u4e09\u5c31\u628a GRE \u8003\u51fa\u6765\uff0c\u5efa\u8bae\u4e5f\u50cf\u4ed6\u4eec\u4e00\u6837\u63d0\u524d\u51c6\u5907\uff0c\u5982\u679c\u4e5f\u767b\u9646\u4e0d\u8fdb\u53bb\uff0c\u591a\u6c42\u52a9\u6c42\u52a9\u8eab\u8fb9\u7684\u4eba\u501f\u8bbe\u5907\u8bd5\u8bd5\uff0c\u6700\u597d\u63d0\u524d\u51c6\u5907\uff0c\u907f\u514d\u5230\u7533\u8bf7\u5b63\u53d1\u73b0\u5f71\u54cd\u9001\u5206\u3002

    \u9001\u5206 Code \u8fd8\u6709\u4e00\u4e9b\u5e16\u5b50\u603b\u7ed3\u8fc7\u7684\uff08\u53ef\u81ea\u884c\u641c\u7d22\uff09\uff0cTG \u90fd\u662f\u7528\u7684\u662f\u540c\u4e00\u4e2a\u9001\u5206 Code\uff0c\u4ee5\u53ca GRE \u5728\u8003\u573a\u91cc\u90a3\u6b21\u514d\u8d39\u9001\u5206\u673a\u4f1a\u4e0d\u7528\u80cc\u9001\u5206 Code\uff0c\u5728\u8003\u573a\u91cc\u4e5f\u53ef\u4ee5\u6309\u6821\u540d\u641c\u7d22\u6dfb\u52a0\u7684\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_2","title":"\u63a8\u8350\u4fe1","text":"

    \u63a8\u8350\u4fe1\u5982\u4f55\u88ab\u5ba1\u6838\uff1a\u636e\u8bf4\u4e00\u822c\u5728\u62db\u751f\u5b98\u624b\u91cc\uff0c\u63a8\u8350\u4fe1\u662f\u4e0e\u7533\u8bf7\u8005\u7684\u5176\u5b83\u6750\u6599\u4e00\u8d77\u62fc\u6210\u4e00\u957f\u4efd\u591a\u9875 PDF \u4e00\u8d77\u88ab\u5ba1\u6838\u7684\uff0c\u51e0\u4efd\u63a8\u8350\u4fe1\u524d\u540e\u5e76\u5217\u3002\u6240\u4ee5\u5173\u4e8e\u201c\u98ce\u683c\u660e\u663e\u4e0d\u660e\u663e\u201d\u201c\u5f3a\u5ea6\u660e\u663e\u4e0d\u660e\u663e\u201d\u201c\u4f1a\u5ba1\u6587\u4ef6\u4fe1\u606f\u201d\u7b49\u95ee\u9898\u53ef\u4ee5\u60f3\u8c61\u4e00\u4e0b\u5ba1\u6750\u6599\u7684\u8fd9\u4e2a\u573a\u666f\uff0c\u4ece\u8fd9\u4e2a\u89d2\u5ea6\u6765\u8003\u8651\u3002

    \u5173\u4e8e\u627e\u591a\u4f4d\u63a8\u8350\u4eba\uff1a\u5927\u7ea6 12.2 \u53f7\u770b\u5230 PhD \u7533\u8bf7\u7fa4\u91cc\u6709\u4eba\u8bf4\uff0c\u5176\u5b9e\u4e0d\u8981\u627e 3 \u4e2a\u63a8\u8350\u4eba\u5c31\u7ed3\u675f\uff0c\u6700\u597d\u63d0\u524d\u627e 4 \u5230 5 \u4e2a\uff0c\u56e0\u4e3a\u591a\u4ea4\u6ca1\u6709\u5173\u7cfb\uff0c\u5927\u90e8\u5206\u5b66\u6821\u90fd\u6709\u6dfb\u52a0\u591a\u4e2a\u63a8\u8350\u4eba\u7684\u9009\u9879\uff08\u6211\u7684\u9009\u6821\u91cc\u53ea\u6709loo\u548cumich\u4e0a\u9650\u4e09\u4e2a\uff09\uff0c\u4f46\u662f\u7ecf\u5e38\u6709\u63a8\u8350\u4eba\u5fd9\u5fd8\u4e86\u6700\u540e\u6ca1\u4ea4\u7684\u60c5\u51b5\u3002\u518d\u95ee\u53e6\u4e00\u4e2a\u7fa4\uff0c\u5f97\u77e5\u5982\u679c\u662f US PhD\uff0c\u4e0d\u4f1a\u56e0\u4e3a\u6709\u4e00\u4e2a\u63a8\u8350\u4eba\u5fd8\u4e86\u4ea4\u62d2\u4f60\uff0c\u4f46\u662f\u5927\u591a master 3 \u5c01\u4ea4\u4e0d\u9f50\u5c31\u65e0\u6cd5\u5f00\u59cb\u5ba1\u6750\u6599\uff0c\u53ef\u80fd\u56e0\u6b64\u4e00\u76f4\u7559\u5728\u6c60\u5b50\u91cc\uff0c\u6216\u8005\u53ef\u80fd\u56e0\u6b64\u9ed8\u62d2\u3002\u4e5f\u6709\u542c\u8bf4\u5982\u679c\u672c\u8be5\u4ea4 3 \u5c01\u4ea4\u4e86 4 \u5c01\uff0c\u53ef\u80fd\u56e0\u6b64\u964d\u4f4e\u5176\u4e2d\u6700\u91cd\u8981\u7684\u90a3\u5c01\u7684\u6548\u529b\uff0c\u8fd9\u70b9\u5982\u679c\u6536\u5230 >3 \u5c01\u63a8\u8350\u4fe1\u5176\u5b9e\u53ef\u4ee5\u901a\u8fc7 exclude \u4e00\u4efd\u6765\u89e3\u51b3\uff0c\u7ecf\u9a8c\u6765\u770b\u70b9 exclude \u65f6\u63a8\u8350\u4eba\u5e94\u8be5\u4e0d\u4f1a\u6536\u5230\u901a\u77e5\u3002

    \u540c\u4e00\u5b66\u6821\u53ef\u4ee5\u5171\u7528\u63a8\u8350\u4fe1\u5417: \u4e00\u822c\u4e0d\u80fd\u3002\u6211\u7533\u8bf7\u7684\u5b66\u6821\u4e2d\u53ef\u4ee5\u7684\u6709

    \u63a8\u8350\u4fe1\u7cfb\u7edf\u4e0d\u5927\u667a\u80fd\u7684\u5730\u65b9:

    \u542c\u8bf4\u8fc7\u67e5 IP/MAC \u5730\u5740\u7684: \u76ee\u524d\u5927\u8305\u548c\u54e5\u5927\u6709\u89c1\u8fc7 DP \u6536\u5230\u5b66\u6821\u90ae\u4ef6\u8bf4\u67e5\u5230\u4fe1\u662f\u81ea\u5df1\u53d1\u7684\u3002\u636e\u6b64\u770b\u6765\u662f\u4e0d\u662f\u85e4\u6821\u4e25\u4e00\u4e9b\u3002IP/MAC addr \u5982\u679c\u67e5\u5e94\u8be5\u662f\u989d\u5916\u67e5\u7684\uff0c\u4e0d\u662f\u5ba1\u6750\u6599\u7684\u62db\u751f\u5b98\u8d1f\u8d23\u67e5\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_3","title":"\u5957\u74f7","text":"

    \u4e00\u5f00\u59cb\u770b\u5230\u7684\u6d88\u606f\u662f\u5957\u5230\u74f7\u624d\u80fd\u7533\u8bf7\uff0c\u540e\u6765\u770b\u5230 n+e's blog \u77e5\u9053\u4e5f\u4e0d\u4e00\u5b9a\uff0c\u5148\u6295\u4e86\u518d\u5957\u4e5f\u53ef\u4ee5\uff0c\u6709\u4e9b\u6559\u6388\u7279\u522b\u5fd9\uff0c\u53ef\u80fd\u62c5\u5fc3\u6709\u4e9b\u5b66\u751f\u804a\u4e86\u4e5f\u6ca1\u6295\uff0c\u53ef\u80fd\u503e\u5411\u5b66\u751f\u786e\u5b9e\u6295\u4e86\u518d\u804a\uff0c\u6216\u8005\u7b49\u5230\u4ed6\u4eec\u81ea\u5df1\u4ece\u6c60\u5b50\u91cc\u635e\u4eba\u7684\u65f6\u95f4\u7ebf\u518d\u804a\u3002\u4e5f\u53ef\u4ee5\u53c2\u8003\u5f3a prof \u548c\u5f3a committee \u5b66\u6821\u7684\u4e00\u4e9b\u540d\u5355\uff08\u76ee\u524d\u770b\u5230\u4e00\u4e2a CS PhD\u5f3acommittee&\u5f3aprofessor List(\u4ec5\u4f9b\u53c2\u8003) \u4e0d\u8fc7\u4e0d\u4e00\u5b9a\u5f88\u51c6\uff0c\u5370\u8c61\u4e2d\u91cc\u9762\u8bf4\u662f\u5f3a committee \u7684\u4e00\u4e9b\u4e5f\u6709\u4e0e prof \u804a\u597d\u5c31\u5f55\u4e86\u7684 DP\uff09\u3002

    double \u7684\u7fa4\u91cc\u8fd8\u6709\u4e2a\u670b\u53cb\u505a\u4e86\u4e2a\u533f\u540d google docs \u4f9b\u7fa4\u53cb\u5206\u4eab\u62ff\u5230\u9762\u8bd5\u7684\u5927\u81f4\u65f6\u95f4\u6bb5\uff0c\u5171\u4eab\u5404\u5b66\u6821\u9762\u8bd5\u53d1\u5230\u4ec0\u4e48\u8fdb\u5ea6\u4e86\uff0c\u53ef\u60dc\u8be5\u8868\u683c\u4e0d\u5e0c\u671b\u88ab\u5916\u4f20\u3002\u4ee5\u540e\u7684\u7533\u8bf7\u7fa4\u91cc\u5927\u5bb6\u4e5f\u53ef\u4ee5\u81ea\u53d1\u521b\u5efa\u4e00\u4e2a\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_4","title":"\u7f51\u7533","text":"

    \u5bfb\u627e\u7f51\u7533\u9875\u9762\u7684\u901a\u7528\u505a\u6cd5\u4e00\u822c\u662f\u641c\u7d22\u5f15\u64ce\u641c\u7d22 \u5b66\u6821\u548c program \u540d\u5b57 + application\uff0c\u7ed3\u679c\u524d\u51e0\u6761\u4e2d\u4e00\u822c\u5c31\u542b\u6b63\u786e\u7684\u7533\u8bf7\u754c\u9762\u3002\u7f51\u7533\u5185\u5bb9\u611f\u89c9\u8fd8\u662f\u9700\u8981\u81ea\u5df1\u586b\uff0c\u4e0d\u8981\u627e\u4ee3\u586b\uff0c\u4fe1\u606f\u5f88\u591a\uff0c\u975e\u672c\u4eba\u4e0d\u719f\u6089\u592a\u5bb9\u6613\u586b\u9519\u4e86\u3002

    \u4e0b\u9762\u8bb0\u5f55\u4e00\u4e9b program-specific \u7684\u5751\u70b9\u3002

    CMU: \u5982\u679c\u76f4\u63a5\u641c\u7d22 MLT application \u51fa\u73b0\u7684\u4ee5\u4e0b\u9875\u9762\u53ca\u7533\u8bf7\u94fe\u63a5\u662f\u627e\u4e0d\u5230MLT\u9879\u76ee\u7684

    Application Management (cmu.edu) \u8fd9\u4e2a\u9875\u9762\u548c\u4ee5\u4e0b\u622a\u56fe\u662f\u6b63\u786e\u7684\uff0c\u540c\u7406mscv\u548cmsaii\u4ec0\u4e48\u7684\u9879\u76ee\u4e5f\u5728\u8fd9\u91cc\u7533\u8bf7\u3002

    mscs \u7684 video essay \u662f\u63d0\u524d\u5f55\u597d\u4e86\u4e0a\u4f20\u5230 youtube \u8fd9\u79cd\u7684\uff0c\u53ef\u4ee5\u81ea\u5df1\u968f\u610f\u5f55\u591a\u6b21\uff0c\u4f46\u6211\u4f30\u8ba1\u4e0d\u8981\u62fc\u63a5\u75d5\u8ff9\u592a\u91cd\uff0c\u4e00\u53e3\u6c14\u8bf4\u4e0b\u6765\u6700\u597d\u3002\u5185\u5bb9\u6211\u8bb0\u5f97\u6ca1\u6709\u9650\u5236\uff0c\u968f\u610f\u8bbe\u8ba1\u81ea\u6211\u4ecb\u7ecd\uff0c\u636e\u8bf4\u4e3b\u8981\u662f\u4e3a\u4e86\u770b\u7533\u8bf7\u4eba\u6027\u683c\u3001\u53e3\u8bed\u3001\u8868\u8fbe\u80fd\u529b\u4e4b\u7c7b\u7684\u6f5c\u5728\u7279\u70b9\u3002

    \u5728\u7ec6\u5206\u7684\u90a3\u51e0\u4e2a ai \u9879\u76ee\u7684 video earry \u662f\u9650 3 \u6b21\u673a\u4f1a\uff0c\u6bcf\u6b21\u968f\u673a\u95ee\u9898\uff0c\u9650\u65f6\u51c6\u5907\uff0c\u9650\u65f6\u8bf4\u3002\u6211\u770b\u5230\u7684\u7f51\u4e0a\u7684\u5e16\u5b50\u8bf4\u597d\u50cf miis ini ece\uff08\u8bb0\u4e0d\u4f4f\u8fd9\u51e0\u4e2a\u9879\u76ee\u540d\u5b57\uff0c\u603b\u4e4b\u7c7b\u4f3c\uff09\u662f 30s \u51c6\u5907\uff0c180s \u8bf4\uff0c\u95ee\u7684\u95ee\u9898\u5927\u7c7b\u6709\uff1a\u4f60\u961f\u53cb\u600e\u4e48\u8bc4\u4ef7\u4f60\uff0c\u4f60\u6536\u5230\u7684\u961f\u53cb\u7684\u4e00\u6761\u8d1f\u9762\u8bc4\u4ef7\u662f\uff0c\u4f60\u600e\u4e48\u9886\u5bfc project\uff0c\u4e00\u4e2a\u6210\u529f\u7684 project \u5bf9\u4f60\u6765\u8bf4\u662f\u600e\u6837\u7684\uff0c\u4f60\u559c\u6b22\u4ec0\u4e48\u6c9f\u901a\u6a21\u5f0f\uff0c\u5bf9\u4f60\u6765\u8bf4\u4ec0\u4e48\u662f\u5f88\u96be\u505a\u7684\u51b3\u5b9a\uff0c\u4f60\u9047\u5230\u632b\u6298\u4e86\u4f1a\u600e\u4e48\u6837...\u8fd9\u79cd\u5f88\u8ddf course project \u548c\u5408\u4f5c\u6709\u5173\u7684\u3002

    \u4f46\u662f\u6211\u5728 mlt \u91cc\u6253\u5f00\u9047\u5230\u7684\u662f 10s \u51c6\u5907\uff0c210s \u8bf4\uff0c\u9047\u5230\u7684\u4e24\u4e2a\u95ee\u9898\u4f9b\u53c2\u8003:

    \u8fd9\u6837\u5f88\u7814\u7a76\u5bfc\u5411\u7684\u95ee\u9898\uff0c\u4e00\u822c\u90fd\u6765\u81ea SoP\u3002

    UWaterloo: \u7533\u8bf7\u5206\u4e3a\u4e24\u4e2a\u9636\u6bb5\uff0c\u7b2c\u4e00\u4e2a\u9636\u6bb5\u91cc\u4ea4\u6389\u624d\u80fd\u5728\u7b2c\u4e8c\u4e2a\u9636\u6bb5\u4e0a\u4f20 cv \u6587\u4e66 \u8bed\u8a00\u6210\u7ee9\u7b49\u4e1c\u897f\uff0c\u7b2c\u4e8c\u9636\u6bb5\u7684\u94fe\u63a5\u4f1a\u5728\u7b2c\u4e00\u9636\u6bb5\u540e 2-4 \u5929\u6536\u5230\u3002\u7533\u8bf7\u8d39\u5728\u7b2c\u4e00\u9636\u6bb5\u4ea4\u3002\u63a8\u8350\u4eba\u5728\u7b2c\u4e00\u9636\u6bb5\u6dfb\u52a0\uff0c\u90ae\u4ef6\u968f\u7740\u7b2c\u4e00\u9636\u6bb5\u63d0\u4ea4\u88ab\u53d1\u51fa\u3002\u7b2c\u4e00\u4e2a\u9636\u6bb5\u4e00\u5b9a\u8981\u6bd4 ddl \u63d0\u524d\u4e24\u4e09\u5929\u4ea4\u3002\u4e14 loo \u7684\u7cfb\u7edf\u597d\u50cf\u7ef4\u62a4\u6bd4\u8f83\u9891\u7e41\uff0c\u53ef\u4ee5\u591a\u9884\u7559\u4e00\u4e9b\u65f6\u95f4\u3002

    UT-Austin: \u540c\u7533\u8bf7\u5206\u4e3a\u4e24\u4e2a\u9636\u6bb5\uff0c\u7b2c\u4e00\u4e2a\u9636\u6bb5\u4ed8\u6b3e\uff0c\u5ba1\u6838 1-3 \u5929\u540e\u624d\u80fd\u5f00\u59cb\u7b2c\u4e8c\u4e2a\u9636\u6bb5\uff08\u542b\u6dfb\u52a0\u63a8\u8350\u4eba\u7b49\uff09\u3002\u7b2c\u4e00\u9636\u6bb5\u63d0\u4ea4\u4e00\u5b9a\u8981\u6bd4 ddl \u65e9\u4e24\u4e09\u5929\u3002

    Umich\uff1a\u7f51\u7533\u7cfb\u7edf\u4e00\u5f00\u59cb\u56db\u4e94\u4e2a\u9875\u9762\u8981\u987a\u5e8f\u586b\u5b8c\uff08\u5305\u62ec\u6dfb\u52a0\u63a8\u8350\u4eba\u7684\u90e8\u5206\uff09\uff0c\u540e\u9762\u7684\u9875\u9762\u624d\u80fd\u8df3\u7740\u586b\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_5","title":"\u6587\u4e66","text":"

    \u6211\u5199\u6587\u4e66\u4e3b\u8981\u53c2\u7167\u7684\u8d44\u6599\u6709 CS-SOP, CMU sop guideline, \u548c\u4e24\u4e09\u4f4d\u5b66\u957f\u5b66\u59d0\u548c peer \u7684\u4fee\u6539\u610f\u89c1\u3002

    CV \u6211\u8ba4\u4e3a\u4e00\u822c\u5927\u5bb6\u505a\u51fa\u6765\u7684\u90fd\u6ca1\u95ee\u9898\uff0c\u5c11\u91cf\u503c\u5f97 comment \u7684\u4e00\u4e9b\u70b9\u6709\uff1a

    SOP

    SOP \u53ef\u4ee5\u7406\u89e3\u4e3a\u5173\u4e8e\u81ea\u5df1\u5b66\u672f\u7ecf\u5386\u548c\u8ba1\u5212\u7684\u4e00\u4efd\u6587\u4e66\u3002\u7ecf\u9a8c\u6765\u770b\u5982\u679c\u4e00\u4e9b\u5b66\u6821\u53ea\u8981\u6c42 PS \u4e0d\u8981\u6c42 SOP\uff0c\u90a3\u4e48 PS \u5e94\u5f53\u5f53\u4f5c\u4e00\u4e2a\u683c\u5f0f\u4e0d\u90a3\u4e48\u4e25\u683c\u7684 SOP \u6765\u5199\u3002

    \u6240\u6709\u9879\u76ee\u7684\u6587\u4e66\u52a0\u8d77\u6765\u5927\u7ea6\u751f\u4ea7\u4e86\u8fd1 20 \u4efd\uff0c\u5176\u4e2d\u5982\u679c\u5185\u5bb9\u76f8\u4f3c\u7684\u5408\u5e76\u4e3a\u540c\u4e00\u4efd\uff0c\u90a3\u5927\u6982\u4e5f\u6709\u516d\u4e03\u4efd\u5b8c\u5168\u4e0d\u540c\u7684\u3002\u4e00\u4e2a\u6709\u70b9\u7384\u5b66\u7684\u611f\u89c9\u662f\u6211\u4e13\u95e8\u4e3a\u5176\u5199\u4e86\u4e00\u4efd\u65b0\u6587\u4e66\u7684\u9879\u76ee\uff0cPhD \u5bfc\u5e08\u5c31\u53d1\u4e86\u9762\u8bd5\uff0cmaster \u5c31\u53d1\u4e86 offer\uff0c\u800c\u4ece\u522b\u7684\u9879\u76ee\u6539\u6539\u800c\u6765\u7684\u90a3\u4e9b\u4e00\u5b9a\u6ca1\u6709\u53d1\u9762\u8bd5/\u62ff offer\u3002\u6709\u53ef\u80fd\u56e0\u679c\u5173\u7cfb\u6709\u201c\u6211\u611f\u89c9\u4e0d\u4f1a\u4e2d/\u4e0d\u662f\u7279\u522b\u5408\u9002\u201d -> \u201c\u56e0\u6b64\u66f4\u52a0\u6ca1\u6709\u8ba4\u771f\u51c6\u5907\u6587\u4e66\u201d -> \u201c\u56e0\u6b64\u5f53\u7136\u62ff\u4e0d\u5230\u201d\u8fd9\u4e00\u5c42\u3002

    \u4e00\u822c\u662f\u81ea\u5df1\u62df\u597d\u8349\u7a3f\u540e\u4ea4\u7ed9\u5b66\u957f\u5b66\u59d0\u6216 peer \u6765\u6539\uff0c\u540e\u6765\u8d76 ddl \u5927\u5bb6\u90fd\u6bd4\u8f83\u5fd9\uff0c\u6709\u4e9b\u5c31\u81ea\u5df1\u5199\u597d\u76f4\u63a5\u4ea4\u4e86\u3002\u5012\u662f\u89c9\u5f97\u81ea\u5df1\u5199\u5b8c\u6709\u6ca1\u6709\u627e\u4eba review \u8fd9\u70b9\u5bf9\u7ed3\u679c\u7684\u5f71\u54cd\u6ca1\u6709\u5f88\u5927\uff0cPhD \u5bfc\u5e08\u4eec\u4e5f\u8868\u793a\u770b\u91cd\u7684\u66f4\u591a\u662f\u65b9\u5411 match \u4e0d match\uff0c\u4fe1\u606f\u8868\u8fbe\u6b63\u786e\u5230\u4f4d\u662f\u6700\u91cd\u8981\u7684\uff0c\u8bed\u8a00\u7f8e\u5316\u5012\u5728\u5176\u6b21\u3002\u4e14\u4e00\u4e9b\u5b66\u6821\uff08Waterloo, UW, Uchi\uff09\u6587\u4e66\u4e5f\u4f1a\u9650\u5236 500/1000 words\uff0c\u8fd9\u6837\u77ed\u7684\u9650\u5236\u91cc\u786e\u5b9e\u8868\u8fbe\u4e0d\u4e86\u591a\u5c11\uff0c\u4e5f\u8bf4\u660e\u4f20\u8fbe\u4fe1\u606f\u662f\u7b2c\u4e00\u4f4d\u7684\u3002\u81ea\u5df1\u5199\u4e5f\u6709\u4e00\u5957\u6bd4\u8f83\u9ad8\u6548\u7684\u6d41\u7a0b\uff0c\u7075\u611f\u6765\u6e90\u4e8e\u5927\u4e00\u4e0a EW1 \u7684\u9b54\u9b3c\u5916\u6559\u8001\u5e08\u8bb2\u7684 shitty first draft \u6982\u5ff5\uff1a\u7b2c\u4e00\u7a3f\u96be\u4e0b\u624b\u5e38\u5e38\u662f\u56e0\u4e3a\u60f3\u8981\u540c\u65f6\u517c\u987e\u4fe1\u606f\u548c\u8868\u8fbe\uff0c\u90a3\u4e48\u628a\u4e24\u4ef6\u4e8b\u62c6\u5f00\uff0c\u7b2c\u4e00\u7a3f\u5148\u4e00\u53e3\u6c14\u5199\u51fa\u4e2a\u8868\u8fbe\u4fe1\u606f\u5168\u9762\u6b63\u786e\u4f46\u7528\u8bed\u975e\u5e38 shitty \u7684\u6587\u7ae0\uff0c\u7b2c\u4e8c\u7a3f\u53ea\u987e\u4f18\u5316\u8868\u8fbe\uff0c\u90a3\u5c31\u4e0d\u4f1a\u5361\u58f3\u3002\u6211\u5199\u7684\u6d41\u7a0b\u4e5f\u5927\u81f4\u662f\u8fd9\u6837\uff0c\u5148\u628a\u6240\u6709\u60f3\u8868\u8fbe\u7684\u4fe1\u606f\u5410\u51fa\u6765\uff0c\u5f62\u6210\u4e00\u7bc7\u81f3\u5c11\u957f\u5f97\u50cf\u6587\u7ae0\u7684\u6587\u7ae0\uff08\u4f46\u751a\u81f3\u4e0d\u4f1a\u987e\u53ca\u7528\u4ec0\u4e48\u8bed\uff0c\u7ecf\u5e38\u4e00\u534a\u82f1\u8bed\u4e00\u534a\u4e2d\u6587\uff09\uff0c\u7136\u540e\u4e00\u6bb5\u4e00\u6bb5\u8f93\u5165 ChatGPT \u8bf7\u5b83 \"please refine this paragraph from a {\u6587\u4f53} for me: {paragraph}\"\uff0c\u518d\u4e00\u53e5\u4e00\u53e5\u6bd4\u5bf9 ChatGPT \u8f93\u51fa\u7ed3\u679c\u4e0e\u81ea\u5df1\u7684\u5199\u4f5c\uff0c\u624b\u52a8\u628a\u4e00\u4e2a\u89c9\u5f97\u66f4\u597d\u7684\u7ed3\u679c\u6572\u56de\u5230\u6587\u7ae0\u4e2d\uff08\u8fd9\u91cc\u6211\u4e2a\u4eba\u8ba4\u4e3a\u8fc7\u4e00\u904d\u8111\u5b50\u540e\u4eb2\u81ea\u51b3\u5b9a\u600e\u4e48\u6539\u662f\u6bd4\u76f4\u63a5\u590d\u5236\u66f4\u9ad8\u6548\u66f4\u660e\u667a\u7684\u65b9\u6cd5\uff0c\u56e0\u4e3a ChatGPT \u5bf9\u4e8e\u7533\u8bf7\u6587\u4e66\u7c7b\u7684\u6587\u4f53\u5e38\u5e38\u6709\u4e00\u5957\u7279\u522b\u56fa\u5b9a\u4e14\u5b98\u65b9\u7684\u7528\u8bcd\uff0c\u4f7f\u5176\u4e0d\u592a\u5408\u9002\u4e14\u592a\u5bb9\u6613\u8bc6\u522b\u51fa\u662f\u673a\u5668\u5199\u7684\uff09\u3002\u6700\u540e\u628a\u8fd9\u904d\u81ea\u5df1\u6539\u8fc7\u7684\u5199\u4f5c\u8fc7\u4e00\u904d grammarly \u68c0\u67e5\u8bed\u6cd5\uff0c\u7b80\u5355\u68c0\u67e5\u540e\u5c31\u57fa\u672c\u53ef\u4ee5\u5b9a\u7a3f\u4e86\u3002

    \u6b64\u5916\u8fd8\u6709\u4e00\u70b9\u662f\uff0c\u6211\u4e2a\u4eba\u8ba4\u4e3a\u5728\u5ba1\u6587\u4e66\u65f6\u6bcf\u4efd\u6587\u4e66 5-10 \u5206\u949f\uff0c\u53ef\u80fd\u6240\u6709\u4eba\u80fd\u4e00\u773c\u770b\u5230\u7684\u662f (1) \u5c0f\u6807\u9898 (2) \u52a0\u7c97\u7684\u5173\u952e\u8bcd\uff0c\u6700\u540e\u624d\u4f1a\u7ec6\u770b\u5927\u91cf\u666e\u901a\u6587\u5b57\u3002\u4e00\u4e2a\u4f8b\u5b50\u662f\u6211\u4e0a\u6b21\u53c2\u52a0\u4e00\u95e8\u8bfe\u7684 group tutorial \u65f6\uff0c\u5f53\u65f6\u5c0f\u7ec4\u6210\u5458\u5408\u5199\u4e86\u4e00\u4efd rp\uff0c\u5176\u4e2d\u6211\u5199\u7684\u662f\u6700\u6666\u6da9\u7684 lit review\uff0c\u5373\u4e13\u4e1a\u672f\u8bed\u5bc6\u5ea6\u6700\u9ad8\u8fd8\u53e5\u5b50\u6700\u957f\uff0c\u4f46\u662f\u6211\u7ed9\u6bcf\u4e2a\u5206\u4e3b\u9898\u52a0\u4e86\u5c0f\u6807\u9898\uff0c\u5176\u5b83\u540c\u5b66\u5199\u7684\u90e8\u5206\u6ca1\u6709\u52a0\u3002\u8001\u5e08\u5728\u4e0e\u6211\u4eec\u8c08\u8bdd\u7684\u95f4\u9699\u7784\u4e86\u51e0\u773c\u6211\u4eec\u7684\u6587\u4ef6\uff0c\u77ed\u77ed\u7684\u65f6\u95f4\u91cc\u5c31\u53ea\u770b\u8fdb\u53bb\u4e86 lit review \u7684\u5c0f\u6807\u9898\uff0c\u70b9\u8bc4\u4e86\u4e00\u4e0b\u8fd9\u90e8\u5206\u3002\u56e0\u6b64\u505a\u6e05\u6670\u7684\u5206\u6bb5\u548c\u5c0f\u6807\u9898\u5f88\u91cd\u8981\uff08\u8fd9\u91cc\u771f\u7684\u6709\u70b9\u50cf\u8bbe\u8ba1\u56db\u539f\u5219\uff0c\u5bf9\u6bd4/\u805a\u5408\uff09\uff0c\u5c24\u5176\u662f\u65f6\u95f4\u7cbe\u529b\u4e0d\u591f\u65f6\uff0c\u5176\u4e2d\u7684\u7ec6\u8282\u5185\u5bb9\u8bf4\u4e0d\u5b9a\u4e0d\u7528\u62a0\u592a\u7ec6\uff0c\u53ef\u80fd\u62db\u751f\u5b98\u548c prof \u5728\u77ed\u6682 review \u7684\u65f6\u95f4\u91cc\u6355\u6349\u5230\u7684\u4fe1\u606f\u4e5f\u53ea\u6709\u5c11\u91cf\u6700\u663e\u773c\u7684\u3002\u56e0\u6b64\u6211\u7684\u6bcf\u4efd\u6587\u4e66\u90fd\u505a\u4e86\u52a0\u7c97 \\noindent \u8fd9\u6837\u7684\u5c0f\u6807\u9898\u6765\u5f15\u5bfc\u62db\u751f\u5b98\uff0c\u4e0d\u77e5\u9053\u5408\u4e0d\u5408\u89c4\uff0c\u4f46\u662f\u5e94\u8be5\u4e5f\u6ca1\u6709\u89c4\u77e9\uff0c\u4e14 CS-SOP \u4e0a\u4e0d\u5c11\u6587\u4e66\u4e5f\u662f\u8fd9\u6837\u52a0\u5c0f\u6807\u9898\u5199\u7684\uff0c\u6211\u8ba4\u4e3a\u8fd9\u6837\u6bd4\u8f83\u6709\u5229\u6240\u4ee5\u5c31\u8fd9\u6837\u505a\u597d\u4e86\u3002

    \u9644\u81ea\u5df1\u9605\u8bfb CS-SOP \u540e\u5199\u81ea\u5df1\u7684 SOP \u524d\uff0c\u7ed9\u81ea\u5df1\u5199\u7684\u7ed3\u6784\u6307\u5bfc

    \u6211\u5728\u5199\u6587\u4e66\u4e4b\u524d\uff0c\u4e00\u76f4\u8ba4\u4e3a\u6211\u7684\u8fc7\u53bb\u7814\u7a76\u7ecf\u5386\u4e0e\u6211\u672a\u6765\u7684\u76ee\u6807\u65b9\u5411\u4e0d\u76f8\u4f3c\uff0c\u4f46\u662f\u6700\u540e push \u81ea\u5df1\u5fc5\u987b\u53bb\u5bfb\u627e\u4e00\u4e2a\u5e73\u8861\u70b9\uff0c\u5bfb\u627e\u80fd\u628a\u5b83\u4eec\u90fd\u6982\u62ec\u4f4f\u7684\u4e24\u4e09\u4e2a\u5c0f\u6807\u9898\u3002\u8fd9\u4e24\u4e09\u4e2a\u5c0f\u6807\u9898\u7684\u9009\u62e9\u9996\u5148\u8981\u670d\u52a1\u4e8e\u672a\u6765\u65b9\u5411\uff0c\u7136\u540e\u56e0\u4e3a\u8fc7\u53bb\u7684\u6bcf\u4e2a\u9879\u76ee\u4e0d\u53ef\u80fd\u53ea\u6709\u4e00\u4e2a\u5c5e\u6027/\u9886\u57df\uff0c\u53ef\u4ee5\u9009\u62e9\u80fd\u591f\u670d\u52a1\u4e8e\u672a\u6765\u65b9\u5411\u7684\u65b9\u9762\u6765\u652f\u6491\u8fd9\u4e9b\u5c0f\u6807\u9898\uff0c\u7528\u201c\u6211\u53d7\u5230\u4e86 xx \u65b9\u9762\u7684\u542f\u53d1\u201d\u201c\u5728\u505a\u8be5\u9879\u76ee\u7684\u65f6\u5019\u4e00\u76f4\u5728\u601d\u8003\u67d0\u65b9\u9762\u4e0d\u8db3\u201d\u4e4b\u7c7b\u7684\u8bdd\u8fde\u63a5\u8d77\u6765\u3002\u6700\u540e\u7684\u611f\u609f\u662f\u5199\u4f5c\u6587\u4e66\u7684\u8fc7\u7a0b\uff08\u63cf\u8ff0\u81ea\u5df1\u7684\u8fc7\u7a0b\uff09\u5373\u8ba4\u8bc6\u548c\u5b9a\u4e49\u81ea\u5df1\u8fc7\u53bb\u7684\u7814\u7a76\u7684\u8fc7\u7a0b\uff0c\u611f\u89c9\u5199\u5b8c\u540e\u6211\u5bf9\u4e4b\u524d\u7814\u7a76\u7684\u8ba4\u8bc6\u4e5f\u786e\u5b9e\u53d8\u6210\u4e86\u8fde\u8d2f\u7684\u4e00\u4e2a\u6574\u4f53\uff0c\u4e14\u4ea7\u751f\u4e86\u4e00\u4e9b\u5bf9\u672a\u6765\u7814\u7a76\u7684\u542f\u53d1\u3002

    \u4ee5\u53ca\u90e8\u5206\u9879\u76ee\u4e5f\u4f1a\u5728\u7f51\u7533\u9875\u9762\u7ed9\u51fa\u6587\u4e66\u5199\u4f5c\u6307\u5bfc\uff08e.g. UCSD, CMU\uff09\uff0c\u53ef\u7559\u610f\u9605\u8bfb\u8fd9\u4e9b\u6307\u5bfc\uff0c\u6309\u5177\u4f53\u9879\u76ee\u7684\u6765\u589e\u5220\u6539\u3002

    PS

    \u5982\u4e0a\u6587\u63d0\u5230\uff0c\u5982\u679c\u90e8\u5206\u5b66\u6821\u53ea\u8981\u6c42\u4e00\u4efd PS\uff0c\u90a3\u4e48\u5e94\u5f53\u662f\u9700\u8981\u5f53\u4f5c SOP \u6765\u5199\u5b66\u672f\u548c\u804c\u4e1a\u5185\u5bb9\u7684\u3002\u6211\u662f\u8fd9\u6837\u89c4\u5212\u7ed3\u6784\u7684\uff1a

    \u5982\u679c PS \u548c SOP \u540c\u65f6\u9700\u8981\uff0c\u90a3\u4e48 PS \u7528\u6765\u8bb2\u6545\u4e8b\u6bd4\u8f83\u597d\u3002\u6211\u6ca1\u6709\u8bbe\u8ba1\u4e00\u4efd\u901a\u7528\u7684\u6545\u4e8b\uff0c\u57fa\u672c\u662f\u770b\u9879\u76ee\u8981\u6c42\u3001\u5f55\u53d6\u504f\u597d\u7136\u540e\u5199\u5bf9\u5e94\u7684\u6545\u4e8b\uff0c\u6bd4\u5982 NEU MSCS \u6211\u5199\u4e86\u4e00\u7bc7\u201c\u81ea\u5df1\u5982\u4f55\u4e00\u76f4\u559c\u6b22 cs \u5e76\u4e00\u70b9\u4e00\u70b9\u505a\u5f00\u6e90\u9879\u76ee\u201d\u7684\u6545\u4e8b\uff0cRice \u8ba9\u5199\u4e00\u4e2a\u514b\u670d\u56f0\u96be\u7684\u6545\u4e8b\uff0c\u6211\u5c31\u5199\u6211\u53d7\u5230\u4e86\u4e00\u4e9b\u4e13\u4e1a\u6b67\u89c6\u4f46\u8fd8\u662f\u52aa\u529b\u53bb\u53c2\u4e0e CS \u8bfe\u7a0b\u548c\u793e\u7fa4\u7684\u7ecf\u5386\u3002\u8fd9\u4e24\u6bb5\u90fd\u662f\u6bd4\u8f83\u4e2a\u4eba\u5316\uff0c\u6709\u70b9 emotional\uff0c\u4f46\u662f\u4e3b\u9898\u53c8\u8ddf\u4e2a\u4eba\u54c1\u8d28\u548c\u5b66\u4e1a\u6709\u5173\u7684\uff0c\u6839\u636e\u9762\u8bd5\u6216 offer \u7b49\u9014\u5f84\u7684\u53cd\u9988\u6765\u770b\u611f\u89c9\u62db\u751f\u5b98\u8fd8\u6bd4\u8f83\u770b\u597d\u3002

    \u6210\u7ee9\u5355

    \u628a\u6210\u7ee9\u5355\u5217\u4e3a\u6587\u4e66\u662f\u56e0\u4e3a\u6211\u4ea4\u4e86\u4e00\u4efd\u975e\u5e38\u4e0d\u5bfb\u5e38\u7684\u6210\u7ee9\u5355\uff0c\u5728\u6210\u7ee9\u5355\u524d\u9762\u9644\u4e86 4 \u9875 cover letter \u8bba\u8ff0\u6211\u8fd9\u51e0\u5e74\u901a\u52e4\u7389\u6cc9\u5927\u6982\u82b1\u8d39\u603b\u65f6\u95f4\u591a\u5c11\uff0c\u6211\u7684\u603b\u5b66\u5206\u6bd4\u522b\u4eba\u591a\u591a\u5c11\uff0c\u6211\u7533\u8bf7\u540e\u6bd5\u4e1a\u524d\u9884\u8ba1\u5b8c\u6210\u7684\u8bfe\u7a0b\u8fd8\u6709\u54ea\u4e9b\uff0c\u603b\u4e4b\u786e\u5b9e\u4e0a\u8bfe\u7684\u5de5\u4f5c\u91cf\u5927\uff0c\u5e0c\u671b\u62db\u751f\u5b98\u4e5f\u80fd\u8003\u8651\u8fd9\u4e2a\u56e0\u7d20\u7b49\u3002\u4e5f\u4e0d\u77e5\u9053\u5408\u4e0d\u5408\u89c4\uff0c\u4f46\u8fd9\u4e9b\u4e1c\u897f\u786e\u5b9e\u4e0d\u77e5\u9053\u54ea\u91cc\u53bb\u5199\u3002\u76ee\u524d\u8fd8\u6ca1\u6709\u76f4\u63a5\u6216\u95f4\u63a5\u7684\u53cd\u9988\u80fd\u544a\u8bc9\u6211\u8fd9\u6837\u505a\u5bf9\u4e0d\u5bf9\u6216\u597d\u4e0d\u597d\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_6","title":"\u6691\u7814","text":"

    \u5bf9\u4e8e\u6691\u7814\u4e00\u4e2a\u6bd4\u8f83\u7b80\u5355\u7684 comment \u662f\u5982\u679c\u60f3\u7533\u5317\u7f8e PhD \u5c31\u76f4\u63a5\u53bb\u9676\u74f7\u5317\u7f8e\uff0c\u4e0d\u8981\u5728\u610f\u201c\u5317\u7f8e rank \u4e0d\u597d\u7684\u5b66\u6821\u662f\u4e0d\u662f\u4e0d\u5982\u522b\u7684\u5730\u533a rank \u597d\u7684\u5b66\u6821\u201d\uff0c\u56e0\u4e3a\u5730\u533a\u5185\u5708\u5b50\u7684\u8001\u5e08\u8fd8\u662f\u4f1a\u6bd4\u5730\u533a\u5916\u719f\u4e00\u4e9b\uff0c\u4e14\u90e8\u5206\u8001\u5e08\u6691\u7814\u7684\u98ce\u683c\u662f\u628a\u597d\u5b66\u751f\u63a8\u5411\u66f4\u597d\u7684\u8001\u5e08\u4ee5\u5efa\u7acb\u5b66\u672f connection\u3002\u4ee5\u53ca\u867d\u7136\u5728\u5317\u7f8e onsite \u7814\u7a76\u786e\u5b9e\u5bf9\u793e\u4ea4\u6709\u5229\uff0c\u4f46\u6761\u4ef6\u5f88\u96be\u5177\u5907\uff0c\u56e0\u4e3a\u7b7e\u8bc1\u529e\u7406\u96be\u5ea6\u5927\uff0c\u5bf9\u6559\u6388\u6765\u8bf4\u5e38\u5e38\u6295\u5165\u5927\u4e8e\u56de\u62a5\uff0c\u5b66\u751f\u9002\u5e94\u6210\u672c\u4e5f\u9ad8\uff0c\u4e0d\u4e00\u5b9a\u80fd\u6709\u5229\u4e8e\u6548\u7387\uff0c\u6240\u4ee5\u5982\u679c\u6709 prof \u8ddf\u6211\u8bf4\u4e0d\u613f\u4e3a\u6211\u529e\u7b7e\u8bc1\u6211\u662f\u80fd\u7406\u89e3\u7684\u3002online \u6548\u529b\u4e5f\u4e0d\u4f4e\u7684\u3002

    \u5e38\u5e74\u5f00\u653e\u7684\u51e0\u4e2a\u6691\u7814\uff08\u4e0d\u5168\u9762\uff0c\u5efa\u8bae\u591a\u65b9\u53c2\u8003\uff0c\u66f4\u5efa\u8bae\u5927\u80c6\u76f4\u63a5\u90ae\u4ef6\u5957\u74f7\uff09

    "},{"location":"docs/4-opinion/plan/24fall/#_7","title":"\u53c2\u8003\u8d44\u6599","text":"

    https://github.com/zhanglj37/Tutorial-on-PhD-Application

    "},{"location":"docs/4-opinion/plan/asundergrad/","title":"As An Undergrad \u672c\u79d1\u7684\u4e00\u8def\u8d70\u6765","text":"

    :material-circle-edit-outline: \u7ea6 284 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u4e00\u5207\u8981\u4ece\u5927\u5b66\u662f\u4ec0\u4e48\u7684\u5b9a\u4e49\u8c08\u8d77

    \u662f\u5426\u6709\u5fc5\u8981\u8c08\u8fd9\u4e48\u6839\u672c\uff1f\u6709

    \u3002\u3002\u3002\u6551\u547d

    \u5148\u5806\u79ef\u4e00\u4e9b\u60f3\u5bf9\u672a\u6765\u7684\u81ea\u5df1\u8bf4\u7684\u53e5\u5b50\u5427

    \u53c8\u56de\u5bb6\u770b\u5230\u8001\u5e08\u5728\u4f53\u7cfb\u7fa4\u6f47\u6d12\u7559\u4e0b\u4e00\u884c\uff1a\u201c\u8981\u5728\u6da7\u6c34\u6cc9\u58f0\u3001\u6797\u6d9b\u677e\u98ce\u3002\u201d\uff08\u6211\u6ca1\u6709\u67e5\u5230\u8fd9\u53e5\u7684\u51fa\u5904\uff0c\u7591\u4f3c\u662f\u201c\u4e00\u79cd\u5b64\u9ad8\u4e0d\u6613\u6500\uff0c\u6b64\u8eab\u53ea\u5408\u4f4f\u6df1\u5c71\u3002\u517b\u6210\u9cde\u7532\u4e3a\u9f99\u53bb\uff0c\u5316\u4f5c\u4e91\u6d9b\u5f85\u9e64\u8fd8\u3002\u58f0\u5165\u7a7a\u6797\u4eba\u5bc2\u5bc2\uff0c\u54cd\u5f52\u5e7d\u6da7\u6c34\u6f7a\u6f7a\u3002\u53ee\u5b81\u83ab\u628a\u677e\u98ce\u5356\uff0c\u7559\u5728\u5343\u5ca9\u4e07\u58d1\u95f4\u3002\u201d\u4e00\u9996\u8bd7\uff1f\uff09\u6709\u540c\u5b66\u63a5\uff1a\u6362\u4e2a\u5f62\u5f0f\u966a\u5927\u5bb6\uff0c\u90fd\u5728\u7684\u3002\u4e8e\u662f\u53c8\u611f\u5230\u4f55\u5fc5\u9053\u522b\uff0c\u6211\u5df2\u7ecf\u628a\u8fd9\u4e9b\u5e74\u5404\u4f4d\u6240\u6709\u4eba\u8d60\u4e88\u6211\u7684\u77e5\u8bc6\u3001\u6027\u683c\u3001\u89c2\u5ff5\u3001\u529b\u91cf\u5168\u90e8\u5e26\u5728\u8eab\u4e0a\u5e26\u8d70\u4e86\u3002

    "},{"location":"docs/4-opinion/plan/find1job/","title":"Find a job in academia or industries?","text":"

    :material-circle-edit-outline: \u7ea6 23 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/plan/find1job/#opinions","title":"Opinions","text":"

    In academia

    "},{"location":"docs/4-opinion/plan/find1job/#-","title":"-","text":"

    In industries

    "},{"location":"docs/4-opinion/plan/find1job/#-_1","title":"-","text":""},{"location":"docs/4-opinion/plan/find1job/#my-choice","title":"My Choice?","text":""},{"location":"docs/4-opinion/plan/find1job/#resources","title":"Resources","text":""},{"location":"docs/4-opinion/plan/survivezju/","title":"Survivezju","text":"

    :material-circle-edit-outline: \u7ea6 1 \u4e2a\u5b57

    Reference

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/","title":"ZJU English Major to CS","text":"

    :material-circle-edit-outline: \u7ea6 4032 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 13 \u5206\u949f

    \u26a0\ufe0f \u611f\u89c9\u5f53\u65f6\u5199\u5f97\u4e0d\u662f\u5f88\u597d\uff0c\u73b0\u5728\u5f88\u591a\u89c2\u5ff5\u53c8\u6709\u4e9b\u6539\u53d8\uff0c\u53ef\u80fd24\u5e74\u6625\u8282\u671f\u95f4\u7a7a\u4e0b\u6765\u4f1a\u518d\u8ba4\u771f\u6539\u4e00\u4e0borz

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_1","title":"\u672c\u6587\u6863\u662f\u4ec0\u4e48\uff1f","text":"

    \u7b14\u8005\u8f6c\u4e13\u4e1a\u8e29\u8fc7\u7684\u5751\u548c\u5bf9\u540e\u8f88\u7684\u5efa\u8bae\uff0c\u771f\u5fc3\u60f3\u5efa\u7acb\u8d77ZJU\u5185\u90e8\u826f\u597d\u7684\u4f20\u5e2e\u5e26\u6c1b\u56f4\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_2","title":"\u89c2\u5ff5&\u4e60\u60ef\u95ee\u9898","text":"

    \u5728\u5177\u4f53\u5efa\u8bae\u524d\u9996\u5148\u56de\u7b54\u4e00\u4e9b\u5e38\u6709\u7684\u62c5\u5fe7+\u505a\u4e00\u4e9b\u4e60\u60ef\u65b9\u9762\u7684\u63d0\u9192

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs","title":"\u6211\u80fd\u8f6c\u5230CS\u5417\uff1f","text":"

    \u80fd\u3002\u6709\u5982\u4e0b\u6848\u4f8b\uff08\u4e0d\u4ee3\u8868\u6240\u6709\u4eba\u613f\u610f\u88ab\u8054\u7cfb\u5230\uff0c\u4e0d\u4fdd\u8bc1\u63d0\u4f9b\u8054\u7cfb\u65b9\u5f0f\uff09

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#nlp","title":"NLP\u4e0d\u8981\u8bed\u8a00\u5b66\u540c\u5b66\u5417\uff1f","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#_3","title":"\u660e\u786e\u4e00\u4e2a\u5341\u5e74\u5230\u4e09\u5341\u5e74\u7684\u957f\u8fdc\u89c4\u5212\uff0c\u4e3b\u8981\u662f\u4ee5\u4e0b\u51e0\u4e2a\u95ee\u9898","text":"\u95ee\u9898 \u6211\u7684\u56de\u7b54 \u6211\u8981\u5728\u54ea\u91cc\u751f\u6d3b\uff0c\u56fd\u5185\u8fd8\u662f\u56fd\u5916\uff1f \u6211\u8f6cCS\u662f\u66f4\u591a\u56e0\u4e3a\u559c\u6b22\u7406\u5de5\u79d1\uff0c\u8fd8\u662f\u56e0\u4e3a\u559c\u6b22\u5de5\u8d44\uff1f \u6211\u8981\u8fdb\u5de5\u4e1a\u754c\uff0c\u53bb\u79d1\u6280\u4e92\u8054\u7f51\u516c\u53f8\u5de5\u4f5c\uff1b\u8fd8\u662f\u7559\u5728\u5b66\u672f\u754c\uff0c\u5728\u9ad8\u6821\u6216\u7814\u7a76\u6240\u5de5\u4f5c\uff1f \u6211\u8981\u505aCS\u9664NLP\u5176\u5b83\u7684\u65b9\u5411\uff0c\u5982\u7cfb\u7edf\u3001\u7f51\u7edc\u3001\u5b89\u5168\u3001CV\u6216\u7eaf\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u65b9\u5411\uff1b\u8fd8\u662f\u505a\u504f\u6df1\u5ea6\u5b66\u4e60\u7684NLP\u65b9\u5411\uff1b\u8fd8\u662f\u505a\u504f\u8bed\u8a00\u5b66\u7684NLP\u65b9\u5411\uff1f \u6211\u6709\u591a\u5c11\u7ecf\u8d39\uff1f \u6211\u591a\u5c11\u5e74\u5185\u9700\u8981\u8f6c\u597d\u4e13\u4e1a\uff1f"},{"location":"docs/4-opinion/plan/zju_ling_cs/#_4","title":"\u89c4\u5212\u4eba\u751f\u4e2d\u8be5\u505a/\u4e0d\u8be5\u505a\u7684\u4e8b\u7684\u4e24\u4e2a\u51c6\u5219","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_1","title":"\u628a\u81ea\u5df1\u770b\u6210CS\u4eba","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_2","title":"CS\u6709\u8001\u5e08\u540c\u5b66\u770b\u4e0d\u8d77\u6211\u600e\u4e48\u529e\uff1f","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_3","title":"\u5b66\u4e0d\u597dCS\uff0c\u662f\u4e0d\u662f\u56e0\u4e3a\u5b66\u82f1\u8bed\u8bfe\u4f7f\u6211\u53d8\u4e0d\u806a\u660e\u4e86\uff1f","text":"

    \u4e0d\u662f\u7684\u3002 - \u7406\u8bba\u4e0a\u662f\u5b8c\u5168\u53ef\u4ee5\u5b66\u597d\u7684\u3002NLP\u5708\u6709\u5f88\u591a\u7814\u7a76\u8005\u8bfb\u8fc7\u8bed\u8a00\u5b66\u548cCS\u53cc\u672c\u79d1\uff0c\u4ee3\u8868AP\u6709AllenNLP Noah Smitch, Colimbia University Zhou Yu\uff08ZJU\u7684\u672c\u79d1\uff09. \u8bfb\u8bed\u8a00\u5b66\u6ca1\u6709\u803d\u8bef\u4ed6\u4eec\u7684\u8111\u5b50\uff0c\u53cd\u800c\u662f\u4e00\u4e2a\u5f88\u597d\u7684idea\u6765\u6e90\u3002\u6211\u611f\u89c9\u6709\u5f88\u591a\u5929\u624d\u7684\u6848\u4f8b\u53ef\u4ee5\u8bc1\u660e\u4eba\u7684\u77e5\u8bc6\u5bb9\u91cf\u548c\u5b66\u4e60\u80fd\u529b\u4e0a\u9650\u662f\u8d85\u51fa\u5927\u5bb6\u60f3\u8c61\u7684\uff0c\u5b66\u4e24\u4e2a\u4e13\u4e1a\u8fd9\u4ef6\u5c0f\u4e8b\u8fdc\u8fdc\u5728\u8fd9\u4e2a\u4e0a\u9650\u4e4b\u4e0b\u3002\u6211\u6c38\u8fdc\u8ba4\u4e3a\u6bc5\u529b\u548c\uff08\u5bf9\u81ea\u5df1\u4eba\u751f\u4e0a\u9650\u7684\uff09\u60f3\u8c61\u529b\u6bd4\u5f53\u524d\u80fd\u529b\u66f4\u6709\u51b3\u5b9a\u4f5c\u7528\u3002 - \u5b9e\u9645\u82f1\u8bed\u4e13\u4e1a\u53bbCS\u53cc\u4e13\u4e1a\u5bb9\u6613\u5403\u4f4e\u7ee9\u70b9\u7684\u539f\u56e0\uff0c\u5f80\u5f80\u4e0d\u662f\u80fd\u529b\u667a\u529b\u4e0d\u8db3\uff0c\u800c\u662f\u6709\u4fe1\u606f\u5dee\uff1a\u751f\u6d3b\u5728\u6587\u79d1\u7684\u6563\u6f2b\u73af\u5883\u4e2d\u96be\u4ee5\u77e5\u9053\u5927\u90e8\u5206\u540c\u5b66\u7684\u81ea\u5b66\u8fdb\u5ea6\uff0c\u548c\u5982\u679c\u67d0\u4e9b\u8bfe\u7a0b\u6709\u5b9e\u8df5\u4e0a\u7684\u5751\uff0c\u6ca1\u6709\u4e0e\u5927\u90e8\u961f\u4e00\u8d77\u5b66\u4e60\u7684\u540c\u5b66\u5c31\u96be\u4ee5\u77e5\u9053\u600e\u6837\u7075\u6d3b\u5e94\u5bf9\u3002\u6240\u4ee5\u5efa\u8bae\u4e0e\u540c\u5b66\u4e00\u8d77\u5b66\u4e60\uff0c\u53c2\u89c1\u4e0b\u4e00\u6761\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#cscs","title":"\u8981\u62e5\u6709\u4e00\u4e2a\u6216\u51e0\u4e2a\u540c\u6837\u8de8\u4e13\u4e1a\u5b66CS\u7684\u670b\u53cb\uff0c\u6216\u76f4\u63a5\u878d\u5165\u540c\u4e00\u7ea7\u7684CS\u672c\u79d1\u751f\u5708\u5b50\u91cc\u3002\u5982\u679c\u5b9e\u5728\u6ca1\u6709\uff0c\u4e00\u4e9b\u5176\u5b83\u5de5\u79d1\u7684\u540c\u5b66\u4e5f\u53ef\u4ee5\u3002","text":"

    \u540c\u5b66\u7684\u7528\u5904\u6709\uff1a - \u5e2e\u52a9\u4f60\u8ddf\u4e0a\u5b66\u4e60\u8282\u594f\u3002CS\u7684\u751f\u6d3b\u8282\u594f\u662f\u82f1\u8bed\u4e13\u4e1a\u76842\u500d\uff0c\u662f\u7406\u79d1\u4e13\u4e1a\u76841.5\u500d\uff0c\u5982\u679c\u51b3\u5b9a\u8f6c\u4e13\u4e1a\u662f\u9700\u8981\u4e3b\u52a8\u63d0\u9ad8\u4e00\u4e0b\u751f\u6d3b\u8282\u594f\u7684\uff0c\u505a\u4e8b\u79ef\u6781\u4e00\u70b9\uff0c\u544a\u522b\u62d6\u5ef6\u3002 - \u4e92\u76f8\u63a8\u8350\u597d\u7684\u81ea\u5b66\u8d44\u6599\uff0c\u4e92\u76f8\u5206\u4eab\u7b14\u8bb0\u548c\u8ba8\u8bba\u9898\u76ee\uff0c\u5206\u5de5\u6574\u7406\u671f\u672b\u590d\u4e60\u8d44\u6599\uff0c\u671f\u672b\u4e92\u76f8\u63d0\u95ee\uff0c\u5f62\u6210\u81ea\u5b66\u6c1b\u56f4\uff0c\u8282\u7701\u4e00\u4e9b\u8e29\u5751\u65f6\u95f4\u3002 - \u5982\u679c\u67d0\u4e9b\u8bfe\u7a0b\u5b89\u6392\u6709\u6559\u5b66\u4e8b\u6545\uff0c\u4f60\u53ef\u4ee5\u53ca\u65f6\u77e5\u9053\u5927\u90e8\u5206\u540c\u5b66\u662f\u600e\u6837\u5e94\u5bf9\u7684\uff0c\u53ca\u65f6\u8c03\u6574\u81ea\u5df1\u7684\u5e94\u5bf9\u63aa\u65bd\uff0c\u9632\u6b62\u5982\u679c\u6210\u7ee9\u5360\u6bd4\u7a81\u7136\u8c03\u6574\uff0c\u81ea\u5df1\u5c06\u52aa\u529b\u82b1\u5728\u4e86\u6700\u540e\u5360\u6210\u7ee9\u6bd4\u91cd\u5f88\u5c0f\u7684\u5730\u65b9\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_5","title":"\u8981\u591a\u8bb0\u7b14\u8bb0","text":"

    \u8bb0\u7b14\u8bb0\u662f\u8d39\u66fc\u5b66\u4e60\u6cd5\u7684\u6295\u5165\u4ea7\u51fa\u6bd4\u6700\u9ad8\u7684\u5b9e\u8df5\u5f62\u5f0f\uff0c\u5373\u65e2\u5e2e\u52a9\u68c0\u67e5\u7406\u89e3\uff0c\u7b14\u8bb0\u53c8\u9020\u798f\u540e\u4eba\u3002\u4f60\u53ef\u4ee5\u79c9\u627f\u5f00\u6e90\u7cbe\u795e\uff0c\u50cf\u524d\u8f88\u4e00\u6837\u591a\u5c06\u7b14\u8bb0\u516c\u5e03\u9020\u798f\u540e\u4eba\uff08\u4e0d\u8fc7\u8bf7\u9075\u5b88\u8bda\u4fe1\u5b88\u5219\uff09\u3002\u975e\u5e38\u5e0c\u671bZJU\u80fd\u9010\u6e10\u5f62\u6210\u8f83\u597d\u7684\u4f20\u5e2e\u5e26\u6c1b\u56f4\uff0c\u8ba9\u540e\u8f88\u4e5f\u6709\u826f\u597d\u6821\u53cb\u8d44\u6e90\u53ef\u4eab\u7528\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_6","title":"\u6211\u53ef\u4ee5\u4ee5\u600e\u6837\u7684\u8eab\u4efd\u672c\u79d1\u6bd5\u4e1a\uff1f\u6211\u6709\u54ea\u4e9b\u53ef\u884c\u7684\u51fa\u8def\uff1f","text":"

    \u4ee5\u4e0b\u8fd9\u4e9b\u90fd\u662f\u53ef\u80fd\u505a\u5230\u7684\uff0c\u6211\u4e5f\u5206\u522b\u5217\u51fa\u4e86\u6211\u8ba4\u4e3a\u9700\u8981\u51c6\u5907\u7684\u80cc\u666f\u3002 - \u51fa\u56fdms\uff1a\u7ee9\u70b9\uff0c\u6691\u7814/\u5b9e\u4e60 - \u51fa\u56fd\u76f4\u63a5phd\uff1a\u6691\u7814\uff0cpaper - \u672c\u6821\u76f4\u535a\uff1a\u7ee9\u70b9\uff0c\u8fdb\u672c\u6821\u7ec4\uff0c\u590f\u4ee4\u8425\uff0cpaper - \u8de8\u6821\u76f4\u535a\uff1a\u7ee9\u70b9\uff0c\u5bf9\u65b9\u6821\u590f\u4ee4\u8425\uff0cpaper - \u5de5\u4f5c\uff1a\u5237\u9898\uff0c\u5b9e\u4e60 \u5176\u4e2d\u6211\u8ba4\u4e3a\u503c\u5f97\u6ce8\u610f\u7684\u8fd8\u6709\uff0c\u5177\u4f53\u6700\u597d\u7531\u8bfb\u8005\u518d\u54a8\u8be2\u76f8\u5e94\u8eab\u4efd\u7684\u4eba\u7684\u5efa\u8bae\u3002\u672c\u6761\u9002\u7528\u524d\u9762\u6240\u8ff0\u201c20\u4e2a\u4eba\u5efa\u8bae\u201d\u51c6\u5219\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_7","title":"\u8bfe\u7a0b","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_4","title":"CS\u5fc5\u4fee\u8bfe","text":"

    \u9996\u5148\u8981\u660e\u786e\u4e00\u4e2a\u8ba4\u77e5\u95ee\u9898\uff1a\u8bfbCS\u53cc\u5b66\u4f4d\u662f\u4e00\u4e2a\u539f\u5b50\u6027\u7684\u4e8b\u52a1\uff0c\u8981\u4e48\u4e0d\u8bfb\uff0c\u8981\u4e48\u6309\u9700\u6c42\u8bfb\u5b8c\u6216\u8f85\u4fee\u6216\u53cc\u5b66\u4f4d\uff0c\u8fd9\u4e24\u79cd\u9009\u62e9\u90fd\u662f\u6295\u5165\u4ea7\u51fa\u6bd4\u8f83\u9ad8\u7684\uff1b\u6295\u5165\u4ea7\u51fa\u6bd4\u6700\u4f4e\u7684\u662f\u8bfb\u4e00\u534a\uff08\u5fae\u8f85\u4fee\u6216\u53cc\u4e13\u4e1a\uff09\u3002 \u8be5\u56fe\u4e2d\u9664\u6570\u7406\u57fa\u7840\u6a21\u5757\u4e0d\u662f\u53cc\u5b66\u4f4d\u5fc5\u4fee\uff0c\u5176\u5b83\u662f\u5fc5\u4fee\u3002 \uff08\u8fd9\u4e2a\u56fe\u4e0d\u77e5\u9053\u4e3a\u4ec0\u4e48\u6709\u4e2a\u7ea2\u5708\uff0c\u627e\u4e0d\u5230\u539f\u56fe\u4e86\uff0c\u6279\u8bc4cyh\u540c\u5b66\u4e71\u753b\uff09

    \u9009\u4e0d\u4e0aCS\u7684\u8bfe\u600e\u4e48\u529e\uff1f - \u6700\u6709\u6548\uff1a\u8865\u9009+\u5728\u8865\u9009\u7684\u51e0\u5929\u91cc\u7ebf\u4e0b\u53bb\u9009\u8bfe\u529e\u6216\u7ed9\u9009\u8bfe\u529e\u53d1\u90ae\u4ef6\u3002\u674e\u6653\u8001\u5e08\u548c\u5f20\u4f20\u534e\u8001\u5e08\u90fd\u5f88nice\uff0c\u8868\u793a\u81ea\u5df1\u5f88\u60f3\u9009\u8bfe\uff0c\u8ddf\u8001\u5e08\u8bf4\u660e\u539f\u56e0\u3002 - \u7b2c\u4e8c\u6709\u6548\uff1a\u5982\u679c\u4efb\u8bfe\u8001\u5e08\u5728\u8ba1\u9662\u8bdd\u8bed\u6743\u8f83\u5927\uff0c\u8bf7\u4efb\u8bfe\u8001\u5e08\u5e2e\u5fd9\u8ddf\u9009\u8bfe\u529e\u8bf4\uff0c\u80fd\u4fdd\u8bc1\u4f60\u9009\u4e0a\u8be5\u8001\u5e08\u7684\u8bfe\u3002 - \u7b2c\u4e09\u6709\u6548\uff1a\u9009\u8bfe\u65f6\u4e0eCS\u7684\u540c\u5b66\u5546\u91cf\uff0c\u505a\u51fa\u65f6\u95f4\u6b63\u597d\u7684\u4e00\u4e9b\u8bfe\u8868\u3002\u53ef\u80fd\u6d89\u53ca\u5230\u201c\u7528\u4e00\u4e9b\u8bfe\u5835\u4f4f\u53e6\u4e00\u4e9b\u8bfe\u201d\u8fd9\u79cd\u590d\u6742\u64cd\u4f5c\uff0c\u6240\u4ee5\u5408\u4f5c\u6bd4\u8f83\u5212\u7b97\u3002

    \u600e\u4e48\u5b66\uff1f - ZJU\u8bfe\u7a0b\u5171\u4eab\u8ba1\u5212 https://github.com/QSCTech/zju-icicles - \u56fe\u7075\u73ed\u8bfe\u7a0b\u901f\u901a\u8ba1\u5212 https://github.com/ZJU-Turing/TuringCourses - \u4e00\u4f4d\u5b66\u957f\u7684\u4f18\u8d28\u7b14\u8bb0 \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4\uff01 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4 (xuan-insr.github.io) - \u4e00\u4f4d\u5b66\u957f\u7684\u4f18\u8d28\u7b14\u8bb0 https://github.com/Zhang-Each/CourseNoteOfZJUSE

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#ai","title":"AI","text":"

    AI\u8bfe\u4e00\u822c\u6bd4CS\u8bfe\u597d\u9009\uff0c\u4f46\u662f\u5982\u679c\u9009\u4e0d\u4e0a\u4e5f\u8bf7\u9075\u7167\u4e0a\u6761\u4e2d\u7684\u5efa\u8bae\u3002 \u975e\u5fc5\u8981\u4e0d\u9009AI\u8bfe\uff0cAI\u8bfe\u6700\u5927\u7684\u6536\u83b7\u662f\u5728\u7b80\u5386\u4e0a\u4f5c\u4e3a\u4e00\u4e2a90+\u8bfe\u7a0b\u51fa\u73b0\uff0c\u57fa\u672c\u5b66\u4e0d\u5230\u4e1c\u897f\uff08\u9664\u4e86NLP\u8bfe\u6211\u611f\u89c9\u542c\u8bfe\u6536\u83b7\u633a\u5927\u7684\uff09\uff0c\u4e3b\u8981\u9760\u81ea\u5b66\u540e\u5377\u51fa\u5927\u4f5c\u4e1a\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_8","title":"\u8bed\u8a00\u5b66","text":"

    \u56e0\u4e3a\u82f1\u4e13\u57f9\u517b\u65b9\u6848\u8fd8\u662f\u8981\u6c42\u4fee\u5927\u91cf\u4e13\u4e1a\u8bfe\u7684\uff0c\u611f\u89c9\u53ef\u4ee5\u5c3d\u91cf\u628a\u8bed\u8a00\u5b66\u6a21\u5757\u591a\u4fee\u4e00\u70b9\uff0c\u6709\u4e9b\u5728\u8fdb\u7ec4\u7684\u65f6\u5019\u53ef\u80fd\u8fd8\u662f\u8ba4\u53ef\u7684\u3002 \u4ee5\u4e0b\u8bfe\u7a0b\u5982\u679c\u62ff\u4e86\u9ad8\u5206\u503c\u5f97\u5728\u7b80\u5386\u4e0a\u4e00\u63d0 - \u5f53\u4ee3\u8bed\u8a00\u5b66 - \u8bed\u97f3\u5b66 - \u53e5\u6cd5\u5b66 - \u5fc3\u7406\u8bed\u8a00\u5b66 - \u8bed\u4e49\u5b66 - \u8bed\u7528\u5b66 - \u8bed\u6599\u5e93\u8bed\u8a00\u5b66

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_9","title":"\u6570\u5b66","text":"

    \u5bf9\u4e8ePhD\u3001\u627e\u5de5\u548c\u56fd\u5185\u76f4\u535a\uff1a \u53ef\u80fd\u4e0d\u9700\u8981\u6570\u5b66\u3002\u3002\u3002\u8ba4\u4e3a\u6700\u597d\u4e0d\u8981\u989d\u5916\u9009\u6570\u5b66\u8bfe \u6211\u81f3\u4eca\u9047\u5230\u7684\u8001\u5e08\u6ca1\u6709\u56e0\u4e3a\u6211\u7b80\u5386\u4e0a\u4efb\u4f55\u6570\u5b66\u76f8\u5173\u7684\u4e1c\u897f\u800c\u5f55\u6211\u6216\u62d2\u6211\u7684\uff0c\u90fd\u662f\u53ea\u95ee\u7f16\u7a0b\u3002 CS\u4e13\u4e1a\u8bfe\u91cc\u7684\u79bb\u6563\u6570\u5b66\u548c\u8ba1\u7b97\u7406\u8bba\uff08\u548c\u53ef\u80fd\u8fd8\u6709\u6570\u903b\uff09\u5df2\u7ecf\u8db3\u591f\u57f9\u517b\u6570\u5b66\u601d\u7ef4\u3002 \u5982\u679c\u62c5\u5fc3\u6570\u636e\u5206\u6790\u548c\u7edf\u8ba1\u6280\u80fd\uff0c\u6587\u6570\u91cc\u636e\u8bf4\u5e94\u7528\u7edf\u8ba1\u5b66\u8fd9\u95e8\u8bfe\u7a0b\u6bd4\u9ad8\u7b49\u6570\u5b66\u597d\u4f7f\uff0c\u8fd8\u6709\u673a\u4f1a\u7684\u540c\u5b66\u53ef\u4ee5\u8bd5\u4e00\u4e0b\u3002

    \u5bf9\u4e8ems\uff1a \u786e\u5b9e\u6709\u4e00\u4e9b\u9879\u76ee\u8981\u6c42\u4fee\u8fc7\u4e00\u4e9b\u6570\u5b66\u8bfe\u7a0b\uff0c\u4f8b\u5982\u521a\u770b\u5230SUTD\u7684ISTD ms\u8981\u6c42\u4e24\u5b66\u671f\u5fae\u79ef\u5206\uff0c\u4e00\u5b66\u671f\u7ebf\u4ee3\u548c\u4e00\u5b66\u671f\u6982\u7edf\uff0c\u8fd9\u79cd\u65e0\u7591\u662f\u6bd4\u8f83\u4e0d\u53cb\u597d\u7684\u9879\u76ee\u4e86\u3002 \u4e5f\u6709\u6bd4\u8f83\u53cb\u597d\u7684\u9879\u76ee\uff0c\u5317\u7f8e\u4e00\u4e9b0\u57fa\u7840\u8f6c\u7801\u9879\u76ee\u53ef\u53c2\u7167OpenCSapp\uff0c\u82f1\u56fd\u7684IC\u548cUCL\u5728\u524d\u5e74\u4e5f\u5f00\u4e86\u96f6\u57fa\u7840\u8f6c\u7801\u9879\u76ee\uff0c\u4e0d\u8fc7\u51fa\u8def\u548c\u542b\u91d1\u91cf\u9700\u8981\u81ea\u5df1\u8861\u91cf\uff0c\u8fd8\u662f\u5efa\u8bae\u201c\u54a8\u8be220\u4e2a\u4eba\u201d\u51c6\u5219\u3002\u4ee3\u8868dp\u662f18\u7ea7SJTU\u82f1\u8bed\u4e13\u4e1a\uff0c4\u6bb5\u79d1\u7814\u6216\u4e92\u8054\u7f51\u5382NLP\u4ea7\u54c1\u5b9e\u4e60\uff0c\u5c11\u91cf\u9ad8\u5206\u6570\u5b66\u548c\u7f16\u7a0b\u8bfe\u7a0b\uff0c\u7ee9\u70b990+ \u2192 IC CS ms

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_10","title":"\u7ee9\u70b9","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#_11","title":"\u79d1\u7814","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#nlp_1","title":"\u5982\u4f55\u9009\u9898\uff1fNLP\u6709\u54ea\u4e9b\u65b9\u5411\u53ef\u505a\uff1f","text":"

    \u53c2\u7167\u8fd9\u4e9b\u9876\u4f1a\u90fd\u6709\u4ec0\u4e48track\uff0c\u4e0b\u9762\u662f\u6700\u8fd1\u4e00\u671f\u6bcf\u4e2atrack\u7684best paper - Best Papers - ACL 2023 (aclweb.org) - Best Paper Awards - emnlp 2022 (balhafni.github.io) - Transactions of the Association for Computational Linguistics (transacl.org) - Announcing the NAACL 2022 Best Paper Awards! - NAACL-HLT 2022

    \u7279\u522b\u5730\uff0c\u60f3\u5230NLP\u91cc\u6bd4\u8f83\u7eaf\u8bed\u8a00\u5b66\u7684\u4e3b\u9898/\u65b9\u6cd5\u4e5f\u6709\u4e00\u4e9b\uff0c\u6709\u5982\u4e0b\u51e0\u4e2a \u4e3a\u4ec0\u4e48\u8981\u8bb2\u8fd9\u4e00\u5757\u56e0\u4e3a\u62c5\u5fc3\u4f60\u5728\u9762\u8bd5\u7684\u65f6\u5019\u4f1a\u9700\u8981\u5411\u8001\u5e08\u8bc1\u660e\u4f60\u7684\u53e6\u4e00\u90e8\u5206\u4e13\u4e1a\u77e5\u8bc6\u4e5f\u662f\u6709\u7528\u7684 \u4e00\u822c\u6b27\u6d32\u7684NLP\u4f1a\u504f\u8bed\u8a00\u5b66\u4e00\u70b9 - \u5b9e\u9a8c\u8bed\u97f3\u548c\u97f3\u7cfb\u5b66 - \u7528\u8bed\u8a00\u5b66\u77e5\u8bc6\u505a\u6570\u636e\u548c\u6570\u636e\u589e\u5f3a - AI\u4e2d\u7684\u4f26\u7406\u9053\u5fb7\u95ee\u9898 - \u7a00\u6709\u8bed\u8a00\u6316\u6398

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_12","title":"\u5982\u4f55\u9009\u5bfc\uff1f","text":"

    \u56fd\u5916\u5bfc\u5e08\uff1a\u5e38\u8bfb\u6bcf\u5e74\u7684\u9876\u4f1a\u6709\u610f\u601d\u8bba\u6587\uff0c\u5e76\u53c2\u7167CSRankings: Computer Science Rankings\uff0c\u5173\u6ce8\u5b66\u672f\u5708\u517b\u597d\u53f7\u540e\u5e38\u5237Twitter \u56fd\u5185\u6821\u5185\u5bfc\u5e08\uff1a\u5982\u679c\u6709\u60f3\u8be2\u95ee\u7684\u5bfc\u5e08\u540d\u5355\u53ef\u4ee5\u90ae\u4ef6\u95ee\u6211 \u9009\u5bfc\u6216\u8005\u8054\u7cfbPhD\u7684\u65f6\u5019\u5982\u679c\u63a5\u5230\u7684\u4efb\u52a1\u662f\u4e8c\u4f5c\u4e09\u4f5c\u5f80\u540e\uff0c\u5f88\u53ef\u80fd\u662f\u6253\u767d\u5de5\uff0c\u57fa\u672c\u53ef\u4ee5\u62d2\u7edd\u3002\u9664\u975e\u4f60\u8ba4\u4e3a\u4f60\u627f\u62c5\u7684\u5de5\u4f5c\u8f83\u4e3a\u91cd\u8981\uff0c\u8001\u5e08\u53ef\u4ee5\u7ed9\u4f60\u63a8\u8350\u4fe1\uff0c\u4e8c\u4f5c\u4e09\u4f5c\u7684\u4f5c\u7528\u53ef\u80fd\u6ca1\u6709\u63a8\u8350\u4fe1\u5927\u3002 \u5982\u679c\u7533\u8bf7PhD\uff0c\u63a8\u8350\u4fe1\u7684\u529b\u5ea6\uff1a\u4f60\u4e0e\u63a8\u8350\u4eba\u7684\u4ea7\u51fa\u5f88\u91cd\u8981+\u76ee\u6807PhD\u5bfc\u8ba4\u8bc6\u7684\u4eba > \u4f60\u4e0e\u63a8\u8350\u4eba\u7684\u4ea7\u51fa\u5f88\u91cd\u8981+\u76ee\u6807PhD\u5bfc\u4e0d\u8ba4\u8bc6\u7684\u4eba > \u5176\u5b83

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_13","title":"\u7533\u8bf7","text":"

    \u56e0\u4e3a\u4fdd\u7814\u548c\u627e\u5de5\u6211\u786e\u5b9e\u4e0d\u61c2\uff0c\u8fd9\u91cc\u6682\u65f6\u53ea\u5199\u7533\u8bf7\u4e86\u3002\u540e\u7eed\u6709\u8bf7\u5171\u540c\u4f5c\u8005\u6269\u5c55\u5185\u5bb9\u7684\u8ba1\u5212\uff0c\u5982\u613f\u610f\u8d21\u732e\u8bf7\u8054\u7cfb\u6211\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#check-point","title":"Check Point","text":"

    \u5927\u4e00\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u4e13\u5fc3\u5b66\u4e13\u4e1a\u8bfe \u5927\u4e8c\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u8fdb\u7ec4\uff0c\u5b66\u4f1apytorch\uff0c\u8bad\u8fc7\u4e00\u4e9b\u5e38\u7528\u7684\u6a21\u578b \u5927\u4e09\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u4ea7\u51fa\u4e00\u4f5c\u6216\u5171\u4e00\u8bba\u6587

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_14","title":"\u6211\u8981\u4e0d\u8981\u627e\u4e2d\u4ecb\uff1f","text":"

    \u4e0d\u8981\u3002 \u539f\u56e0\u4e00\uff1aCS\u7684\u5728\u7ebf\u514d\u8d39\u8d44\u6599\u8db3\u591f\u4f7f\u7528 \u539f\u56e0\u4e8c\uff1a\u4e2d\u4ecb\u7684\u4fe1\u606f\u66f4\u65b0\u901f\u5ea6\u8d76\u4e0d\u4e0aCS\u5b66\u79d1\u7684\u53d1\u5c55\u901f\u5ea6

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_15","title":"\u6211\u7533\u8bf7\u53ef\u4ee5\u53c2\u8003\u54ea\u4e9b\u8d44\u6599\uff1f","text":"

    \u7533\u8bf7MS - \u5317\u7f8e\u7684CS master Home - Open CS Application - \u9664\u5317\u7f8e\u5916\u7684\u5176\u5b83CS master Global CS (global-cs-application.github.io) - \u4e00\u4ea9\u4e09\u5206\u5730/\u5bc4\u6258\u5bb6\u56ed\u7b49\u8bba\u575b - CC98\u4e0a\u6bcf\u4e00\u5e74CS\u7684\u98de\u8dc3\u624b\u518c

    \u7533\u8bf7PhD - \u6b27\u7f8eNLP\u5708\u5bf9PhD\u7533\u8bf7\u7684\u5efa\u8bae https://github.com/zhijing-jin/nlp-phd-global-equality - \u4e86\u89e3\u5b66\u79d1\u4f18\u52bf\u5b66\u6821\u548c\u5bfc\u5e08 CSRankings: Computer Science Rankings - \u6ce8\u518c\u4e00\u4e2aTwitter\u8d26\u53f7\uff0c\u5f00\u59cb\u5173\u6ce8NLP\u5708\u7684PhD\u548cAP\uff0c\u5404\u79cd\u7533\u8bf7\u673a\u4f1a\u4ed6\u4eec\u90fd\u4f1a\u5c3d\u5feb\u53d1\u5e03\u7684\u3002\u6bd4\u5982\u4f60\u53ef\u4ee5\u5148\u4eceAndrew Ng\u3001Christopher Manning\u3001Geoffrey Hinton\u8fd9\u79cd\u8001\u6559\u6388\u5173\u6ce8\u8d77\uff0c\u7136\u540e\u5173\u6ce8\u4ed6\u4eec\u7684\u5173\u6ce8\u8fd9\u6837\u6765\u641e\u3002 - \u5173\u6ce8\u4e00\u4ea9\u4e09\u5206\u5730/CC98/\u4e00\u4e9b\u5fae\u4fe1\u516c\u4f17\u53f7/\u77e5\u4e4e\u7684\u62db\u751f\u4fe1\u606f

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_16","title":"\u6295\u9012\u6691\u7814\u6ce8\u610f\u4e8b\u9879","text":"

    \u6d41\u7a0b\u540c\u7533\u8bf7PhD \u5df2\u7ecf\u719f\u8bc6\u7684\u5bfc\u5e08\u63a8\u8350\u662f\u6700\u5feb\u7684\uff1b\u5426\u5219\u5c31\u81ea\u5df1\u6d77\u6295\uff0c\u6295\u53d1\u5e03\u8fc7\u62db\u751f\u5e7f\u544a\u6216\u4e3b\u9875\u8868\u660e\u6b63\u5728\u62db\u751f\u7684\u8001\u5e08\u662f\u6700\u5feb\u7684\u3002\u6709\u7684\u65f6\u5019\u53ef\u4ee5\u5c1d\u8bd5\u6295\u8ba4\u8bc6\u7684PhD\uff0c\u56e0\u4e3a\u6691\u7814\u671f\u95f4\u5927\u90e8\u5206\u60c5\u51b5\u8fd8\u662f\u8ddf\u7740PhD\u6253\u5de5\u3002 \u5982\u679c\u8001\u5e08\u7ed9\u4f60\u7684\u8d23\u4efb\u6bd4\u8f83\u91cd\uff0c\u4e14\u4f60\u6709\u6bd4\u8f83\u597d\u7684\u5de5\u4f5c\u73af\u5883\uff0c\u6211\u8ba4\u4e3a\u7ebf\u4e0a\u7ebf\u4e0b\u533a\u522b\u4e0d\u5927\u3002 \u60f3\u53bb\u5317\u7f8e\u5c31\u5957\u5317\u7f8e\uff0c\u6211\u89c9\u5f97\u6700\u597d\u4e0d\u8981\u627e\u8df3\u677f\uff0c\u6709\u5317\u7f8e\u7684\u7ebf\u4e0a\u6691\u7814\u4e5f\u5f88\u597d\uff0c\u53ea\u8981\u662f\u4f60\u4e00\u4f5c\uff0c\u65f6\u957f6\u4e2a\u6708\u4ee5\u4e0a\uff0c\u6bcf\u5468\u6c47\u62a5\u8fdb\u5ea6\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_17","title":"\u6295\u9012\u5b9e\u4e60\u6ce8\u610f\u4e8b\u9879","text":"

    \u9700\u8981\u5b9e\u4e60 iff \u4f60\u6253\u7b97\u627e\u5de5or\u8bfb\u5b8c\u7855\u58eb\u627e\u5de5\uff0c\u7533\u8bf7\u5b66\u672f\u7c7bms\u548cPhD\u7684\u8bdd\uff0c\u5b9e\u4e60\u4e0d\u5f3a\u6c42\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#-xuan-insrgithubio","title":"- \ud83c\udff3\ufe0f\u200d\ud83c\udf08 \u603b\u89c8 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4 (xuan-insr.github.io) \u627e\u6691\u671f\u5b9e\u4e60\u548c\u79cb\u62db\u7684\u7ecf\u9a8c\u5e16","text":"

    http://www-cc98-org-s.webvpn.zju.edu.cn:8001/topic/4950730

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_18","title":"\u5173\u4e8e\u7b14\u8005&\u8054\u7cfb\u7b14\u8005","text":"

    \u7b14\u8005\u4f30\u8ba1\u662f\u4ece\u82f1\u8bed\u4e13\u4e1a\u8f6cNLP\u89c4\u5212\u6700\u4e0d\u987a\u3001\u8fdb\u5ea6\u6700\u66f2\u6298\u7684\u4e00\u4e2a\u3002\u8fd9\u4efd\u6587\u6863\u4e0d\u662f\u4ec0\u4e48\u6210\u529f\u7ecf\u9a8c\u5206\u4eab\uff0c\u6211\u5e76\u4e0d\u6210\u529f\uff0c\u53ea\u662f\u60f3\u628a\u6211\u8e29\u8fc7\u7684\u5751\u544a\u8bc9\u540e\u4eba\uff0c\u5e0c\u671b\u5c11\u6709\u4eba\u91cd\u8e48\u6211\u7684\u8986\u8f99\u3002\u6211\u89c9\u5f97\u6211\u7684\u9ad8\u4e2d\u548c\u672c\u79d1\u8fc7\u5f97\u592a\u574e\u5777\u4e86\uff0c\u771f\u8bda\u5730\u60f3\u5e2e\u52a9\u5b66\u5f1f\u5b66\u59b9\uff0c\u5e0c\u671b\u4f60\u4eec\u4e00\u5207\u987a\u5229\u3002\u8bfb\u8005\u53ef\u4ee5\u4ee5\u6211\u4f5c\u4e3a\u57fa\u51c6\uff0c\u5728\u56db\u5e74\u540e\u4e0d\u80fd\uff08\u5f53\u7136\u5982\u679c\u65e9\u505a\u89c4\u5212\uff0c\u4e00\u76f4\u5728\u52aa\u529b\uff0c\u4e5f\u4e0d\u4f1a\uff09\u6bd4\u6211\u66f4\u5dee\u3002\u6bd5\u7adf\u4e00\u6761\u8def\u8d70\u7684\u4eba\u591a\u4e86\uff0c\u540e\u4eba\u4e00\u5b9a\u662f\u8981\u8d8a\u8d70\u8d8a\u987a\u7684\u3002

    \u5982\u6709\u5efa\u8bae\u6216\u7591\u95ee\u8bf7\u901a\u8fc7\u90ae\u4ef6\u8054\u7cfb\u6211 RuoxiNing@outlook.com\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#recommended-readings","title":"Recommended Readings","text":""},{"location":"docs/4-opinion/tools/","title":"Introducing my tools! \u6211\u7684\u5de5\u5177\u7bb1\uff01","text":"

    :material-circle-edit-outline: \u7ea6 47 \u4e2a\u5b57

    \u8bb0\u5f55\u4e00\u70b9\u597d\u7528\u7684\u5de5\u5177

    "},{"location":"docs/4-opinion/tools/#contents","title":"Contents \u76ee\u5f55","text":""},{"location":"docs/4-opinion/tools/#_1","title":"\u96f6\u6563\u5de5\u5177","text":"

    \u96f6\u6563\u7684\u5c31\u653e\u5728\u8fd9\u91cc

    "},{"location":"docs/4-opinion/tools/#_2","title":"\u5728\u7ebf\u6253\u65f6\u95f4\u8f74\u5de5\u5177","text":"

    https://judes.me/lrc_editor/

    "},{"location":"docs/4-opinion/tools/howtocite/","title":"How to cite elegantly?","text":"

    :material-circle-edit-outline: \u7ea6 17 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/tools/howtocite/#which-format","title":"Which format?","text":""},{"location":"docs/4-opinion/tools/howtocite/#in-text-citation","title":"In-text citation","text":""},{"location":"docs/4-opinion/tools/howtocite/#references","title":"References","text":""},{"location":"docs/4-opinion/tools/howtocite/#tools","title":"Tools","text":"

    ... But the best tool is by hand

    "},{"location":"docs/4-opinion/tools/notes/","title":"\u5bf9\u7b14\u8bb0\u5de5\u5177\u548c\u4fe1\u606f\u8bb0\u5f55\u7684\u601d\u8003","text":"

    :material-circle-edit-outline: \u7ea6 423 \u4e2a\u5b57 :fontawesome-solid-code: 3 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/4-opinion/tools/notes/#_2","title":"\u4e3a\u4ec0\u4e48\u8981\u5199\u8fd9\u4e9b\u7b14\u8bb0","text":"

    \u672c\u6765\u60f3\u5199\u591a\u4e00\u70b9\u7684\uff0c\u4f46\u662f\u592a\u61d2\u4e86

    "},{"location":"docs/4-opinion/tools/notes/#_3","title":"\u7b14\u8bb0\u5de5\u5177\uff1f","text":"

    \u5bf9\u6211\u6765\u8bf4\u4e00\u4e2a\u5b8c\u5168\u9762\u5411\u8fc7\u7a0b\u7684 -> \u4e00\u4e2a\u5b8c\u5168\u9762\u5411\u5bf9\u8c61\u7684

    \u6bd4\u5982 notion \u662f\u9762\u5411\u6d41\u7a0b\u7684

    \u800c\u5982\u679c\u8981\u6709\u7ed3\u6784\u5199\u4f5c\uff0c\u5c31\u7528 mkdocs

    "},{"location":"docs/4-opinion/tools/notes/#notionobsidian","title":"\u9009\u62e9Notion\u548cObsidian","text":"

    \u5148\u5199\u4e00\u4e2a\u7b80\u5355\u7684\u7ed3\u8bba

    \u4f18\u70b9/\u5de5\u5177 Notion Obsidian \u8bed\u6cd5 \u81ea\u5df1\u7684\u4e00\u5957\u8bed\u6cd5\uff0c\u90e8\u5206\u662fmarkdown \u7eafmarkdown \u4e66\u5199\u901f\u5ea6 \u6162 \u5feb \u6587\u6863\u6574\u9f50\u7a0b\u5ea6 \u9ad8 \u4f4e \u90e8\u7f72\u5230mkdocs\u96be\u6613 \u6613\uff0c\u53ef\u76f4\u63a5\u7528 \u96be\uff0c\u9700\u8c03\u6574\u5f88\u591a\u683c\u5f0f \u5bfc\u51fa\u4e2d\u6587\u652f\u6301\u7a0b\u5ea6 \u53ea\u6709\u4e09\u79cd\u5b57\u4f53\uff0c\u90e8\u5206\u4e2d\u6587\u7f3a\u5b57 \u5b57\u4f53\u591a\uff0c\u652f\u6301\u6bd4\u8f83\u597d

    \u76ee\u524d\u6211\u9009\u62e9\u7684 workflow: \u5b8c\u5168\u629b\u5f03 Ob \u4e86\uff01

    graph TD\n    \u542c\u5199 --> Notion \n    Notion -- \u6709\u65f6\u95f4 --> mkdocs\n
    "},{"location":"docs/4-opinion/tools/notes/#_4","title":"\u6587\u732e\u7ba1\u7406\u5de5\u5177","text":"

    TODO

    \u5176\u5b9e\u4ed3\u5e93\u91cc\u672c\u6587\u4ef6\u5939\u4e0b\u7684asset\u91cc\u73b0\u5728\u6709\u4e2a\u600e\u4e48\u914d\u7f6ezotero\u7684ppt\uff0c\u592a\u61d2\u6ca1\u65f6\u95f4\u6574\u8fc7\u6765\uff0c\u53ef\u4ee5\u5148\u53bb\u4ed3\u5e93\u91cc\u627e\u627eorz

    "},{"location":"docs/4-opinion/tools/notes/#_5","title":"\u8bba\u6587\u7b14\u8bb0","text":"

    TODO

    "},{"location":"docs/4-opinion/tools/notes/#todolist","title":"TODOlist\uff1f","text":"

    \u5bf9\u6211\u6765\u8bf4\u4e5f\u9700\u8981\u4e00\u4e2a\u9762\u5411\u8fc7\u7a0b\u7684\uff08\u60f3\u5230\u9700\u8981\u505a\u6240\u4ee5\u8bb0\u4e0b\u6765\u7684\u6a21\u7cca\u4efb\u52a1\uff09+ \u4e00\u4e2a\u9762\u5411\u5bf9\u8c61\u7684\uff08\u4e00\u4e2a\u6709\u660e\u786e\u8d77\u6b62\u65f6\u95f4\u7684\u3001\u7ed3\u675f\u6807\u5fd7\u7684\u4efb\u52a1\uff09\u3002

    \u524d\u8005\u6211\u5e0c\u671b\u662f\u4e00\u4e2a\u53ef\u4ee5\u65e0\u9650\u6269\u5c55\u7684 list\uff0c\u5e76\u4e14\u5141\u8bb8\u6dfb\u52a0\u5404\u79cd sublist -> \u4e00\u4e2a\u5f88\u8212\u670d\u7684 markdown \u7f16\u8f91\u5668\u5373\u53ef\u3002

    \u540e\u8005\u5219\u6700\u597d\u6709\u5929\u3001\u5468\u3001\u6708\u7b49 view \u53ef\u4ee5\u770b\u4efb\u52a1\u7684 availability\u3002

    \u6211\u73b0\u5728\u7684\u65b9\u6cd5

    "},{"location":"docs/5-life/","title":"C'est la vie","text":"

    :material-circle-edit-outline: \u7ea6 4 \u4e2a\u5b57

    "},{"location":"docs/5-life/portfolio/","title":"Portfolio for CMU METALS Application","text":"

    :material-circle-edit-outline: \u7ea6 80 \u4e2a\u5b57

    Hi there! \ud83d\udc4b

    This site is a temporary portfolio for CMU METALS application.

    "},{"location":"docs/5-life/portfolio/#frontend-works","title":"Frontend Works","text":"Glyph

    Gun violence in US visualization

    "},{"location":"docs/5-life/portfolio/#graphic-design","title":"Graphic Design","text":"Calendar Card1 Card2 Card3

    logo

    "},{"location":"docs/5-life/annual-summary/","title":"Annual Summary \u5e74\u5ea6\u603b\u7ed3","text":"

    :material-circle-edit-outline: \u7ea6 10 \u4e2a\u5b57

    "},{"location":"docs/5-life/annual-summary/#contents","title":"Contents \u76ee\u5f55","text":""},{"location":"docs/5-life/annual-summary/2024/","title":"2024","text":"

    :material-circle-edit-outline: \u7ea6 967 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    Never believe in anything that claims to bring you success, never, never, never.

    We are what we talk about every day. Talking about math and science and technology makes us full of math and science and technology. Talking about the school administration fills us with nothing but only makes rule adaptors. Talking about unserious entertainment chores makes us trivial characters. Talking about the name of technologies instead of the real details and ideas behind them makes us only excited at the thoughts of 'I will learn/am learning this technology soon!' and become distracted suddenly after clicking into a post or a video about it.

    The topic of rules and policies also reminds me of the story of a senior professor who works on computational syntax in the school of international studies at my undergrad school, who ended his 10-year career here and joined another school of a similar (or slightly lower) ranking in Shanghai this year. I saw in his annual summary a sentence going like, in the next 10 years I plan to deal less with the administration materials and procedures but to put the stress on the research that I am really fond of; now given this change in my career, this goal seems pretty at hand.

    I sneered for sharing the same feeling with this prof. After joining UWaterloo, I felt that it was the first time in a long time that I was cared for by people around (administrators, profs, colleagues) as an ordinary student -- not because I was doing anything excellent -- in fact, I lagged behind my peers too much. And this is the reason why I should tell myself from time to time, that feeling well for now does not mean feeling well for good. Don't trust your feelings cause it does not lead you to the goal.

    To be specific in my researches -- I am mainly in (or to say, leading?) 3 researches this year, and none of them finally yields any paper. Sarcastically, another research that I am not leading was accepted fluently by a top conference (I sincerely thank the talented first author and other helpful co-workers who made the acceptance of this work so undoubtful on the meanwhile of critizing my unintelligence).

    I reflected a lot from the rest 3 research on why they currently failed (at least according to my criteria). The first research is a stupid (sorry) benchmark, whose birth now appears too reckless to me -- I was too slow to catch up with the user demands so now few people are using it. I think I will hereby say that I will not make a benchmark unless I desperately feel that a great number of people, or a few but important people, are or will be in need of it, or that I will be the only person who can make it across the world and during the following at least 10 years. Besides, my poor code and data management at the beginning of the year also led to several pitfalls which took me a great amount of time to fix, so now I would like to set up rules for myself, that is to always use unchangeable data ID to identify data pieces and to always consider the searching efficiency when designing the data structure, and to always think of reusing codes (thus I should maintain them more with oop structures). For the rest two projects which are on syntax and multimodal information encoding, I always felt that I didn't know how to introduce them to others esp. my roommates -- always commented that I had no improvement on the models and thus my research was of no use. Okay, I have no words to refute so how to refute will be one of the important questions that I will address in my papers.

    Here should have been another paragraph about my another research. It was such a painful experience collaborating with those collaborators that I don't want to recall and write it down here. If you are interested, let's talk about it privately.

    I spent much time pondering on choosing the industry or academia, some time looking for an internship, and little time submitting applications, and got response from none. I browsed several posts discussing the career planning for PhDs in the middle of which I found a website open-sourcing the salaries of employed professors from each Canadian university, with their real name. I am a bit shocked by the mere salaries of full professors. A solution to this question also desperately awaits in the following year.

    I also traveled a lot and watched a lot of musicals and operas this year (if you are interested in my recommendations, I am working on a list of my favorite musical works), but again I think I should talk about them less and less, since we will become what we talk about. Let's make our conversations full of technologies and ideas that will nurture our knowledge and thoughts.

    Anyway, my primary new year's resolution for 2025 is that,

    to have a paper such that, whenever people talk about this research area, they think of me; and whenever they think of me, they think of my paper.

    This will be the foundation of anything else.

    Besides, I hope I can have time to

    It was the most determined year and it was the most confused year, and it will be the most confused year and it will be the most determined year. I'm ready to see.

    "},{"location":"docs/5-life/read-watch-listen/","title":"Read, Watch, Listen \u4e66\u5f71\u97f3","text":"

    :material-circle-edit-outline: \u7ea6 14 \u4e2a\u5b57

    "},{"location":"docs/5-life/read-watch-listen/#my-top-10-updating","title":"My Top 10 (Updating)","text":""},{"location":"docs/5-life/read-watch-listen/#contents","title":"Contents","text":""},{"location":"docs/5-life/read-watch-listen/music-theory/","title":"\u4e50\u7406","text":"

    :material-circle-edit-outline: \u7ea6 3094 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_2","title":"\u6982\u8ff0","text":"

    \u4e00\u4e9b\u7269\u7406\u6982\u5ff5

    \u4e50\u7406\u7684\u57fa\u7840\u89c4\u5219\u6709\u4e09\u6761

    \u4ee5\u53ca\u4ee5\u6b64\u5ef6\u4f38\u7684\u51e0\u6761\u89c4\u5219

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_3","title":"\u58f0\u97f3","text":"

    !!! \ud83d\udca1 TODO: \u8fd9\u4e2a\u663e\u793a\u9891\u7387\u7684\u662f\u4ec0\u4e48\u5de5\u5177\uff1f

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_4","title":"\u7eaf\u97f3","text":"

    \u53ea\u5305\u542b\u4e00\u79cd\u9891\u7387\u7684\u97f3\u79f0\u4e3a\u7eaf\u97f3\u3002

    \u591a\u79cd\u9891\u7387\u590d\u5408\u5728\u4e00\u8d77\u7684\u97f3\u79f0\u4e3a\u590d\u5408\u97f3\u3002

    \u5b9e\u9645\u6f14\u594f\u4e2d\uff0c\u4e00\u822c\u6bd4\u5982\u6f14\u594f\u67d0\u9891\u7387\u7684\u97f3\u65f6\uff0c\u4e5f\u4f1a\u540c\u65f6\u4ea7\u751f2\u500d\u9891\u7387\uff08\u7b2c2\u6cdb\u97f3\uff0c\u57fa\u97f3\uff09\u30013\u500d\u9891\u7387\uff08\u7b2c3\u6cdb\u97f3\uff09\u2026\u7b49\u97f3\u3002\u8fd9\u662f\u7531\u4e8e\u58f0\u97f3\u5728\u7a7a\u6c14\u4e2d\u4f20\u64ad\u65f6\u53cd\u5c04\uff0c\u53cd\u5c04\u540e\u7684\u6ce2\u5f62\u4f1a\u4e0e\u539f\u6ce2\u5f62\u53e0\u52a0\u4ea7\u751fN\u500d\u6cdb\u97f3\u3002\u6bcf\u4e2a\u4e50\u5668\u7684\u97f3\u8272\u4e0d\u540c\uff0c\u672c\u8d28\u4e0a\u662f\u5b83\u4eec\u7684\u6cdb\u97f3\u7684\u632f\u5e45\u4e0e\u57fa\u97f3\u4e0d\u540c\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_5","title":"\u94a2\u7434","text":""},{"location":"docs/5-life/read-watch-listen/music-theory/#_6","title":"\u5c0f\u63d0\u7434","text":"

    \u51cf\u5f31\u5e45\u5ea6\u6ca1\u6709\u94a2\u7434\u5927\uff0c\u6240\u4ee5\u6bd4\u94a2\u7434\u5c16\u9510\uff08\u56e0\u4e3a\u9891\u7387\u8d8a\u9ad8\u8d8a\u5c16\u9510\uff09

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_7","title":"\u53cc\u7c27\u7ba1","text":"

    \u7b2c2\u6cdb\u97f3\u6bd4\u57fa\u97f3\u5927

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_8","title":"\u97f3\u5f8b","text":"

    \u97f3\u5f8b\u53ef\u4ee5\u8ba4\u4e3a\u662f\u6307\u4e00\u79cd\u201c\u9009\u62e9\u54ea\u4e9b\u9891\u7387\u6765\u4f5c\u4e3a\u4e00\u4ef6\u4e50\u5668\u7684\u97f3\u201d\u8fd9\u79cd\u89c4\u5219\u6216\u4ee5\u6b64\u9009\u51fa\u6765\u7684\u4e00\u7ec4\u9891\u7387\u3002\u5982\u679c\u5177\u4f53\u4e00\u70b9\u6765\u8bb2\uff0c\u4e50\u5668\u53ef\u4ee5\u62bd\u8c61\u6210\u4e00\u7ec4\u957f\u5ea6\u4e0d\u540c\u7684\u5f26\uff0c\u7531\u4e8e\u957f\u5ea6\u4e0d\u540c\u6240\u4ee5\u53d1\u51fa\u4e0d\u540c\u9891\u7387\u7684\u97f3\uff0c\u800c\u4e50\u5668\u8bbe\u8ba1\u8005\u6700\u5173\u5fc3\u7684\u95ee\u9898\u5c31\u662f\u600e\u6837\u8bbe\u8ba1\u8fd9\u7ec4\u5f26\u957f\uff08\u8fd9\u7ec4\u9891\u7387\uff09\uff0c\u4ee5\u4f7f\u53d1\u51fa\u7684\u9891\u7387\u6700\u7b26\u5408\u542c\u4f17\u5fc3\u4e2d\u90a3\u4e9b\u548c\u8c10\u7684\u97f3\u3002

    \u4e00\u4e2a\u5e38\u8bc6\u662f\uff0c\u4e00\u822c\u9700\u8981\u5dee\u5f02 5% \u53ca\u4ee5\u4e0a\u7684\u4e24\u4e2a\u9891\u7387\uff0c\u53ef\u4ee5\u88ab\u6b63\u5e38\u4eba\u5206\u8fa8\u4e3a\u4e24\u4e2a\u4e0d\u540c\u7684\u97f3\u3002\u6240\u4ee5\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u6700\u5c0f\u5dee\u8ddd\u4e0d\u5fc5\u5c0f\u4e8e\u8fd9\u4e2a\u9891\u7387\u5dee\u3002

    \u5728\u6b64\u989d\u5916\u63d0\u51fa\u4e00\u4e2a\u97f3\u7a0b\u7684\u5b9a\u4e49\uff1a\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u9891\u7387\u4e4b\u5dee\u53eb\u97f3\u7a0b\u3002\u6211\u4eec\u5728\u8fd9\u91cc\u4e3b\u8981\u5173\u5fc3\u7684\u97f3\u7a0b\u662f\u4e00\u4e2a\u516b\u5ea6\u3002

    \u8bbe\u5b9a\u97f3\u5f8b\u7684\u8457\u540d\u505a\u6cd5\u4e3b\u8981\u6709\u4ee5\u4e0b\u4e09\u79cd\uff0c\u4e09\u5206\u635f\u76ca\u6cd5\uff0c\u4e94\u5ea6\u76f8\u751f\u6cd5\uff0c\u548c\u5341\u4e8c\u5e73\u5747\u5f8b\uff0c\u6211\u4eec\u4f9d\u6b21\u4ecb\u7ecd\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_9","title":"\u8c03\u6027","text":"

    \u8c03\u6027\u4e3b\u8981\u5305\u542b\u4e86\u8c03\u9ad8\uff08\u4e3b\u97f3\uff09\u4e0e\u8c03\u5f0f\u4e24\u5927\u65b9\u9762\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_10","title":"\u8c03\u5f0f","text":"

    \u674e\u91cd\u5149\u300a\u57fa\u672c\u4e50\u7406\u901a\u7528\u6559\u7a0b\u300b\u4e2d\u5b9a\u4e49\u8c03\u5f0f\u4e3a

    \u51e0\u4e2a\u97f3\uff08\u4e00\u822c\u4e0d\u8d85\u8fc7\u4e03\u4e2a\uff0c\u4e0d\u5c11\u4e8e\u4e09\u4e2a\uff09\u6309\u7167\u4e00\u5b9a\u7684\u5173\u7cfb\uff08\u9ad8\u4f4e\u5173\u7cfb\u3001\u7a33\u5b9a\u4e0e\u4e0d\u7a33\u5b9a\u7684\u5173\u7cfb\u7b49\uff09\u8054\u7ed3\u5728\u4e00\u8d77\uff0c\u6784\u6210\u4e00\u4e2a\u97f3\u7ec4\u7ec7\uff0c\u5e76\u4ee5\u67d0\u4e00\u4e2a\u97f3\u4e3a\u4e2d\u5fc3\uff0c\u8fd9\u4e2a\u97f3\u7ec4\u7ec7\u5c31\u53eb\u201c\u8c03\u5f0f\u201d\u3002

    \u8c03\u5f0f\u4e4b\u95f4\u7684\u5dee\u5f02\u65e2\u6709\u97f3\uff0c\u4e5f\u6709\u97f3\u7a0b

    e.g. \u5206\u6790\u4e24\u4e2a\u8c03\u6bcf\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u97f3\u7a0b\u5173\u7cfb\u3002

    \u53e6\u4e00\u4e2a\u56de\u7b54\u5219\u8bf4\u533a\u522b\u5728\u4e0e\u4e3b\u97f3\u4e4b\u95f4\u7684\u97f3\u7a0b\u5173\u7cfb\u3002\u5e94\u8be5\u662f\u4e00\u6837\u7684\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_11","title":"\u5173\u7cfb\u5927\u5c0f\u8c03\u548c\u4e94\u5ea6\u5708","text":"

    \u4e0a\u8ff0\u4e24\u4e2a\u8c03\u662f\u5173\u7cfb\u5927\u5c0f\u8c03\uff0c\u4e5f\u5c31\u662f\u53ea\u6709\u5faa\u73af\u987a\u5e8f\u6539\u53d8\u4e86\uff0c\u5347\u964d\u5173\u7cfb\u662f\u76f8\u540c\u7684\u3002\u4ee5\u6b64\u6211\u4eec\u5f97\u5230\u4e00\u4e2a\u4e94\u5ea6\u5708

    \u8fd9\u4e2a\u56fe\u4e0a\u53ef\u4ee5\u5f97\u5230\u7684\u4fe1\u606f\u6709\uff1a

    \u5982\u4f55\u9ad8\u6548\u8bb0\u5fc6\u4e94\u5ea6\u5708\uff1a

    \u4e0a\u534811\u70b9\uff0cFat Cat Go Down And Eat Bread\uff0c\u6240\u4ee5\u4e94\u5ea6\u5708\u4ece11\u70b9\u5f00\u59cb\u987a\u65f6\u9488\u65b9\u5411\u662fFCGDAEB

    \u4e0b\u53486\u70b9\uff0cGo Down And Eat Bread\uff0c\u4ece6\u70b9\u65b9\u5411\u5f00\u59cb\u53c8\u662fGDAEB\uff0c\u7531\u4e8e\u662f\u665a\u4e0a\u6240\u4ee5\u90fd\u8981\u964d\u534a\u97f3

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_12","title":"\u5927\u8c03\u4e0e\u5c0f\u8c03","text":"

    \u4e0a\u8ff0\u4f8b\u5b50\u4e2d\u5f15\u5165\u4e86\u5927\u8c03\u4e0e\u5c0f\u8c03\u7684\u6982\u5ff5\u3002\u4e00\u4e2a\u66f4\u6b63\u5f0f\u7684\u5b9a\u4e49\u5982\u4e0b

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_13","title":"\u8c03\u53f7","text":"

    \u5f53\u628a\u4e0a\u8ff0\u97f3\u7a0b\u5173\u7cfb\u5957\u5165\u4e00\u4e2a\u7528\u4efb\u610f\u4e3b\u97f3\u5f00\u59cb\u7684\u97f3\u8282\uff0c\u5c31\u4f1a\u51fa\u73b0\u5e26\u5404\u79cd\u5347\u964d\u53f7\u7684\u8c03\u6027\uff0c\u6bcf\u79cd\u6709\u4e00\u4e2a\u8c03\u53f7\u6765\u547d\u540d\u3002

    \u8c03\u53f7\u7684\u4e00\u4e2a\u8bb0\u5fc6\u89c4\u5219\u662f

    \u53d7\u9650\u4e8e\u4ee5\u524d\u7684\u5f8b\u5236\u548c\u6bcf\u4e2a\u97f3\u9891\u7387\u4e4b\u95f4\u7684\u6bd4\u4f8b\u5173\u7cfb\uff0c\u4ee5\u524d\u662f\u65e0\u6cd5\u968f\u610f\u7ad9\u6362\u8c03\u6027\u7684\uff0c\u56e0\u4e3a\u5982\u679c\u8f6c\u6362\uff0c\u97f3\u7b26\u4e4b\u95f4\u7684\u6bd4\u4f8b\u5c31\u4e0e\u4e4b\u524d\u4e0d\u4e00\u6837\u4e86\u3002\u4f46\u56e0\u4e3a\u6709\u5341\u4e8c\u5e73\u5747\u5f8b\uff0c\u8f6c\u8c03\u53d8\u5f97\u968f\u610f\u3002

    \u4e0a\u8ff0\u8ba8\u8bba\u7684\u4e94\u5ea6\u5708\u548c\u5927\u5c0f\u8c03\u662f\u7406\u8bba\u5f97\u51fa\u7684\uff0c\u53ef\u80fd\u4e5f\u53ef\u4ee5\u79f0\u4e3a\u81ea\u7136\u97f3\u9636\u8c03\u5f0f\uff0c\u5f85\u8003\u8bc1\u3002\u4e0b\u9762\u6765\u4ecb\u7ecd\u4e00\u4e9b\u5386\u53f2\u4e0a\u5e38\u7528\u7684\u7ecf\u5178\u8c03\u5f0f\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#7","title":"7\u79cd\u4e2d\u53e4\u8c03\u5f0f\uff08\u6559\u4f1a\u8c03\u5f0f\uff09","text":"\u6559\u4f1a\u8c03\u5f0f \u97f3\u540d \u534a\u97f3\u95f4\u9694 \u7279\u70b9 Ionian\u5927 CDEFGAB 2212221 \u5927\u8c03\uff0c\u542c\u8d77\u6765\u660e\u6717\u5f00\u9614 Dorian DEFGABC 2122212 \u6c11\u65cf\u97f3\u4e50\uff0c\u5e38\u7528\u4e8e\u6e38\u620f\u548c\u7535\u5f71\u97f3\u4e50 Phrygian EFGABCD 1222122 \u5c0f\u4e8c\u5ea6\u7684Phrygian\u8c03\u5f0f\u542c\u8d77\u6765\u6c89\u91cd\uff0c\u5e38\u7528\u4e8e\u60b2\u5267\u7535\u5f71\u97f3\u4e50 Lydian FGABCDE 2221221 \u6ca1\u6709\u7eaf\u56db\u5ea6\u7684Lydian\u8c03\u5f0f\u9065\u8fdc\u6d69\u701a\uff0c\u6709\u79d1\u5e7b\u611f\uff0c\u5e38\u7528\u4e8e\u79d1\u5e7b\u7535\u5f71\u97f3\u4e50\u3002 Mixoly GABCDEF 2212212 \u6bd4\u5927\u8c03\u91cd\u53e0\u7387\u9ad8\uff08\u5177\u4f53\u91cd\u53e0\u7387\u7684\u8ba1\u7b97\u53ef\u4ee5\u89c1\u4e0b\u65b9\u5e16\u5b50\uff09\uff0c\u4e14\u660e\u6717\u751f\u52a8\u7684Mixoly\u5e38\u7528\u84dd\u8c03\u548c\u786c\u6838\u6447\u6eda Aeolian\u5c0f ABCDEFG 2122122 \u67d4\u548c\u6697\u6de1 Locrian BCDEFGA 1221222 \u6ca1\u6709\u7eaf\u4e94\u5ea6\u7684Locrian\u542c\u8d77\u6765\u6050\u6016\u9ed1\u6697\uff0c\u5e38\u7528\u4e8e\u707e\u96be\u6050\u6016\u7535\u5f71\u97f3\u4e50

    \u4e00\u4e2a\u6559\u4f1a\u8c03\u5f0f\u4e2d\u5177\u6709\u7684\u5ea6\u4e0e\u542c\u611f\u7684\u5173\u7cfb\u5206\u6790\u5982\u8fd9\u4e2a\u5e16\u5b50\u6240\u793a\uff1a

    \u97f3\u7a0b - \u97f3\u4e50\u7406\u8bba\u7684\u79d1\u5b66\u4e0e\u8d77\u6e90 - \u97f3\u4e50\u7406\u8bba\u81ea\u5b66\u5165\u95e8\u57fa\u7840\u6559\u7a0b (pianoabrsm.com)

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_14","title":"\u8c03\u53f7\u4e0e\u60c5\u7eea\u8272\u5f69\u7684\u5173\u7cfb","text":"

    \u81ea\u7136\u97f3\u9636\u5404\u8c03\u5f0f\u4e0e\u60c5\u7eea\u8272\u5f69\u7684\u5173\u7cfb\u3002\u5f88\u6709\u610f\u601d

    \u6211\u7684\u4e2a\u4eba\u89c2\u70b9\uff08TODO \u5f85\u66f4\u65b0\uff09

    \u8c03\u5f0f \u8272\u5f69 \u610f\u8c61 C \u5927\u8c03 C \u5c0f\u8c03 D \u5927\u8c03 \u91d1\u8272 \u91d1\u78a7\u8f89\u714c\u7684\u5bab\u6bbf D \u5c0f\u8c03 E \u5927\u8c03 E \u5c0f\u8c03 F \u5927\u8c03 F \u5c0f\u8c03 \u58a8\u84dd\u8272 \u9ed1\u4e91\u5bc6\u5e03\u6d77\u6d6a\u7ffb\u6d8c G \u5927\u8c03 G \u5c0f\u8c03 A \u5927\u8c03 A \u5c0f\u8c03 \u51b0\u5ddd\u84dd \u707f\u70c2\u9633\u5149\u4e0b\u95ea\u8000\u7684\u51b0\u5ddd B \u5927\u8c03 B \u5c0f\u8c03"},{"location":"docs/5-life/read-watch-listen/music-theory/#_15","title":"\u548c\u58f0\u7406\u8bba","text":"

    \u62cd\u97f3\u90fd\u662f\u548c\u58f0\uff0c\u4f46\u662f\u548c\u58f0\u4e0d\u4e00\u5b9a\u4ea7\u751f\u62cd\u97f3\uff0c\u56e0\u4e3a\u8d85\u51fa\u4eba\u8033\u53ef\u4ee5\u542c\u5230\u7684\u9891\u7387\u7684\u4e0d\u7b97\u62cd\u97f3\uff0c\u4e0d\u540c\u4e50\u5668\u53d1\u51fa\u7684\u4e5f\u4e0d\u53eb\u62cd\u97f3\uff0c\u540c\u65f6\u62cd\u97f3\u4e5f\u4e25\u683c\u8981\u6c42\u6240\u6709\u97f3\u7684\u9891\u7387\u8d77\u59cb\u4f4d\u7f6e\u4e25\u683c\u5bf9\u9f50\uff0c\u800c\u548c\u58f0\u53ea\u8981\u6709\u540c\u65f6\u53d1\u58f0\u7684\u65f6\u523b\u5373\u53ef\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_16","title":"\u548c\u58f0\u4e0e\u548c\u8c10\u7a0b\u5ea6\u7684\u5173\u7cfb","text":"

    \u9996\u5148\u6709\u76f8\u90bb\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u9891\u7387\u6bd4\u7ea6\u4e3a 1.06\uff08\u8bb0\u4e3ap\uff09\u3002\u5404\u4e2a\u97f3\u7a0b\u7684\u9891\u7387\u6bd4\uff08\u5373\uff0c\u76f8\u8ddd\u67d0\u4e2a\u97f3\u7a0b\u7684\u4f4e\u97f3\u4e0e\u9ad8\u97f3\u9891\u7387\u4e4b\u6bd4\uff09\u5219\u53ef\u4ee5\u7531\u5176\u97f3\u6570t\u6309\u516c\u5f0f\u7b97\u5f97 \\(1/2^{2t/12} = 1/06^{-2t}\\) \uff0c\u5176\u4e2d\uff0c\u7b49\u5f0f\u5de6\u8fb9\u662f\uff0c\u7b49\u5f0f\u53f3\u8fb9\u662f

    \u4e8e\u662f\u5f97\u5230\u7684\u6240\u6709\u5173\u7cfb\uff08\u5e76\u7ecf\u8fc7\u5b9e\u9a8c\uff09\u5f97\u5230\u4e00\u4e2a\u7ecf\u9a8c\u8868\u683c\u3002\u8fd9\u4e2a\u8868\u683c\u5e94\u8be5\u6700\u65e9\u662f\u7531\u516c\u5143\u524d\u6bd5\u8fbe\u54e5\u62c9\u65af\u5f97\u51fa\u7684\uff0c\u4ed6\u8868\u8ff0\u4e3a\uff1a\u4e24\u4e2a\u97f3\u7684\u7434\u5f26\u957f\u4e4b\u6bd4\u7684\u6700\u5927\u516c\u7ea6\u6570\u8d8a\u5c0f\uff0c\u4e24\u4e2a\u97f3\u540c\u65f6\u5f39\u594f\u5c31\u8d8a\u548c\u8c10\u3002\uff08\u5982\u679c\u56de\u5fc6\u6211\u4eec\u4e0a\u9762\u8ba8\u8bba\u7684\u6cdb\u97f3\uff0c\u6cdb\u97f3\u91cd\u53e0\u6bd4\u4f8b\u8d8a\u9ad8\u5c31\u8d8a\u548c\u8c10\uff09

    \u5341\u4e8c\u5e73\u5747\u5f8b\u97f3\u9ad8\u53c2\u8003\u7ebf\uff1a

    \u53ef\u67e5\u9605\u7684\u548c\u8c10\u4e0e\u4e0d\u548c\u8c10\u8868\u683c\uff1a

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_17","title":"\u4f34\u594f","text":"

    \u6bcf\u79cd\u8c03\u5f0f\u53ef\u91c7\u7528\u7684\u548c\u5f26\u79cd\u7c7b\uff0c\u53ef\u4ee5\u7528\u4ee5\u4e0b\u8868\u683c\u6765\u67e5\u9605\u3002

    \u4f34\u594f\u4e0d\u4e00\u5b9a\u662f\u548c\u5f26\u4e2d\u6240\u6709\u97f3\u4e00\u8d77\u5f39\uff0c\u4e5f\u53ef\u4ee5\u62c6\u89e3\u3002\u5e38\u89c1\u7684\u62c6\u89e3\u6cd5\u6709

    \u4e09\u548c\u5f26\u8f6c\u4f4d TODO

    \u6bd4\u5982\u6709\u4e00\u4e2a\u4e09\u548c\u5f26CEG\uff0c\u79f0\u4e3a\u539f\u4f4d\uff0c\u5c06C\u53d8\u6210\u9ad8\u516b\u5ea6\u7684C\uff0c\u79f0\u4e3a\u7b2c\u4e00\u8f6c\u4f4d\uff0c\u5728\u7b2c\u4e00\u8f6c\u4f4d\u57fa\u7840\u4e0a\u5c06E\u53d8\u6210\u9ad8\u516b\u5ea6\u7684E\uff0c\u79f0\u4e3a\u7b2c\u4e8c\u8f6c\u4f4d\u3002

    \u7ec8\u6b62\u5f0f TODO

    \u4e0d\u5b8c\u5168\u7ec8\u6b62\u5f0f TODO

    \u4e03\u548c\u5f26 TODO

    \u548c\u5f26 - \u97f3\u4e50\u7406\u8bba\u7684\u79d1\u5b66\u4e0e\u8d77\u6e90 - \u97f3\u4e50\u7406\u8bba\u81ea\u5b66\u5165\u95e8\u57fa\u7840\u6559\u7a0b (pianoabrsm.com)

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_18","title":"\u53c2\u8003\u8d44\u6599","text":""},{"location":"docs/5-life/read-watch-listen/musicals/","title":"Musicals","text":"

    :material-circle-edit-outline: \u7ea6 7 \u4e2a\u5b57

    Musical Recommendations

    "},{"location":"docs/5-life/read-watch-listen/musicals/#austrian-german-musicals","title":"Austrian & German Musicals","text":"

    TODO

    "}]} \ No newline at end of file +{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"\ud83c\udfdb\ufe0f Mini Babel Library","text":"

    :material-circle-edit-outline: \u7ea6 231 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    La biblioteca de Babel

    \u300c\u5b87\u5b99\uff08\u522b\u4eba\u7ba1\u5b83\u53eb\u56fe\u4e66\u9986\uff09\u7531\u8bb8\u591a\u516d\u89d2\u5f62\u7684\u56de\u5eca\u7ec4\u6210\uff0c\u6570\u76ee\u4e0d\u80fd\u786e\u5b9a\uff0c\u4e5f\u8bb8\u662f\u65e0\u9650\u7684\u300d \u2014\u2014 Jorge Luis Borges (1939)

    \u8fd9\u662f\u6211\u4e3b\u8981\u7528\u4e2d\u6587\u5199\u7684 BLOG\uff0c\u5927\u90e8\u5206\u5185\u5bb9\u662f\u5b66\u4e60\u7b14\u8bb0\u3002\u6211\u7684\u7b14\u8bb0\u4e0d\u591a\uff01\u4ee5\u540e\u4e5f\u4e0d\u4f1a\u591a\u7684(\u4fdd\u8d28\u4e0d\u4fdd\u91cf) \u6b22\u8fce\u6765\u770b\u6211\u7684\u7b14\u8bb0\uff01

    "},{"location":"#content-shortcut","title":"\ud83d\uded7 Content Shortcut\u23f0 \u66f4\u65b0\u8bb0\u5f55","text":"

    \ud83d\udcbb Computer Science

    Selection

    \ud83c\udf33 Linguistics

    Selection

    \ud83c\udf93 Deep Learning

    Selection

    \ud83d\udcad Opinions

    Selection

    \ud83c\udfb9 Life

    Selection

    2025-01-04\u00b6

    Music Theory \u4e50\u7406

    French Tense \u6cd5\u8bed\u65f6\u6001

    2025-01-01\u00b6

    2024 Summary

    2024-12-14\u00b6

    Main Page

    \u8bb0\u5f55\u751f\u6210\u5de5\u5177\uff1aTonyCrane/mkdocs-changelog-plugin"},{"location":"#_1","title":"\ud83e\uddd1\u200d\ud83e\udd1d\u200d\ud83e\uddd1 \u53cb\u94fe","text":"\u7ad9 \u5b9a\u4f4d\u662f \u672c\u7ad9\uff1a# \u63ba\u6742\u81ea\u5df1\u89c2\u70b9\u7684\u7b14\u8bb0 + \u5fc3\u5f97 \u4ed3\u5e93\uff1a\ud83d\udd17ZJUCourse \u5ba2\u89c2\u901a\u7528\u7684\u4e00\u4e2aZJU\u8bfe\u7a0b\u8d44\u6599\u5de5\u5177\u7bb1 \ud83d\udd17mem \u7684\u5c0f\u7ad9 \u5185\u5bb9\u4e3b\u8981\u662f\u7b97\u6cd5\u7b14\u8bb0 + ZJU \u8bfe\u7a0b\u7b14\u8bb0\u3002\u8c22\u8c22\u7b2c\u4e00\u4f4d\u627e\u6211\u6362\u53cb\u94fe\u7684\u5c0f\u670b\u53cb\uff01\u662f\u5f88\u5389\u5bb3\u7684 OIer \ud83d\udd17\u79d1\u5b66\u7a7a\u95f4 \u82cf\u5251\u6797\u82cf\u795e\u7684 blog\uff0c\u66f4\u65b0\u4e86\u5341\u51e0\u5e74\u4e86\uff0c\u4ef0\u6155"},{"location":"#_2","title":"\u260e\ufe0f \u8054\u7cfb\u4f5c\u8005","text":"

    \ud83d\udceb \u90ae\u7bb1 | \ud83e\uddd1\u200d\ud83d\udcbb \u4e3b\u9875

    "},{"location":"docs/1-cs/","title":"Computer Science Notes","text":"

    :material-circle-edit-outline: \u7ea6 460 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    This section mainly consists of my selected notes on the course/project/assignment of the computer science courses from Zhejiang University. \u672c\u7ae0\u8282\u5185\u5bb9\u4e3b\u8981\u4e3a\u6d59\u6c5f\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662\u8bfe\u7a0b\u7684\u8bfe\u7a0b/\u9879\u76ee/\u4f5c\u4e1a\u7b14\u8bb0\u3002

    I respect the honest code of computer science school of Zhejiang University and do not publish any content against this code (e.g., solutions of the assignments or source codes of the projects). Please contact me if you find anything that has the risk to violate the code.

    "},{"location":"docs/1-cs/#compass","title":"\ud83e\udded Compass","text":"

    \u5728\u7f51\u4e0a\u627e\u7b14\u8bb0/\u8d44\u6e90\u7684\u65f6\u5019\uff0c\u6211\u7684\u6700\u5927\u611f\u53d7\u4e4b\u4e00\u662f\u867d\u7136\u8d44\u6e90\u5f88\u591a\u5f88\u591a\uff0c\u4f46\u662f\u5e38\u5e38\u4e0d\u77e5\u9053\u67d0\u4e2a\u8d44\u6e90\u6709\u591a\u91cd\u8981\uff0c\u65e0\u6cd5\u8bc4\u4f30\u91cc\u9762\u6db5\u76d6\u4e86\u591a\u5c11\u4e1c\u897f\u4ece\u800c\u4e0d\u77e5\u9053\u8981\u4e0d\u8981\u70b9\u5f00\uff0c\u6216\u8005\u65e0\u6cd5\u4f30\u8ba1\u5728\u671f\u672b\u6709\u9650\u7684\u65f6\u95f4\u91cc\u5e94\u8be5\u82b1\u591a\u5c11\u65f6\u95f4\u590d\u4e60\u67d0\u4e2a\u8d44\u6e90\u3002\u6211\u6b63\u5728\u52aa\u529b\u5728\u8fd9\u91cc\u5efa\u4e00\u4e2a\u5c1a\u80fd\u8bfb\u7684\u8d44\u6e90\u7684 pagetable\uff0c\u4ee5\u9632\u4e0d\u5e78\u7684\u6e38\u5ba2\u4ece\u4fa7\u8fb9\u680f\u6e38\u8d70\u8fdb\u672c\u56fe\u4e66\u9986\u7684\u5783\u573e\u5806\u6f29\u6da1\ud83c\udf00\u3002\u5982\u679c\u6211\u76ee\u524d\u7684\u7b14\u8bb0\u5728\u8fd9\u4e2a\u7ef4\u5ea6\u4e0a\u505a\u5f97\u4e0d\u597d\uff0c\u8bf7\u8054\u7cfb\u6211\u6216\u8005\u5411\u6211\u63d0 issue \u50ac\u6211\u6539 \u8c22\u8c22\uff01

    \u56fe\u4f8b

    \ufe0f\ud83d\udcd8 \ufe0f\ud83d\udcd6 \ud83e\uddea \ud83d\udd17 \u5b8c\u6210\u5ea6\u4e0d\u9ad8\uff0c\u5f03\u5751\u6216\u5728\u5199\uff0c\u4e0d\u63a8\u8350\u9605\u8bfb \uff08\u7279\u6307\u7406\u8bba\uff09\u5b8c\u6210\u5ea6\u8db3\u591f\u9ad8\uff0c\u53ef\u4ee5\u9605\u8bfb\uff01 \u4ec5\u5b9e\u9a8c\u8d44\u6e90\uff0c\u672a\u5199\u7406\u8bba\u90e8\u5206 \u540c\u7c7b\u4f18\u8d28\u6216\u66f4\u4f18\u8d44\u6e90\u63a8\u8350 \u7c7b\u522b \u8bfe.. \u7f16\u7a0b\u8bed\u8a00 \ud83d\udcd8C\u5c16 \ud83d\udcd8C++ \ud83d\udd17\u8bb2\u4e49@\u6684 \ud83d\udcd8Verilog \ud83d\udd17\u5b9e\u9a8c@\u74dc \ud83d\udd17playground@HDLB \ud83d\udcd8Python \ud83d\udcd6x86\u6c47\u7f16 \u8ba1\u7b97\u673a\u79d1\u5b66 \ud83d\udcd8\u79bb\u6563\u6570\u5b66 \ud83d\udd17\u8bb2\u4e49@Kaleo \ud83d\udcd8FDS \ud83d\udcd8ADS \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8\u8ba1\u7b97\u7406\u8bba \ud83d\udd17\u8bb2\u4e49@\u6684 \ufe0f\ud83d\udcd8\u7f16\u8bd1\u539f\u7406 \ud83d\udd17\u8bb2\u4e49@\u6684 \u8f6f\u4ef6 \ud83e\uddeaOS \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8DBMS \ud83d\udcd8\u8ba1\u7f51 \ud83d\udcd8\u8f6f\u5de5 \u786c\u4ef6 \ud83d\udcd8\u6570\u903b \ud83d\udd17\u8bb2\u4e49@\u4fee \ud83d\udcd8\u8ba1\u6982 \ud83d\udcd8\u8ba1\u7ec4 \ud83d\udd17\u8bb2\u4e49@\u6684&\u4fee \ud83d\udcd6\u4f53\u7cfb"},{"location":"docs/1-cs/#contents","title":"\ud83d\udcdd Contents","text":""},{"location":"docs/1-cs/assembly-x86/","title":"x86\u6c47\u7f16","text":"

    :material-circle-edit-outline: \u7ea6 5487 \u4e2a\u5b57 :fontawesome-solid-code: 47 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f

    "},{"location":"docs/1-cs/assembly-x86/#lab","title":"Lab\u8bb0\u5f55","text":"

    Failure

    Lab\u5df2\u7ecf\u5168\u90e8\u6362\u6389\uff0c\u8fd9\u90e8\u5206\u4f5c\u4e1a\u4ecb\u7ecd\u65e0\u6cd5\u53c2\u8003\u4e86\u3002

    "},{"location":"docs/1-cs/assembly-x86/#6","title":"6\u79cd\u5bfb\u5740\u65b9\u5f0f\u4e0e\u5176\u4f5c\u7528","text":"\u8bf4\u660e \u793a\u4f8b \u4f5c\u7528 \u7acb\u5373\u5bfb\u5740 mov eax,56H \u901a\u5e38\u7528\u4e8e\u8d4b\u503c \u76f4\u63a5\u5bfb\u5740 mov eax,[1255887H] \u901a\u5e38\u7528\u4e8e\u5904\u7406\u53d8\u91cf \u5bc4\u5b58\u5668\u5bfb\u5740 mov eax,[edi] \u5730\u5740\u5728\u5bc4\u5b58\u5668\u4e2d \u5bc4\u5b58\u5668\u76f8\u5bf9\u5bfb\u5740 mov eax,[edi+20H] \u5e38\u7528\u4e8e\u8bbf\u95ee\u6570\u7ec4\u548c\u7ed3\u6784 \u57fa\u5740\u52a0\u53d8\u5740\u5bfb\u5740 mov eax,[EBP+ESI] \u5e38\u7528\u4e8e\u8bbf\u95ee\u6570\u7ec4 \u76f8\u5bf9\u57fa\u5740\u52a0\u53d8\u5740\u5bfb\u5740 mov eax,[EBX+EDI-10H] \u5e38\u7528\u4e8e\u8bbf\u95ee\u7ed3\u6784"},{"location":"docs/1-cs/assembly-x86/#obj-dump","title":"obj dump","text":"

    \u6e90\u4ee3\u7801\u6587\u4ef6\u540dmytest.c

    gcc -c -g -o mytest mytest.c\nobjdump -s -d main.o > main.o.txt\n

    \u76ee\u6807\u6587\u4ef6\u53cd\u6c47\u7f16\uff0c\u540c\u65f6\u663e\u793a\u6e90\u4ee3\u7801

    gcc -g -c -o main.o main.c\nobjdump -S -d main.o > main.o.txt\n

    \u663e\u793a\u6e90\u4ee3\u7801\u7684\u540c\u65f6\u663e\u793a\u884c\u53f7

    objdump -j .text -ld -C -S main.o > main.o.txt\n

    \u53ef\u6267\u884c\u6587\u4ef6\u53cd\u6c47\u7f16

    gcc -o main main.c\nobjdump -s -d main > main.txt\n

    \u540c\u65f6\u663e\u793a\u6e90\u4ee3\u7801

    gcc -g -o main main.c\nobjdump -S -d main > main.txt\n
    "},{"location":"docs/1-cs/assembly-x86/#_1","title":"\u671f\u672b\u8003\u8bd5","text":"
    1. \u662f\u975e\u9898(10\u4e2a\uff0c\u6bcf\u98981\u5206\uff0c\u517110\u5206)
    2. \u586b\u7a7a(15\u4e2a\uff0c\u6bcf\u7a7a2\u5206\uff0c\u517130\u5206)\uff1a

    3. \u7a0b\u5e8f\u586b\u7a7a\u9898(3\u9898\uff0c\u6bcf\u989810\u5206\uff0c\u517130\u5206)

      \u4e00\u822c\u90fd\u4f1a\u7528stack\u538b\u5165\u53c2\u6570 \u4f1a\u7ed9\u51fac\u8bed\u8a00\u7684\u539f\u578b\uff08\uff1f\uff0c\u53c2\u6570\u7684\u538b\u5165\u987a\u5e8f\u4ece\u53f3\u5230\u5de6\uff0ccaller\u6e05\u7406 pascal\uff0c\u4ece\u5de6\u5230\u53f3\uff0ccallee\u6e05\u7406 stdcall\uff0c\u4ece\u53f3\u5230\u5de6\uff0ccaller\u6e05\u7406 \u90fd\u7528ax\u8fd4\u56de\u53c2\u6570 \u4e00\u822c\u4e24\u4e2a\u7a7a\u4e0d\u53ef\u4ee5\u4ea4\u6362\u3002\u3002\u3002 \u5148\u81ea\u5df1\u5199\u4e00\u904d\u518d\u586b \uff08\u4e00\u822c20\u51e0\u884c\u7684\u7a0b\u5e8f\uff09

    4. \u7a0b\u5e8f\u9605\u8bfb(2\u9898\uff0c\u6bcf\u98985\u5206\uff0c\u517110\u5206) \u4f1a\u95ee\u8fd0\u884c\u7ed3\u679c\u548c\u4e2d\u95f4\u7ed3\u679c\uff08#\uff09\uff08\u5982\u679c\u6709\u5faa\u73af\uff0c\u6bcf\u6b21\u5faa\u73af\u5230\u90fd\u8981\u5199\uff0c\u4f46\u662f\u4e0d\u4f1a\u592a\u591a\uff09

    \u4e0d\u4f1a\u6709\u76f4\u63a5\u624b\u5199\u4e00\u6574\u4e2a\u7a0b\u5e8f\u7684\u9898

    \u91cd\u70b9\uff1a \u51fd\u6570\u53c2\u6570\u4f20\u9012\uff0c\u5982\u4f55\u6784\u9020\u4e00\u4e2a\u5806\u6808\u6846\u67b6\uff0cebp\u3002\u3002 \u9700\u8981\u770b\u61c2\u662f\u4e0d\u662f\u9012\u5f52\uff0c \u6709\u4e00\u4e2a\u7a0b\u5e8f\u586b\u7a7a\u4f1a\u51fa\u5355\u6b65\u8c03\u8bd5\uff0c\u8fb9\u89e3\u5bc6\u8fb9\u52a0\u5bc6\u90a3\u4e2a\u3002\u3002 \u4e0d\u4f1a\u8003\u4fdd\u62a4\u6a21\u5f0f\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_2","title":"\u590d\u4e60","text":""},{"location":"docs/1-cs/assembly-x86/#intel-808680386-cpu","title":"Intel 8086/80386 CPU \u529f\u80fd\u7ed3\u6784","text":""},{"location":"docs/1-cs/assembly-x86/#_3","title":"\u5de5\u4f5c\u65b9\u5f0f","text":"
    1. \u4ece\u5b58\u50a8\u5668\u4e2d\u53d6\u4e00\u6761\u6307\u4ee4
    2. \u5206\u6790\u6307\u4ee4\u7684\u64cd\u4f5c\u7801
    3. \u4ece\u5b58\u50a8\u5668\u4e2d\u8bfb\u53d6\u64cd\u4f5c\u6570
    4. \u6267\u884c\u6307\u4ee4
    5. \u5199\u5165\u7ed3\u679c\u96c6
    6. \u56de\u52301

    \u8fd0\u7b97\u5668\u8fdb\u884c\u4fe1\u606f\u5904\u7406\uff0c\u5bc4\u5b58\u5668\u8fdb\u884c\u4fe1\u606f\u5b58\u50a8\uff0c\u63a7\u5236\u5668\u63a7\u5236\u5404\u79cd\u5668\u4ef6\u5de5\u4f5c\uff0c\u603b\u7ebf\u8fde\u63a5\u5404\u79cd\u5668\u4ef6\u3002

    "},{"location":"docs/1-cs/assembly-x86/#163280x86-view","title":"16\u4f4d\u548c32\u4f4d\u768480x86\u7684\u533a\u522b - \u64cd\u4f5c\u7cfb\u7edfview","text":""},{"location":"docs/1-cs/assembly-x86/#_4","title":"\u903b\u8f91\u5730\u5740\u4e0e\u7269\u7406\u5730\u5740\u8f6c\u6362\uff1a","text":"

    1234h:0058h \u8f6c\u5316\u6210\u7269\u7406\u5730\u5740=12340h+0058h=12398h \u8865\u7801

    "},{"location":"docs/1-cs/assembly-x86/#_5","title":"\u6807\u5fd7\u4f4d","text":"

    \u72b6\u6001\u6807\u5fd7\uff1aCF ZF SF OF AF PF \u63a7\u5236\u6807\u5fd7\uff1aDF(direction flags) TF(trace/trap flag) IF(interrupt flag)

    "},{"location":"docs/1-cs/assembly-x86/#_6","title":"\u6570\u636e\u5728\u5185\u5b58\u4e2d\u7684\u5b58\u653e\u89c4\u5f8b\uff1a","text":"

    \u5c0f\u7aef\u683c\u5f0f\u3002\u4f4e\u5b57\u8282\u5728\u524d\uff0c\u9ad8\u5b57\u8282\u5728\u540e\u3002 \u8bbeds=1000h, bx=2000h, ax=1234h Mov ds:[bx], ax \u6267\u884c\u540e1000:2001\u6307\u5411\u7684\u5b57\u8282=12h

    "},{"location":"docs/1-cs/assembly-x86/#_7","title":"\u5bc4\u5b58\u5668","text":"

    \u603b\u7ed3

    \u5bc4\u5b58\u5668 \u7c7b\u522b \u7528\u9014 AX \u6570\u636e\u5bc4\u5b58\u5668 \u7b97\u672f\u8fd0\u7b97\u4e2d\u7684\u4e3b\u8981\u5bc4\u5b58\u5668\uff0c\u5728\u4e58\u9664\u8fd0\u7b97\u4e2d\u7528\u6765\u5236\u5b9a\u88ab\u9664\u6570\uff0c\u4e5f\u662f\u4e58\u9664\u8fd0\u7b97\u540e\u7ed3\u679c\u7684\u9ed8\u8ba4\u5b58\u50a8\u5355\u5143\u3002\u53e6\u5916I/O\u6307\u4ee4\u5747\u4f7f\u7528\u8be5\u5bc4\u5b58\u5668\u4e0eI/O\u8bbe\u5907\u4f20\u9001\u4fe1\u606f\u3002 BX \u6570\u636e\u5bc4\u5b58\u5668 \u6307\u4ee4\u5bfb\u5740\u65f6\u5e38\u7528\u505a\u57fa\u5740\u5bc4\u5b58\u5668\uff0c\u5b58\u5165\u504f\u79fb\u91cf\u6216\u504f\u79fb\u91cf\u7684\u6784\u6210\u6210\u5206 CX \u6570\u636e\u5bc4\u5b58\u5668 \u5728\u5faa\u73af\u6307\u4ee4\u64cd\u4f5c\u6216\u4e32\u5904\u7406\u6307\u4ee4\u4e2d\u9690\u542b\u8ba1\u6570 DX \u6570\u636e\u5bc4\u5b58\u5668 \u5728\u53cc\u5b57\u8282\u957f\u8fd0\u7b97\u4e2d\u4e0eAX\u6784\u621032\u4f4d\u64cd\u4f5c\u6570\uff0cDX\u4e3a\u9ad816\u4f4d\u3002\u5728\u67d0\u4e9bI/O\u6307\u4ee4\u4e2d\uff0cDX\u88ab\u7528\u6765\u5b58\u653e\u7aef\u53e3\u5730\u5740 SP \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u59cb\u7ec8\u662f\u6808\u9876\u7684\u4f4d\u7f6e\uff0c\u4e0eSS\u5bc4\u5b58\u5668\u4e00\u8d77\u6784\u6210\u6808\u9876\u6570\u636e\u7684\u7269\u7406\u5730\u5740 BP \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u7cfb\u7edf\u9ed8\u8ba4\u5176\u6307\u5411\u5806\u6808\u4e2d\u67d0\u4e00\u5355\u5143\uff0c\u5373\u63d0\u4f9b\u6808\u4e2d\u8be5\u5355\u5143\u7684\u504f\u79fb\u91cf\u3002\u52a0\u6bb5\u524d\u7f00\u540e\uff0cBP\u53ef\u4f5c\u4e3a\u975e\u5806\u6808\u6bb5\u7684\u5730\u5740\u6307\u9488 SI \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u4e0eDS\u8054\u7528\uff0c\u6307\u793a\u6570\u636e\u6bb5\u4e2d\u67d0\u64cd\u4f5c\u7684\u504f\u79fb\u91cf\u3002\u5728\u505a\u4e32\u5904\u7406\u65f6\uff0cSI\u6307\u793a\u6e90\u64cd\u4f5c\u6570\u5730\u5740\uff0c\u5e76\u6709\u81ea\u52a8\u589e\u91cf\u548c\u81ea\u52a8\u51cf\u91cf\u7684\u529f\u80fd\u3002\u53d8\u5740\u5bfb\u5740\u65f6\uff0cSI\u4e0e\u67d0\u4e00\u4f4d\u79fb\u91cf\u5171\u540c\u6784\u6210\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf DI \u6307\u9488\u53ca\u53d8\u5740\u5bc4\u5b58\u5668 \u4e0eDS\u8054\u7528\uff0c\u6307\u793a\u6570\u636e\u6bb5\u4e2d\u67d0\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf\uff0c\u6216\u4e0e\u67d0\u4e00\u4f4d\u79fb\u91cf\u5171\u540c\u6784\u6210\u64cd\u4f5c\u6570\u7684\u504f\u79fb\u91cf\uff0c\u4e32\u5904\u7406\u64cd\u4f5c\u65f6\uff0cDI\u6307\u793a\u9644\u52a0\u6bb5\u4e2d\u76ee\u7684\u5730\u5740\uff0c\u5e76\u6709\u81ea\u52a8\u589e\u91cf\u548c\u51cf\u91cf\u7684\u529f\u80fd\u3002 CS \u6bb5\u5bc4\u5b58\u5668 \u5b58\u653e\u5f53\u524d\u7a0b\u5e8f\u7684\u6307\u793a\u4ee3\u7801 DS \u6bb5\u5bc4\u5b58\u5668 \u5b58\u653e\u7a0b\u5e8f\u6240\u8bbe\u8ba1\u7684\u6e90\u6570\u636e\u6216\u7ed3\u679c SS \u6bb5\u5bc4\u5b58\u5668 \u4ee5\u201c\u5148\u5165\u540e\u51fa\u201d\u4e3a\u539f\u5219\u7684\u6570\u636e\u533a ES \u6bb5\u5bc4\u5b58\u5668 \u8f85\u52a9\u6570\u636e\u533a\uff0c\u5b58\u653e\u4e32\u6216\u5176\u5b83\u6570\u636e IP \u63a7\u5236\u5bc4\u5b58\u5668 \u5b83\u59cb\u7ec8\u6307\u5411\u5f53\u524d\u5c06\u8981\u6267\u884c\u6307\u4ee4\u5728\u4ee3\u7801\u6bb5\u4e2d\u7684\u504f\u79fb\u91cf FR \u63a7\u5236\u5bc4\u5b58\u5668 \u63a7\u5236\u6807\u5fd7\u4f4d

    "},{"location":"docs/1-cs/assembly-x86/#_8","title":"\u901a\u7528\u5bc4\u5b58\u5668","text":"

    IA-32\u67b6\u6784\u4e2d\u4e00\u5171\u67094\u4e2a32\u4f4d\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u4fdd\u5b58\u4e34\u65f6\u6570\u636e\uff0c\u8fd94\u4e2a\u901a\u7528\u5bc4\u5b58\u5668\u53ef\u4ee5\u5f53\u4f5c16\u4f4d\u7528\uff0c\u4e5f\u53ef\u4ee5\u4f5c8\u4f4d\u7528\u3002

    AX BX CX DX\uff1a\u6570\u636e\u5bc4\u5b58\u5668\uff0c\u6bcf\u4e2a\u6570\u636e\u5bc4\u5b58\u5668\u90fd\u53ef\u4ee5\u62c6\u6210\u4e24\u4e2a 8 \u4f4d\u5bc4\u5b58\u5668\u72ec\u7acb\u4f7f\u7528\uff0c\u5982 AX \u53ef\u62c6\u5206\u4e3a AH \u548c AL\uff0cBX \u62c6\u5206\u4e3a BH \u548c BL \u7b49\u3002H \u548c L \u5206\u522b\u8868\u793a\u9ad8 8 \u4f4d\u548c\u4f4e 8 \u4f4d\u3002

    AX(accumulator)\uff1a\u7d2f\u52a0\u5668\u3002\u5728\u4e58\u9664\u6cd5\u8fd0\u7b97\u3001\u4e32\u8fd0\u7b97\u3001 I/O \u6307\u4ee4\u4e2d\u90fd\u4f5c\u4e3a\u4e13\u7528\u5bc4\u5b58\u5668\uff1b BX (base)\uff1a\u57fa\u5740\u5bc4\u5b58\u5668\uff0c\u5e38\u7528\u4e8e\u5b58\u6863\u5185\u5b58\u5730\u5740\u3002

    CX (count)\uff1a\u8ba1\u6570\u5bc4\u5b58\u5668\u3002\u5e38\u7528\u4e8e\u5b58\u653e\u5faa\u73af\u8bed\u53e5\u7684\u5faa\u73af\u6b21\u6570\uff0c\u5b57\u7b26\u4e32\u64cd\u4f5c\u4e2d\u4e5f\u5e38\u7528\u3002

    DX (data)\uff1a\u6570\u636e\u5bc4\u5b58\u5668\u3002\u5e38\u5e38\u548cEAX\u4e00\u8d77\u4f7f\u7528\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_9","title":"\u53d8\u5740\u5bc4\u5b58\u5668","text":"

    \u5b58\u653e\u5728\u53d8\u52a8\u7684\u5185\u5b58\u5730\u5740

    ESI(source index): \u6e90\u53d8\u5740\u5bc4\u5b58\u5668\uff0c\u901a\u5e38\u5b58\u653e\u8981\u5904\u7406\u7684\u6570\u636e\u7684\u5185\u5b58\u5730\u5740\u3002

    EDI(destination index)\uff1a\u76ee\u7684\u53d8\u5740\u5bc4\u5b58\u5668\uff0c\u901a\u5e38\u5b58\u653e\u5904\u7406\u540e\u7684\u6570\u636e\u7684\u5185\u5b58\u5730\u5740\u3002

    ESI\u548cEDI\u5e38\u7528\u6765\u914d\u5408\u4f7f\u7528\u5b8c\u6210\u6570\u636e\u7684\u8d4b\u503c\u64cd\u4f5c

    rep movs dword ptr[edi], dword ptr[esi];\n

    \u8fd9\u53e5\u7684\u610f\u601d\u662f\u628aESI\u6307\u5411\u7684\u5185\u5b58\u5730\u5740\u4e2d\u7684\u5185\u5bb9\u590d\u5236\u5230EDI\u6240\u6307\u5411\u7684\u5185\u5b58\u4e2d\uff0c\u6570\u636e\u957f\u5ea6\u5728ECX\u4e2d\u6307\u5b9a\u3002

    "},{"location":"docs/1-cs/assembly-x86/#_10","title":"\u6307\u9488\u5bc4\u5b58\u5668","text":"

    ESP\uff08stack pointer\uff09\uff1a\u5806\u6808\u6307\u9488\u5bc4\u5b58\u5668\u3002SS\uff1aSP\u6307\u5411\u5806\u6808\u7684\u6808\u9876\uff0c\u56e0\u6b64\u867d\u7136\u662f\u901a\u7528\u5bc4\u5b58\u5668\uff0c\u4f46\u4e0d\u5e94\u968f\u4fbf\u6539\u53d8SP\u7684\u503c\u3002\u4e0d\u53ef\u4ee5\u4f5c\u4e3a\u901a\u7528\u5bc4\u5b58\u5668\u4f7f\u7528\uff0cESP\u5b58\u653e\u5f53\u524d\u5806\u6808\u6808\u9876\u7684\u5730\u5740\uff0c\u4e00\u822c\u60c5\u51b5\u4e0b\uff0cESP\u548cEBP\u8054\u5408\u4f7f\u7528\u6765\u8bbf\u95ee\u51fd\u6570\u4e2d\u7684\u53c2\u6570\u548c\u5c40\u90e8\u53d8\u91cf\u3002 EBP\uff08base pointer\uff09\uff1a\u57fa\u5740\u6307\u9488\u5bc4\u5b58\u5668\u3002\u53ef\u4ee5\u4f5c\u4e3a\u901a\u7528\u5bc4\u5b58\u5668\u7528\u4e8e\u5b58\u653e\u64cd\u4f5c\u6570\uff0c\u5e38\u7528\u6765\u4ee3\u66ff\u5806\u6808\u6307\u9488\u8bbf\u95ee\u5806\u6808\u7684\u6570\u636e\u3002 EIP\uff1a\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668\uff0c\u603b\u662f\u6307\u5411\u4e0b\u4e00\u6761\u8981\u6267\u884c\u7684\u6307\u4ee4\u7684\u5730\u5740\u3002 \u5e38\u89c1\u7684\u8bbf\u95ee\u5806\u6808\u6307\u4ee4\uff1a

    push ebp\nmov ebp, esp\nsub esp, 78\npush esi\npush edi\ncmp dword ptr [ebp+8], 0\n

    ss\u6808\u6bb5\u5bc4\u5b58\u5668 sp\u6808\u9876\u6307\u9488\u5bc4\u5b58\u5668 bp\u9ed8\u8ba4\u7684\u6808\u5bfb\u5740\u5bc4\u5b58\u5668

    "},{"location":"docs/1-cs/assembly-x86/#_11","title":"\u6807\u5fd7\u5bc4\u5b58\u5668","text":"

    \u6807\u5fd7\u5bc4\u5b58\u5668EFLAGS\u4e00\u5171\u670932\u4f4d\uff0c\u5728\u8fd932\u4f4d\u4e2d\u5927\u90e8\u5206\u662f\u4fdd\u7559\u7ed9\u7f16\u5199\u64cd\u4f5c\u7cfb\u7edf\u7684\u4eba\u7528\u7684\u3002

    IP (instruction pointer)\uff1a\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668\u3002\u4ee3\u7801\u6bb5\u5bc4\u5b58\u5668 CS \u548c\u6307\u4ee4\u6307\u9488\u5bc4\u5b58\u5668 IP \u662f 8086CPU \u4e2d\u6700\u5173\u952e\u7684\u4e24\u4e2a\u5bc4\u5b58\u5668\u3002\u5b83\u4eec\u5206\u522b\u7528\u6765\u63d0\u4f9b\u5f53\u524d\u6307\u4ee4\u7684\u6bb5\u5730\u5740\u548c\u504f\u79fb\u5730\u5740\u3002\u5373\u4efb\u610f\u65f6\u523b\uff0c8086CPU \u5c06 CS:IP \u6307\u5411\u7684\u5185\u5bb9\u5f53\u505a\u547d\u4ee4\u6267\u884c\u3002\u6bcf\u6761\u6307\u4ee4\u8fdb\u5165\u6307\u4ee4\u7f13\u51b2\u5668\u540e\u3001\u6267\u884c\u524d\uff0cIP += \u6240\u8bfb\u53d6\u6307\u4ee4\u7684\u957f\u5ea6\uff0c\u4ece\u800c\u6307\u5411\u4e0b\u4e00\u6761\u6307\u4ee4\u3002\u7528\u6237\u4e0d\u80fd\u76f4\u63a5\u8bbf\u95ee IP \u5bc4\u5b58\u5668\u3002

    FL (flags)\uff1a\u6807\u5fd7\u5bc4\u5b58\u5668\u3002\u4e0e\u5176\u4ed6\u5bc4\u5b58\u5668\u4e00\u6837\uff0c\u6807\u5fd7\u5bc4\u5b58\u5668\u4e5f\u6709 16 \u4f4d\uff0c\u4f46\u662f\u6807\u5fd7\u5bc4\u5b58\u5668\u53ea\u7528\u5230\u5176\u4e2d\u7684 9 \u4f4d\u3002\u8fd9 9 \u4f4d\u5305\u62ec 6 \u4e2a\u72b6\u6001\u6807\u5fd7\u548c 3 \u4e2a\u63a7\u5236\u6807\u5fd7\uff0c\u53c2\u89c1\u4e0b\u9762\u7684\u201c\u6807\u5fd7\u4f4d\u201d\u3002

    OF\uff08Overflow Flag\uff09:\u6ea2\u51fa\u6807\u5fd7\uff0c\u6ea2\u51fa\u65f6\u4e3a1\uff0c\u5426\u5219\u7f6e0\u3002\u4e24\u4e2a\u6b63\u6570\u76f8\u52a0\u53d8\u8d1f\uff0c\u6216\u4e24\u4e2a\u8d1f\u6570\u76f8\u52a0\u53d8\u6b63\u4f1a\u6ea2\u51fa\u3002#

    DF \uff08Direction Flag\uff09:\u65b9\u5411\u6807\u5fd7\uff0c\u5728\u4e32\u5904\u7406\u6307\u4ee4\u4e2d\u63a7\u5236\u4fe1\u606f\u7684\u65b9\u5411\u30020:\u6b63\u65b9\u5411\uff0c1\uff1a\u53cd\u65b9\u5411\u3002cld\uff0cstd\u3002#

    IF (Interrupt Flag) :\u4e2d\u65ad\u6807\u5fd7\u3002\u7981\u6b62\u4e2d\u65ad0\uff0c\u5141\u8bb8\u4e2d\u65ad1\u3002cli\uff0csti\u3002#

    AF (Auxiliary carry Flag) :\u8f85\u52a9\u8fdb\u4f4d\u6807\u5fd7\uff0c\u6709\u8fdb\u4f4d\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    ZF (Zero Flag) :\u96f6\u6807\u5fd7\uff0c\u8fd0\u7b97\u7ed3\u6784\u4e3a0\u65f6ZF\u4f4d\u4f4d\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    SF (Sign Flag):\u7b26\u53f7\u6807\u5fd7\uff0c\u7ed3\u679c\u4e3a\u8d1f\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002#

    CF (Carry Flag): \u8fdb\u4f4d\u6807\u5fd7\uff0c\u8fdb\u4f4d\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002\u914d\u5957\u7684clc\uff0cstc\u4e24\u6761\u8bbe\u7f6e\u6307\u4ee4\uff1a\u6e05\u9664\u548c\u7f6e1\u3002#

    PF (Parity Flag): \u5947\u5076\u6807\u5fd7\u3002\u7ed3\u679c\u64cd\u4f5c\u6570\u4e2d1\u7684\u4e2a\u6570\u4e3a\u5076\u6570\u65f6\u7f6e1\uff0c\u5426\u5219\u7f6e0\u3002

    TF\uff1a\u5355\u6b65\u8c03\u8bd5\u8981\u7528\u3002#

    EFLAGS\u662f\u5b9e\u73b0\u6761\u4ef6\u5224\u65ad\u548c\u903b\u8f91\u5224\u65ad\u7684\u4e00\u79cd\u673a\u5236\uff0c\u5728\u6c47\u7f16\u8bed\u8a00\u4e2d\u4e00\u822c\u4e0d\u76f4\u63a5\u8bbf\u95eeEFLAGS\u5bc4\u5b58\u5668\uff0c\u800c\u662f\u901a\u8fc7\u6307\u4ee4\u7684\u64cd\u4f5c\u9690\u542b\u8bbf\u95eeEFLAGS\u5bc4\u5b58\u5668\u3002

    cmp dword ptr [ebp+8], 0. // \u5f71\u54cd\u6807\u5fd7\u4f4dCF\uff0cZF\uff0cSF\uff0cOF\uff0cAF\u548cPF\nJz 99495898 //\u5982\u679cZF\u7b49\u4e8e1\uff0c\u5219\u8df3\u8f6c\u523000405898
    "},{"location":"docs/1-cs/assembly-x86/#_12","title":"\u6307\u4ee4","text":"

    \u603b\u7ed3

    \u6307\u4ee4 \u4f5c\u7528 \u53c2\u6570 \u6539\u53d8\u6807\u5fd7\u4f4d mov \u8d4b\u503c \u88ab\u8d4b\u503c\u5bc4\u5b58\u5668\uff0c\u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\uff0c\u503c\u3011 no xchg \u6570\u636e\u4ea4\u6362 \u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\u3011\uff0c\u3010\u5bc4\u5b58\u5668\uff0c\u5185\u5b58\u3011 no push \u8fdb\u6808 \u6e90\u64cd\u4f5c\u6570\u3010\u5bc4\u5b58\u5668\u3011 pop \u51fa\u6808 \u76ee\u7684\u64cd\u4f5c\u6570\u3010\u5bc4\u5b58\u5668\u3011 pushf \u6807\u5fd7\u4f4d\u8fdb\u6808 \u65e0 popf \u6807\u5fd7\u4f4d\u51fa\u6808 \u65e0 lea Load effect address\uff0c\u5bfb\u5740\uff0c\u53d6\u504f\u79fb\u5730\u5740 lds \u5f53\u6307\u4ee4\u6307\u5b9a\u7684\u662f16\u4f4d\u5bc4\u5b58\u5668\u65f6\uff0c\u628a\u6e90\u64cd\u4f5c\u6570\u5b58\u50a8\u5355\u5143\u4e2d\u5b58\u653e\u7684\u5341\u516d\u4f4d\u504f\u79fb\u5730\u5740\u53d6\u51fa\u5b58\u653e\u5728\u5bc4\u5b58\u5668\u4e2d\uff0c\u7136\u540e\u628a\u6e90\u64cd\u4f5c\u6570+2\u7684\u5341\u516d\u4f4d\u6570\u88c5\u5165\u6307\u4ee4\u6307\u5b9a\u7684\u6bb5\u5bc4\u5b58\u5668\u3002\u5f53\u6307\u4ee4\u6307\u5b9a\u7684\u662f32\u4f4d\u5bc4\u5b58\u5668\u65f6 \u628a\u6e90\u64cd\u4f5c\u6570\u5b58\u50a8\u5355\u5143\u4e2d\u5b58\u653e\u768432\u4f4d\u504f\u79fb\u5730\u5740\u88c5\u5165\u5bc4\u5b58\u5668 \u7136\u540e\u628a \u6e90\u64cd\u4f5c\u6570+4 \u768416\u4f4d\u6570\u88c5\u5165\u6bb5\u5bc4\u5b58\u5668\u3002mem\u6307\u5411\u7684\u5730\u5740,\u9ad8\u4f4d\u5b58\u653e\u5728DS\u4e2d,\u4f4e\u4f4d\u5b58\u653e\u5728reg\u4e2d. LDS reg,mem les \u628a\u5185\u5b58\u4e2d\u6307\u5b9a\u4f4d\u7f6e\u7684\u53cc\u5b57\u64cd\u4f5c\u6570\u7684\u4f4e\u4f4d\u5b57\u88c5\u5165\u6307\u4ee4\u4e2d\u6307\u5b9a\u7684\u5bc4\u5b58\u5668\u3001\u9ad8\u4f4d\u5b57\u88c5\u5165ES\u5bc4\u5b58\u5668\u3002 cbw 8\u4f4d\u6570\u6269\u5c55\u4e3a16\u4f4d\u6570\uff0c\u6709\u7b26\u53f7\u6269\u5145 no cwd \u5b57(16\u4f4d)\u6269\u5c55\u4e3a\u53cc\u5b57(32\u4f4d)\uff0c\u6709\u7b26\u53f7\uff1f no add \u52a0 OPRDS\uff0cOPRDD adc \u5e26\u8fdb\u4f4d\u52a0\uff08\u7ed3\u679c\u542b\u6807\u5fd7\u4f4dCF\u7684\u503c\uff0c=OPRDS\uff0bOPRDD\uff0bCF\uff09 OPRDS\uff0cOPRDD sub \u51cf OPRDD\uff0cOPRDS sbb \u5e26\u8fdb\u4f4d\u51cf\uff08\u7ed3\u679c\u542b\u6807\u5fd7\u4f4dCF\u7684\u503c\uff0c=OPRDD\uff0dOPRDS\uff0dCF\uff09 OPRDD\uff0cOPRDS inc \u81ea\u589e1 \u5bc4\u5b58\u5668 dec \u81ea\u51cf1 \u5bc4\u5b58\u5668 mul 32\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aEAX\uff0c\u90a3\u4e48\u4e58\u79ef\u5c06\u5b58\u653e\u5728EDX\uff1aEAX\u4e2d 32\u4f4d\u4e58\u6570 16\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aAX\u90a3\u4e48\u4e58\u79ef\u5c06\u653e\u5728DX\uff1aAX\u4e2di 16\u4f4d\u4e58\u6570 8\u4f4d\uff1a\u88ab\u4e58\u6570\u9ed8\u8ba4\u4e3aAL\uff0c\u90a3\u4e48\u4e58\u79ef\u5c06\u653e\u5728AX 8\u4f4d\u4e58\u6570 div 32\u4f4d\uff1a\u88ab\u9664\u6570\u5c06\u662fEDX\uff1aEAX\uff0c \u6700\u7ec8\u7684\u5546\u5c06\u5b58\u653e\u5728EAX\uff0c \u4f59\u6570\u5c06\u5b58\u653e\u5728EDX\u4e2d 32\u4f4d\u4e58\u6570 16\u4f4d\uff1a\u88ab\u9664\u6570\u4e3aEAX\uff0c\u6700\u7ec8\u5f97\u5230\u7684\u5546\u653e\u5728AX\uff0c\u4f59\u6570\u653e\u5728EAX\u7684\u9ad816\u4f4d 16\u4f4d\u4e58\u6570 8\u4f4d\uff1a\u88ab\u9664\u6570\u662f16\u4f4d\uff0c\u6700\u7ec8\u5f97\u5230\u7684\u5546\u5c06\u653e\u5728AL\u4e2d\uff0c\u4f59\u6570\u653e\u5728AH\u4e2d 8\u4f4d\u4e58\u6570 imul \u65e0\u7b26\u53f7\u4e58 idiv \u65e0\u7b26\u53f7\u9664 xlat \u6362\u7801\u6307\u4ee4\uff0c\u4ee5bx\u4e3a\u9996\u5730\u5740\u7684\uff0c\u504f\u79fb\u5730\u5740\u4e3aal\u7684\u5185\u5bb9\u9001\u7ed9al\u3002 in \u7aef\u53e3\u8bfb\u5199\u6307\u4ee4 IN AL,21H\uff1b\u8868\u793a\u4ece21H\u7aef\u53e3\u8bfb\u53d6\u4e00\u5b57\u8282\u6570\u636e\u5230AL out \u7aef\u53e3\u8bfb\u5199\u6307\u4ee4 and \u6309\u4f4d\u4e0e or \u6309\u4f4d\u6216 xor \u6309\u4f4d\u5f02\u6216 not \u64cd\u4f5c\u6570\u6309\u4f4d\u53d6\u53cd neg \u64cd\u4f5c\u6570\u6309\u4f4d\u53d6\u53cd\u52a0\u4e00 test \u5bf9\u4e24\u4e2a\u64cd\u4f5c\u6570\u8fdb\u884c\u6309\u4f4d\u4e0e\u64cd\u4f5c\u3002\u4e0eand\u4e0d\u540c\uff0c\u4e0d\u5f71\u54cd\u76ee\u6807\u64cd\u4f5c\u6570\u7684\u503c\u3002 shl \u903b\u8f91\u5de6\u79fb\uff0c\u5c06\u4e00\u4e2a\u5bc4\u5b58\u5668\u4e2d\u7684\u503c\u6216\u5355\u5143\u4e2d\u7684\u6570\u636e\u5411\u5de6\u79fb\u4f4d\uff0c\u5c06\u6700\u540e\u79fb\u51fa\u7684\u4e00\u4f4d\u5199\u5165cf\u4e2d\u3002\u6700\u4f4e\u4f4d\u75280\u8865\u5145\u3002 shr \u903b\u8f91\u53f3\u79fb\uff0c\u5c06\u4e00\u4e2a\u5bc4\u5b58\u5668\u4e2d\u7684\u503c\u6216\u5355\u5143\u4e2d\u7684\u6570\u636e\u5411\u5de6\u79fb\u4f4d\uff0c\u5c06\u6700\u540e\u79fb\u51fa\u7684\u4e00\u4f4d\u5199\u5165cf\u4e2d\u3002\u6700\u9ad8\u4f4d\u75280\u8865\u5145\u3002 sal \u7b97\u672f\u5de6\u79fb\uff0c\u4e0eshl\u4e00\u6837\uff0c\u88650 sar \u7b97\u672f\u53f3\u79fb\uff0c\u4e0eshr\u4e0d\u4e00\u6837\uff0c\u7b97\u672f\u53f3\u79fb\u8865\u6700\u9ad8\u4f4d rol \u5faa\u73af\u5de6\u79fb ror \u5faa\u73af\u53f3\u79fb rcl \u5e26\u8fdb\u4f4d\u5faa\u73af\u5de6\u79fb\uff0c\u5de6\u79fb\u7684\u65f6\u5019\u79fb\u51fa\u53bb\u7684\u4f1a\u653e\u5728cf\uff1f rcr \u5e26\u8fdb\u4f4d\u5faa\u73af\u53f3\u79fb cmp \u6bd4\u8f83 ja jump if above jb Jump if below jae Jump if above or equal jbe Jump if below or equal jg jump if greater\uff0c\u6709\u7b26\u53f7\u5927\u4e8e\u8df3\u8f6c jl jump less\uff0c\u6709\u7b26\u53f7\u5c0f\u4e8e\u8df3\u8f6c jge jump if greater or equal jle Jump if less or equal jc jump if with carry, CF = 1 jnc jump if not with carry, CF = 0 je = jz jump if equal, ZF = 1 jne = jnz jump if not equal, ZF = 0 jz jump if zero, ZF = 1 jnz jump if not zero, ZF = 0 jcxz jump if cx equals zero js SF = 1 jns SF = 0 jo Jump if overflow, OF = 1 jno jump if not overflow, OF = 0 loop \u5faa\u73af \u4ee3\u7801\u6bb5\uff08\uff1f\uff09\u540d clc clear carry flag\uff0c\u5c06cf\u4f4d\u6e05\u96f6 stc set carry flag\uff0cCF\u7f6e1 cli clear interrupt endable flag\uff0cIF\u6e05\u96f6\uff0c\u5173\u95ed\u4e2d\u65ad sti set interrupt endable flag\uff0cIF\u7f6e\u4f4d1\uff0c\u6253\u5f00\u4e2d\u65ad CMC complement carry flag\uff0cCF\u53d6\u53cd CLD clear direction flag\uff0cDF\u6e05\u96f6 STD set interrupt endable flag\uff0cDF\u7f6e1 call \u8fd1\u8c03\u7528 ret \u8fd1\u8fd4\u56de call far ptr \u8fdc\u8c03\u7528\u3002\u4e09\u4e2apush\u4e00\u4e2ajmp\u3002push f\uff0cpush cs\uff0cpush ip\uff0cjump retf \u8fdc\u8fd4\u56de\u3002\u4e09\u4e2apop\u3002\u6307\u4ee4\u2f64\u6808\u4e2d\u7684\u6570\u636e\uff0c\u4fee\u6539CS\u548cIP\u7684\u5185\u5bb9\uff0c\u4ece\u2f7d\u5b9e\u73b0\u8fdc\u8f6c\u79fb int \u4e2d\u65ad\u6307\u4ee4 iret \u4e2d\u65ad\u8fd4\u56de jmp short \u6bb5\u5185\u77ed\u8f6c\u79fb\uff0c\u77ed\u662f\u6307\u8981\u8df3\u2f84\u7684\u2f6c\u6807\u5730\u5740\u4e0e\u5f53\u524d\u5730\u5740\u524d\u540e\u76f8\u5dee\u4e0d\u8d85\u8fc7128\u5b57\u8282 jmp near ptr \u6bb5\u5185\u8fd1\u8f6c\u79fb\u3002\u8fd1\u662f\u6307\u8df3\u8f6c\u7684\u2f6c\u6807\u5730\u5740\u4e0e\u5f53\u524d\u5730\u5740\u5728\u2f64\u2f00\u4e2a\u6bb5\u5185\uff0c\u5373CS\u7684\u503c\u4e0d\u53d8\uff0c\u53ea\u6539\u53d8EIP\u7684\u503c jmp far ptr \u6bb5\u95f4\u8f6c\u79fb\uff0c\u8fdc\u6307\u8df3\u5230\u53e6\u2f00\u4e2a\u4ee3\u7801\u6bb5\u53bb\u6267\u2f8f\uff0cCS/EIP\u90fd\u8981\u6539\u53d8 Jmp dword ptr \u6bb5\u95f4\u8f6c\u79fb\uff0c\u4ee5\u5185\u5b58\u5730\u5740\u5355\u5143\u5904\u7684\u53cc\u5b57\u6765\u4fee\u6539\u6307\u4ee4\uff0c\u2fbc\u5730\u5740\u5185\u5bb9\u4fee\u6539CS\uff0c\u4f4e\u5730\u5740\u5185\u5bb9 \u4fee\u6539IP\uff0c\u5185\u5b58\u5730\u5740\u53ef\u4ee5\u4ee5\u4efb\u4f55\u5408\u6cd5\u7684\u2f45\u5f0f\u7ed9\u51fa repe/renpe scasb \u5b57\u7b26\u4e32\u626b\u63cf\u6307\u4ee4\u3002cmp al, es:[di] di++; \u5f53DF=1\u65f6\uff0c\u4e3adi-- repne:\u5f53ECX!=0\u5e76\u4e14ZF==0\u65f6 \u91cd\u590d repe: cx != 0\u4e14zf != 0\u91cd\u590d repe/renpe cmpsb \u5b57\u7b26\u4e32\u6bd4\u8f83\u6307\u4ee4\u3002\u2f50\u8f83byte ptr ds:[si]\u4e0ebyte ptr es:[di] \u5f53DF=0\u65f6\uff0cSI++\uff0cDI++ \u5f53DF=1\u65f6\uff0cSI--\uff0cDI-- repne:\u5f53ECX!=0\u5e76\u4e14ZF==0\u65f6 \u91cd\u590d repe: cx != 0\u4e14zf != 0\u91cd\u590d rep movsb \u5b57\u7b26\u4e32\u79fb\u52a8\u6307\u4ee4\u3002\u5176\u4e2drep\u8868\u793arepeat\uff0cs\u8868\u793astring\uff0cb\u8868\u793abyte \u5728\u6267\u2f8f\u6b64\u6307\u4ee4\u524d\u8981\u505a\u4ee5\u4e0b\u51c6\u5907\u2f2f\u4f5c\uff1a \u2460ds:si lodsb \u5757\u88c5\u5165\u6307\u4ee4\uff0c\u628aSI\u6307\u5411\u7684\u5b58\u50a8\u5355\u5143\u8bfb\u5165\u7d2f\u52a0\u5668\uff0clodsb\u5c31\u8bfb\u5165ax\uff0clodsw\u5c31\u8bfb\u5165ax\uff0c\u7136\u540esi\u81ea\u52a8\u589e\u52a0\u6216\u51cf\u5c0f1\u62162 stosb/stosw/stosd SI\u6307\u5411\u7684\ud83d\udd17,\u5176\u4e2dLODSB\u662f\u8bfb\u5165AL, LODSW\u662f\u8bfb\u5165AX\u4e2d, \u7136\u540eSI\u81ea\u52a8\u589e\u52a0\u6216\u51cf\u5c0f1\u62162\u4f4d.\u5f53\u65b9\u5411\u6807\u5fd7\u4f4dDF=0\u65f6\uff0c\u5219SI\u81ea\u52a8\u589e\u52a0\uff1bDF=1\u65f6\uff0cSI\u81ea\u52a8\u51cf\u5c0f\u3002 rep stosb lodsb"},{"location":"docs/1-cs/assembly-x86/#_13","title":"\u6570\u636e\u4f20\u9001\u6307\u4ee4","text":"

    \u6570\u636e\u4f20\u9001\u6307\u4ee4\u662f\u4e3a\u4e86\u5b9e\u73b0CPU\u548c\u5185\u5b58\uff0c\u8f93\u5165\u548c\u8f93\u51fa\u7aef\u53e3\u4e4b\u95f4\u7684\u6570\u636e\u4f20\u9001\u3002

    mov

    mov eax, 56 // \u5c0656H\u4f20\u9001\u5230eax\u5bc4\u5b58\u5668\nmov esi, dword ptr [eax * 2 + 1]  // \u5c06\u5185\u5b58\u5730\u5740\u4e3aeax*2+1\u76844\u5b57\u8282\u6570\u636e\u4f20\u9001\u5230esi\u5bc4\u5b58\u5668\nmov ah, byte ptr [esi * 2 + eax]  // \u5c06\u5185\u5b58\u5730\u5740\u4e3aesi*+eax\u5904\u76848\u4f4d\u6570\u636e\u4f20\u9001\u5230AH\u5bc4\u5b58\u5668\n

    xchg

    \u5bc4\u5b58\u5668\u548c\u5185\u5b58\u7684\u6570\u636e\u4ea4\u6362\uff0c\u4ea4\u6362\u7684\u6570\u636e\u53ef\u4ee5\u662f8\u5b57\u8282\u300116\u5b57\u8282\u621632\u5b57\u8282\uff0c\u5fc5\u987b\u683c\u5f0f\u76f8\u540c

    xchg eax, edx; // \u5c06edx\u5bc4\u5b58\u5668\u7684\u503c\u548ceax\u5bc4\u5b58\u5668\u7684\u503c\u4ea4\u6362\nxchg [esp-55], edi; // \u5c06edi\u5bc4\u5b58\u5668\u7684\u503c\u548c\u5806\u6808\u5730\u5740\u4e3a[esp-55]\u5904\u7684\u503c\u4ea4\u6362\n

    push pop

    push\u548cpop\uff1a\u79f0\u4e3a\u538b\u5165\u5806\u6808\u6307\u4ee4\u548c\u5f39\u51fa\u5806\u6808\u6307\u4ee4\uff0c\u683c\u5f0f\u662fpush src(\u6e90\u64cd\u4f5c\u6570)\u548cpop dst(\u76ee\u7684\u64cd\u4f5c\u6570)\uff0cpush\u6307\u4ee4\u548cpop\u6307\u4ee4\u9700\u8981\u5339\u914d\u51fa\u73b0\uff0c\u5426\u5219\u5806\u6808\u4f1a\u4e0d\u5e73\u8861\u3002push\u6307\u4ee4\u5c06\u539f\u64cd\u4f5c\u6570src\u538b\u5165\u5806\u6808\uff0c\u540c\u65f6esp-4\uff08\u6808\u9876\u6307\u9488\u51cf\u4e00\u4e2a4\u4f4d\uff09\uff0c\u800cpop\u53cd\u4e4b\uff0c\u4ece\u5806\u6808\u7684\u9876\u90e8\u5f39\u51fa4\u5b57\u8282\u7684\u6570\u503c\u7136\u540e\u653e\u5165dst\u3002\u572832\u4f4d\u7684\u64cd\u4f5c\u7cfb\u7edf\u4e0a\uff0cpush\u548cpop\u7684\u64cd\u4f5c\u662f\u4ee54\u5b57\u8282\u4e3a\u5355\u4f4d\u7684\uff0cpush\u548cpop\u6307\u4ee4\u5e38\u7528\u4e8e\u5411\u51fd\u6570\u4f20\u53c2\u3002

    push eax // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u4ee54\u5b57\u8282\u538b\u5165\u5806\u6808\uff0c\u540c\u65f6esp-4\npush dword ptr [12FF8589] // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230\u5185\u5b58\u5730\u5740\u4e3a12FF8589\u6240\u6307\u5730\u65b9\uff0c\u540c\u65f6esp+4\n-----------------------------------------------------------------------------\npop dword ptr [12FF8589] // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230\u5185\u5b58\u5730\u5740\u4e3a12FF8589\u6240\u6307\u7684\u5730\u65b9\uff0c\u540c\u65f6esp+4\npop eax // \u5c06\u5806\u6808\u9876\u90e8\u76844\u5b57\u8282\u5f39\u51fa\u5230eax\u5bc4\u5b58\u5668\uff0c\u540c\u65f6esp+4\n
    "},{"location":"docs/1-cs/assembly-x86/#_14","title":"\u5730\u5740\u4f20\u9001\u6307\u4ee4","text":"

    x86\u67093\u6761\u5730\u5740\u4f20\u9001\u6307\u4ee4\uff0c\u5206\u522b\u662fLEA\uff0cLDS\u548cLES\u3002\u5176\u5b9eLDS\u548cLES\u6307\u4ee4\u548c\u6bb5\u5bc4\u5b58\u5668\u6709\u5173\uff0c\u572832\u4f4d\u7684windows\u64cd\u4f5c\u7cfb\u7edf\u4e0a\uff0c\u4e00\u822c\u7684\u7a0b\u5e8f\u5458\u90fd\u4e0d\u9700\u8981\u7ba1\u7406\u6bb5\u5bc4\u5b58\u5668\uff0c\u6240\u4ee5\u76f8\u5bf9\u800c\u8a00\uff0cLDS\u548cLES\u5bc4\u5b58\u5668\u4f7f\u7528\u5f97\u6bd4\u8f83\u5c11\uff0c\u4e00\u822c\u60c5\u51b5\u4e0b\u5e38\u89c1\u7684\u53ea\u6709LEA\u6307\u4ee4\u3002

    LEA

    \u79f0\u4e3a\u5730\u5740\u4f20\u9001\u6307\u4ee4\uff0c\u683c\u5f0f\u662f\u201cLEA DST, ADDR\u201d\u3002LEA\u5c06ADDR\u5730\u5740\u52a0\u8f7d\u5230DST\uff0c\u5176\u4e2dADDR\u53ef\u4ee5\u662f\u5185\u5b58\uff0c\u4e5f\u53ef\u4ee5\u662f\u5bc4\u5b58\u5668\uff0c\u800cDST\u5fc5\u987b\u662f\u4e00\u4e2a\u901a\u7528\u5bc4\u5b58\u5668\u3002

    lea eax, [12345678]; // \u6307\u4ee4\u6267\u884c\u540eeax\u5bc4\u5b58\u5668\u7684\u503c\u4e3a12345678H\nmov eax, [12345678]; // \u800cmov eax, [12345678] \u6307\u4ee4\u6267\u884c\u540eeax\u5bc4\u5b58\u5668\u7684\u503c\u4e3a\u5185\u5b58\u5730\u574012345678\u6307\u5411\u7684\u90a3\u4e2a\u6570\u503c\n// LEA\u6307\u4ee4\u53ef\u7528\u4e8e\u7b97\u6cd5\u8fd0\u7b97\nlea ecx, [ecx + eax*4];  // ecx = ecx + eax * 4\n// \u76f8\u5f53\u4e8e\u8ba1\u7b97\u51faecx+eax*4\u7684\u6570\u503c\uff0c\u5728[]\u91cc\u662f\u4e00\u4e2a\u5730\u5740\uff0clea\u53d6\u5730\u5740\u540e\u5c31\u53d6\u5230\u4e86\u8fd9\u4e2a\u6570\u503c\n
    "},{"location":"docs/1-cs/assembly-x86/#_15","title":"\u7b97\u6570\u8fd0\u7b97\u6307\u4ee4","text":"

    80x86\u63d0\u4f9b\u4e868\u6761\u52a0\u51cf\u6cd5\u6307\u4ee4\uff0c4\u6761\u4e58\u9664\u6cd5\u6307\u4ee4\u3002

    ADD\uff1a\u52a0\u6cd5\u6307\u4ee4

    add eax, esi; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u52a0\u4e0aesi\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u7684\u5bc4\u5b58\u5668\u4e2d\nadd ebx, dword ptr[12345678] // \u5c06ebx\u5bc4\u5b58\u5668\u7684\u503c\u52a0\u4e0a\u5185\u5b58\u5730\u5740\u4e3a12345678\u6240\u5728\u76844\u5b57\u8282\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728ebx\u5bc4\u5b58\u5668\u4e2d\n// \u4e0d\u540c\u7684\u5e73\u53f0\u548c\u7f16\u8bd1\u5668\u4e2d\uff0cdword\u5360\u7528\u7684\u5b57\u8282\u6570\u4e0d\u540c\uff0c\u572832\u4f4d\u7684windows\u4e2d\u4e00\u4e2aword\u536016\u5b57\u8282\uff0cdword\u536032\u5b57\u8282\n// 64\u4f4d\u4e2d\u4e00\u4e2aword\u536032\u5b57\u8282\uff0cdword\u536064\u5b57\u8282\n

    sub \u51cf\u6cd5\u6307\u4ee4

    sub ecx, 4H; // \u5c06ecx\u5bc4\u5b58\u5668\u7684\u503c\u51cf\u53bb4H\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\nsub byte ptr[eax], ch; // \u5c06\u5185\u5b58\u5730\u5740\u4e3aeax\u6240\u6307\u5411\u7684\u6570\u636e\u7ed3\u6784\u6309\u5b57\u8282\u4e3a\u5355\u4f4d\u548cch\u5bc4\u5b58\u5668\u76f8\u51cf\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u6309\u5b57\u8282\u4e3a\u5355\u4f4d\u4fdd\u5b58\u5728eax\u6240\u6307\u5411\u7684\u4f4d\u7f6e\n

    inc\u52a01\u6307\u4ee4

    inc eax; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u52a01\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u653e\u5728\u539f\u6765\u7684\u5730\u65b9\n

    dec\u51cf1\u6307\u4ee4

    dec edx; // \u5c06dec\u5bc4\u5b58\u5668\u7684\u503c\u51cf1\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u653e\u5728\u539f\u6765\u7684\u5730\u65b9\n

    cmp\u6bd4\u8f83\u6307\u4ee4

    \u79f0\u6bd4\u8f83\u6307\u4ee4\u683c\u5f0f\u662f\u201dcmp oper1, oper2\u201d

    cmp\u6307\u4ee4\u5c06oper1\u51cf\u53bboper2\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4e0d\u4fdd\u5b58\uff0c\u53ea\u662f\u76f8\u5e94\u5730\u8bbe\u7f6e\u5bc4\u5b58\u5668eflags\u7684cf\uff0cpf\uff0czf\uff0caf\uff0csf\u548cof\u3002\u4e5f\u5c31\u662f\u8bf4\u53ef\u4ee5\u901a\u8fc7\u6d4b\u8bd5\u5bc4\u5b58\u5668eflags\u76f8\u5173\u7684\u6807\u5fd7\u503c\u5f97\u77e5cmp\u6267\u884c\u540e\u7684\u7ed3\u679c

    cmp eax, 56H; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u51cf\u53bb56H\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4e0d\u4fdd\u5b58\uff0c\u5e76\u4e14\u8bbe\u7f6e\u5bc4\u5b58\u5668eflags\u76f8\u5173\u7684\u6807\u5fd7\u4f4d\n

    neg

    neg\uff1a\u53d6\u8865\u6307\u4ee4\uff0c\u683c\u5f0f\u662fneg oper

    neg\u6307\u4ee4\u5c06oper\u64cd\u4f5c\u6570\u53d6\u53cd\uff0c\u7b80\u800c\u8a00\u4e4b\u5c31\u662f\u5c060\u51cf\u53bboper\u64cd\u4f5c\u6570\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5b58\u5728oper\u81ea\u8eab\u4e2d\u3002

    neg eax; \n

    mul imul

    \u65e0\u7b26\u53f7\u4e58\u6cd5\u6307\u4ee4\u548c\u6709\u7b26\u53f7\u4e58\u6cd5\u6307\u4ee4\u3002mul\u6307\u4ee4\u9690\u542b\u4e86\u4e00\u4e2a\u53c2\u52a0\u8fd0\u7b97\u7684\u64cd\u4f5c\u6570eax\u5bc4\u5b58\u5668\uff0c\u5c06eax\u5bc4\u5b58\u5668\u91cc\u7684\u503c\u4e58oper\uff0c\u7ed3\u679c\u4fdd\u5b58\u5728eax\u4e2d\u3002\u5982\u679c\u7ed3\u679c\u8d85\u8fc732\u4f4d\u5219\u9ad832\u4f4d\u4f7f\u7528edx\u5bc4\u5b58\u5668\u4fdd\u5b58\uff0ceax\u5bc4\u5b58\u5668\u4fdd\u5b58\u4f4e32\u4f4d\u3002

    mul edx; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u4e58\u4ee5edx\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\n

    div idiv

    \u9664\u6cd5\u6307\u4ee4\u548c\u6709\u7b26\u53f7\u9664\u6cd5\u6307\u4ee4\u3002

    div ecx; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u63094\u5b57\u8282\u4e3a\u5355\u4f4d\u9664\u4ee5ecx\u5bc4\u5b58\u5668\u7684\u503c\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5546\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\uff0c\u4f59\u6570\u4fdd\u5b58\u5728edx\u5bc4\u5b58\u5668\u4e2d\u3002\ndiv word ptr [esp+36]; // \u5c06eax\u5bc4\u5b58\u5668\u7684\u503c\u6309word\u4e3a\u5355\u4f4d\u9664\u4ee5\u5806\u6808\u5730\u5740\u4e3aesp+36\u6240\u6307\u5411\u7684\u6570\u636e\uff0c\u5f97\u51fa\u7684\u7ed3\u679c\u5546\u4fdd\u5b58\u5728eax\u5bc4\u5b58\u5668\u4e2d\uff0c\u4f59\u6570\u4fdd\u5b58\u5728edx\u5bc4\u5b58\u5668\u4e2d\u3002\n
    "},{"location":"docs/1-cs/assembly-x86/#80386","title":"\u9ad8\u7ea7\u8bed\u8a00\u4e2d\u7684\u6570\u636e\u7ed3\u6784\u4e0e80386\u95f4\u63a5\u5bfb\u5740","text":"

    BX BP SI DI

    BX\uff1a

    BP\uff1a

    SI\uff1a

    DI\uff1a

    \u95f4\u63a5\u5bfb\u5740\uff1abx\uff0cbp\uff0csi\uff0cdi\uff0c\u53ef\u4ee5\u653e\u5728\u65b9\u62ec\u53f7\u5185

    \u7f3a\u7701\u6bb5\u5740\uff1ads\u548css\uff0c\u5982\u679c\u65b9\u62ec\u53f7\u5185\u6709bp\uff0c\u4e00\u5b9a\u662fss\uff0cbx\u4e00\u5b9a\u662fds

    CS (code segment): \u4ee3\u7801\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u4ee3\u7801\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    DS (data segment)\uff1a\u6570\u636e\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u6570\u636e\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    SS (stack segment)\uff1a\u5806\u6808\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u50a8\u5806\u6808\u6bb5\u7684\u6bb5\u5730\u5740\u3002

    ES (extra segment)\uff1a\u9644\u52a0\u6570\u636e\u6bb5\u5bc4\u5b58\u5668\uff0c\u7528\u6765\u5b58\u653e\u9644\u52a0\u6bb5\u7684\u6bb5\u5730\u5740\u3002\u6709\u65f6\uff0c\u4e00\u4e2a\u6570\u636e\u6bb5\u4e0d\u591f\u7528\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u58f0\u660e\u4e00\u4e2a\u9644\u52a0\u6bb5\u6765\u5b58\u653e\u66f4\u591a\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u58f0\u660e 2 \u4e2a\u6570\u636e\u6bb5\uff0c\u5206\u522b\u7528 DS \u548c ES \u6307\u5411\u3002

    \u7a0b\u5e8f\u5f00\u59cb\u8fd0\u884c\u65f6\uff0cDOS \u4f1a\u628a ds \u548c es \u8d4b\u503c\u4e3a psp(program segment prefix) \u6bb5\u5730\u5740\u3002psp \u6bb5\u4f4d\u4e8e\u7a0b\u5e8f\u9996\u4e2a\u6bb5\u7684\u524d\u9762\uff0c\u957f\u5ea6\u4e3a 100h \u5b57\u8282\uff0c\u5176\u7528\u9014\u662f\u4fdd\u5b58\u5f53\u524d exe \u76f8\u5173\u7684\u4e00\u4e9b\u4fe1\u606f\uff0c\u5982 psp:80h \u5f00\u59cb\u5b58\u653e\u4e86 exe \u7684\u547d\u4ee4\u884c\u53c2\u6570\u3002

    \u95f4\u63a5\u5bfb\u5740\uff1a \u53ef\u4ee5\u2f64\u4f5c\u95f4\u63a5\u5bfb\u5740\u7684\u5bc4\u5b58\u5668\u53ea\u6709\u56db\u4e2a\uff1abx, bp, si, di [bx], [bp], [si], [di]\u662f\u6700\u7b80\u5355\u7684\u95f4\u63a5\u5bfb\u5740 [bx + si], [bp + si], [bx + di], [bp + di]\u6ce8\u610f\u524d\u2faf\u5fc5\u987b\u662fbx/bp\uff0c\u540e\u2faf\u5fc5\u987b\u662fdi/si [bx+2] [bp-2] [si+1] [di-1] [bx+si+2] [bx+di-2]

    [bp+si+1] [bp+di-1] tips\uff1a\u4e24\u4e2a\u5bc4\u5b58\u5668\u76f8\u52a0\u7684\u95f4\u63a5\u5bfb\u5740\u2f45\u5f0f\u4e2d, bx\u6216bp\u901a\u5e38\u2f64\u6765\u8868\u793a\u6570\u7ec4\u7684\u2fb8\u5730\u5740, \u2f7dsi\u6216di\u5219\u2f64\u6765\u8868\u793a\u4e0b \u6807\u3002

    \u7f3a\u7701\u6bb5\u5740\uff1a\u4e0d\u542bbp\u7684\u6e90\u64cd\u4f5c\u6570\u2f00\u822c\u90fd\u7701\u7565\u7684\u6bb5\u5730\u5740ds\uff0c\u542b\u6709bp\u7684\u6e90\u64cd\u4f5c\u6570\u7701\u7565\u4e86ss\uff0c\u2f7d\u8fd9\u4e2a\u9ed8\u8ba4\u7684\u6bb5\u5730\u5740\u662f \u53ef\u4ee5\u88ab\u6539\u53d8\u7684

    \u7528\u5806\u6808\u4f20\u9012\u53c2\u6570\u65f6\uff0c\u5982\u4f55\u7528[bp+]\u5b9e\u73b0\u5bf9\u53c2\u6570\u7684\u5f15\u7528\uff1f

    bp + \u591a\u5c11\u5c31\u662f\u6808\u91cc\u7684\u591a\u5c11

    \u738b\u723d\u300a\u6c47\u7f16\u8bed\u2f94\u300b\u7b2c\u56db\u7248 \u9644\u5f554:\u2f64\u6808\u4f20\u9012\u53c2\u6570

    difcube:\n    mov bp, sp\n    mov ax, [bp+4]  ;a\u7684\u503c\u9001\u5165ax\u4e2d\n    sub ax, [bp+6]  ;\u51cf\u6808\u4e2db\u7684\u503c\n    mov bp, ax\n    mul bp\n    mul bp\n    pop bp\n    ret 4\n
    "},{"location":"docs/1-cs/assembly-x86/#_16","title":"\u5176\u5b83\u7684\u7b14\u8bb0","text":""},{"location":"docs/1-cs/assembly-x86/#x86_1","title":"x86\uff1a","text":"

    Intel\u4ece16\u4f4d\u5fae\u5904\u7406\u56688086\u5f00\u59cb\u7684\u6574\u4e2aCPU\u82af\u7247\u7cfb\u5217\uff0c\u7cfb\u5217\u4e2d\u7684\u6bcf\u79cd\u578b\u53f7\u90fd\u4fdd\u6301\u4e0e\u4ee5\u524d\u7684\u5404\u79cd\u578b\u53f7\u517c\u5bb9\uff0c\u4e3b\u8981\u67098086\uff0c8088\uff0816\u4f4dCPU\uff09\uff0c80186\uff0c80286\uff08\u8fd9\u4e24\u4e2a\u662f\u8fc7\u6e21\u4ea7\u54c1\uff09\uff0c 80386\uff0c80486\u4ee5\u53ca\u4ee5\u540e\u5404\u79cd\u578b\u53f7\u7684Pentium\u82af\u7247\uff0832\u4f4dCPU\uff09\uff0c\u901a\u5e38\u6240\u8bf4\u7684x86\u90fd\u662f\u630732\u4f4dCPU

    80386: 32\u4f4d\u6c47\u7f16\u3002

    80836\u5bc4\u5b58\u5668

    \u901a\u7528\u5bc4\u5b58\u5668(EAX EBX ECX EDX,ESP,EBP,ESI,EDI)

    \u901a\u7528\u5bc4\u5b58\u5668\u4e0e8086\u7684\u5bc4\u5b58\u5668\u76f8\u6bd4,\u753116\u4f4d\u53d8\u4e3a\u4e8632\u4f4d

    ESP:\u6808\u9876

    EBP:\u6808\u5e95

    EAX\uff0cEBX\uff0cECX\uff0cEDX\u901a\u7528\u5bc4\u5b58\u5668

    EAX\uff1a\u7d2f\u52a0\u5668\uff08\u4e58\u6cd5\u7684\u65f6\u5019\u5b58\u4f4e\u4f4d\uff09

    EBX\uff1a\u57fa\u5740\uff08\uff3bEBX\uff0b100\uff28\uff3d\uff09

    ECX\uff1a\u8ba1\u6570\uff08\u5faa\u73af\u7684\u65f6\u5019\u8ba1\u6570\uff09

    EDX\uff1a\u6570\u636e\uff08\u9ed8\u8ba4EDX\uff0a10H\uff0b\uff0e\uff0e\uff0e\uff1b\u4e58\u6cd5\u7684\u65f6\u5019\u5b58\u9ad8\u4f4d\uff09

    ESI\uff0cEDI\uff1a\u53d8\u5740\u5bc4\u5b58\u5668

    ESI\uff1a\u6e90\u53d8\u5740\u5bc4\u5b58\u5668

    EDI\uff1a\u76ee\u7684\u53d8\u5740\u5bc4\u5b58\u5668\u3000\u4e0eEBX\u57fa\u5740\u642d\u914d\u4f7f\u7528

    "},{"location":"docs/1-cs/assembly-x86/#_17","title":"\u53c2\u8003\u6587\u732e","text":"

    asm_sum.doc

    xxjj\u7684\u300a\u6c47\u7f16\u8bed\u8a00\u8003\u8bd5\u603b\u7ed3\u300b https://www.yuque.com/xianyuxuan/coding/mkte6u

    [80386]80x86\u6c47\u7f16\u6307\u4ee4_CarlosX\u7684\u535a\u5ba2-CSDN\u535a\u5ba2_80386\u6307\u4ee4\u96c6

    80386 \u7b97\u672f\u8fd0\u7b97\u6307\u4ee4\uff0c\u903b\u8f91\u8fd0\u7b97\u6307\u4ee4\uff0c\u79fb\u4f4d\u6307\u4ee4 (\u4e09) _ttzyanswer\u7684\u535a\u5ba2-CSDN\u535a\u5ba2

    "},{"location":"docs/1-cs/c-libgraphics/","title":"C\u5927\u7a0b libgraphics \u6587\u6863 \u4f7f\u7528\u8bb0\u5f55","text":"

    :material-circle-edit-outline: \u7ea6 562 \u4e2a\u5b57 :fontawesome-solid-code: 162 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    \u26a0\ufe0f \u6ca1\u5199\u5b8c TODO

    "},{"location":"docs/1-cs/c-libgraphics/#_1","title":"\u5df2\u77e5\u95ee\u9898","text":""},{"location":"docs/1-cs/c-libgraphics/#devc","title":"DevC++\u56fe\u5f62\u7f16\u7a0b\u8fc7\u7a0b","text":""},{"location":"docs/1-cs/c-libgraphics/#_2","title":"\u51fd\u6570\u5e93","text":"

    graphics.h \u4ec5\u63d0\u4f9b\u4ee5\u4e0b\u5c11\u91cf\u753b\u56fe\u51fd\u6570\u63a5\u53e3

    InitGraphics();\nMovePen(x, y);\nDrawLine(dx, dy);\nDrawArc(r, start, sweep);\nGetWindowWidth();\nGetWindowHeight();\nGetCurrentX();\nGetCurrentY();\n

    \u6211\u4eec\u5c06\u5728\u4e0b\u9762\u4ecb\u7ecd\u8fd9\u4e9b\u63a5\u53e3\u7684\u7528\u6cd5\u3002

    "},{"location":"docs/1-cs/c-libgraphics/#_3","title":"\u521d\u59cb\u5316\u64cd\u4f5c","text":"

    \u5728main.c\u91cc\u9700\u8981\u8fdb\u884c\u5982\u4e0b\u521d\u59cb\u5316

    #include \"graphics.h\"\n#include \"extragraph.h\"\n#include \"imgui.h\"\nvoid Main()        // \u6ce8\u610f\u8fd9\u91cc\u9700\u8981\u4f7f\u7528\u5927\u5199Main\n{\nSet WindowTitle(\"Your Title\");\nInitGraphics();  // \u8c03\u7528\u4e86\u56fe\u5f62\u6a21\u5f0f\n}\n

    InitGraphics(); \u8fd9\u4e2a\u51fd\u6570\u4f1a\u6253\u5f00\u4e00\u4e2a\u7a7a\u7684\u56fe\u5f62\u7a97\u53e3\u3002

    "},{"location":"docs/1-cs/c-libgraphics/#_4","title":"\u7a97\u53e3","text":"

    \u4ee5\u4e0b\u56db\u4e2a\u51fd\u6570\u90fd\u4e0d\u9700\u8981\u4f20\u5165\u53c2\u6570\uff0c\u5206\u522b\u8fd4\u56de\u7a97\u53e3\u5bbd\u3001\u9ad8\uff0c\u5f53\u524dX\u3001Y\u5750\u6807\u3002

    GetWindowWidth();\nGetWindowHeight();\nGetCurrentX();\nGetCurrentY();\n
    "},{"location":"docs/1-cs/c-libgraphics/#_5","title":"\u597d\u7684\u7f16\u5199\u4e60\u60ef","text":"

    \u5e94\u8be5\u5148\u5b9a\u4e49\u4e00\u4e9b\u5e38\u91cf\uff0c\u7ed9\u8fd9\u4e9b\u5e38\u91cf\u53d6\u540d\u5b57

    #define HouseHeight 2.0\n#define HouseWidth 3.0\n#define AtticHeight 0.7\n#define DoorWidth 0.4\n#define DoorKnobRadius 0.03\n#define DoorKnobInset 0.07\n#define PaneHeight 0.25\n#define PaneWidth 0.2\n#define FirstFloorWindows 0.3\n#define SecondFloorWindows 1.25\n
    "},{"location":"docs/1-cs/c-libgraphics/#_6","title":"\u753b\u56fe\u5f62\u7684","text":""},{"location":"docs/1-cs/c-libgraphics/#movepen","title":"MovePen","text":"

    \u5c06\u7b14\u79fb\u52a8\u5230(x, y)\u8be5\u5750\u6807\u3002\u6ce8\u610f\u5f53\u753b\u56fe\u5f62\u65f6\uff0c\u540e\u9762\u51e0\u4e2a\u51fd\u6570\u7684\u76f8\u5bf9\u4f4d\u79fb\uff0c\u90fd\u662f\u76f8\u5bf9\u4e8e\u8fd9\u4e2a\u51fd\u6570\u8bbe\u7f6e\u7684\u7b14\u5750\u6807\u79fb\u52a8\u7684\u3002

    MovePen(double x, double y);\n
    "},{"location":"docs/1-cs/c-libgraphics/#drawline","title":"DrawLine","text":"

    \u5728\u753b\u7ebf\u4e4b\u524d\u4e00\u5b9a\u8981MovePen();

    DrawLine(double dx, double dy);\n

    \u753b\u7ebf\u7684\u65b9\u5411\uff1a

    \u6a2a\u5750\u6807\u6700\u5de6\u8fb9\u662f0\uff0c\u5411\u53f3\u589e\u5927

    \u7eb5\u5750\u6807\u6700\u4e0b\u9762\u662f0\uff0c\u5411\u4e0a\u589e\u5927

    \u53ef\u4ee5\u7406\u89e3\u4e3a\u6211\u4eec\u5728\u7b2c\u4e00\u8c61\u9650

    "},{"location":"docs/1-cs/c-libgraphics/#drawarc","title":"DrawArc","text":"

    \u5728\u753b\u5f27\u4e4b\u524d\u4e00\u5b9a\u8981MovePen();

    DrawArc(double r, double start, double sweep);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_7","title":"\u6211\u4eec\u5e94\u5f53\u628a\u753b\u77e9\u5f62\u5c01\u88c5\u6210\u4e00\u4e2a\u65b0\u7684\u51fd\u6570","text":"
    void DrawBox (double x, double y, double width, double height)\n{\nMovePen(x, y);\nDrawLine(0, height);\nDrawLine(width, 0);\nDrawLine(0, height);\nDrawLine(-width, 0);\n}\n
    void DrawCenteredBox(double x, double y, double width, double height)\n{\nDrawBox(w - width/2, y - height/2, width, height);\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_8","title":"\u753b\u5706\u7684\u51fd\u6570","text":"
    void DrawCenteredCircle(double x, double y, double r)\n{\nMovePen(x + r, y);\nDrawArc(r, 0, 360);\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_9","title":"\u6587\u5b57","text":"

    \u4ece\u5f53\u524d\u4f4d\u7f6e\u5f00\u59cb\u8f93\u51fa\u6587\u672c\u4e32

    DrawTextString(string);\n

    \u8fd9\u4e2a\u51fd\u6570\u7528\u4e8e\u83b7\u53d6\u67d0\u4e2a\u5b57\u7b26\u4e32\u957f\u5ea6

    double stringLen = TextStringWidth(string);
    "},{"location":"docs/1-cs/c-libgraphics/#_10","title":"\u67e5\u770b\u56de\u8c03\u51fd\u6570\u7c7b\u578b","text":"
    typedef void(* KeyboardEventCallback)(int key, int event);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_11","title":"\u5b9a\u65f6\u5668","text":""},{"location":"docs/1-cs/c-libgraphics/#_12","title":"\u65f6\u95f4\u56de\u8c03\u51fd\u6570","text":"
    registerTimerEvent(mytimer);  //\u83b7\u53d6\u7535\u8111\u65f6\u949f\u4fe1\u606f\u8fd4\u56de\u7ed9mytimer\nstartTimer(0, (int)(1000/speed));  // \u8981\u8ba8\u8bba\u4f20\u8fdb\u6765\u7684timer\u662f\u4ec0\u4e48\n
    "},{"location":"docs/1-cs/c-libgraphics/#_13","title":"\u5b9a\u65f6\u5668\u6d88\u606f\u56de\u8c03\u51fd\u6570","text":"
    void TimerEventProcess(int timerID);\n

    \u793a\u4f8b

    typedef enum\n{\nLabelTimer,\nBoxTimer,\n} MyTimer;\n
    void mytimer(int  timerID)\n{\nswitch (timerID)\n{\ncase LabelTimer:\nlabel_x += 0.5;\nif (label_x > 5.0) label_x = 1.0;\ndisplay();\nbreak;\ncase BoxTimer:\nbox_y += 0.5;\nif (box_y > 5.0) box_y = 1.0;\ndisplay();\nbreak;\nbreak;\n}\n}\n
    registerTimerEvent(mytimer);\nstartTimer(LabelTimer, 100);\nstartTimer(BoxTimer, 200);\n
    "},{"location":"docs/1-cs/c-libgraphics/#_14","title":"\u9f20\u6807","text":""},{"location":"docs/1-cs/c-libgraphics/#_15","title":"\u9f20\u6807\u6d88\u606f\u56de\u8c03\u51fd\u6570","text":"
    void MouseEventProcess(int x, int y, int button, int event);\n

    x, y - \u4f4d\u7f6e\u5750\u6807

    button - \u6309\u4e0b\u7684\u662f\u54ea\u4e2a\u952e

    event - \u6309\u4e0b\uff0c\u677e\u5f00\uff0c\u79fb\u52a8\u7b49\u4e8b\u4ef6

    void myMouseEvent (int x, int y, int button, int event)\n{\nmouse_x = ScaleXInches(x);   // \u8fd9\u4e2a\u51fd\u6570\u5728extragraph\u5e93\u91cc\nmouse_y = ScaleYInches(y);\ndisplay();\n}\n

    \u9700\u8981\u5728Main()\u91cc\u6dfb\u52a0\u8fd9\u4e00\u884c

    registerMouseEvent(myMouseEvent);\n

    \u5728display()\u91cc

    void display()\n{\ndouble w = 1.0;\ndouble h = GetFontHeight() * 2;\n// \u6e05\u9664\u5c4f\u5e55\nDisplayClear();\n// draw a square\nSetPenColor(\"Red\");\ndrawLabel(label_x, label_y, \"Lable is Here\");\n//draw a rect/box to trace the mouse\n//drawRectangle(mouse_x, mouse_y, w, h, 0);\nSetPenColor(\"Blue\");\ndrawBox(mouse_x, mouse_y, w, h, 1, \"This box follows the mouse\", 'L', \"Red\");\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#linkedlist","title":"\u4f7f\u7528linkedlist\u5e93","text":"
    #include \"linkedlist.h\"\n

    \u521b\u5efa\u4e00\u4e2a linkedlist \u540d\u53eb g_polylines

    linkedlistADT g_polylines = NULL;\ng_polylines = NewLinkedList();\ndisplay();\n
    void display()\n{\nlinkedlistADT poly = NextNode(g_polylines, g_polylines);\nSetPenColor(\"Blue\");\nif (poly) {\nPoint * p = (Point*) NodeObj(g_polylines, poly);\ndouble lx = p->x;\ndouble ly = p->y;\nMovePen(lx, ly);\nwhile (poly = NextNode(g_polylines, poly))\n{\np = (Point*) NodeObj(g_polylines, poly);\nDrawLine(p->x - lx, p->y - ly);\nlx = p->x;\nly = p->y;\n}\n}\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#button","title":"\u4f7f\u7528button\u548c\u952e\u76d8","text":"

    \u8fd9\u6b21\u9700\u8981\u7528\u5230\u7684\u5e93

    #include <windows.h>\n#include <winuser.h>\n#include \"graphics.h\"\n#include \"extgraph.h\"\n#include \"imgui.h\"\n#include \"linkedlist.h\"\n
    "},{"location":"docs/1-cs/c-libgraphics/#_16","title":"\u5b57\u7b26\u8f93\u5165\u56de\u8c03\u51fd\u6570","text":"
    void charEventProcess(char c);\n

    c - \u8f93\u5165\u5b57\u7b26\u7684ASCII\u7801

    "},{"location":"docs/1-cs/c-libgraphics/#_17","title":"\u952e\u76d8\u56de\u8c03\u51fd\u6570","text":"
    void KeyboardEventProcess(int key, int event);\n

    key - \u54ea\u4e2a\u952e

    event - \u6309\u4e0b\u8fd8\u662f\u677e\u5f00

    \u793a\u4f8b

    \u5728Main()\u4e2d

    \n
    void myKeyboardEvent(int key, int event)\n{\nuiGetKeyboard(key, event); // needed for using simpleGUI\ndisplay();\nswitch (event)\n{\ncase KEY_UP:\nif (key == VK_F1)\ng_add_point = !g_add_point;\nbreak;\ndefault:\nbreak;\n}\n}\n
    "},{"location":"docs/1-cs/c-libgraphics/#_18","title":"\u989c\u8272\u5e93","text":"

    \u81ea\u5e26\u7684\u989c\u8272\u5217\u8868

    char colorlist[100][100] = {\u201dBlack\u201d, \u201cDark Gray\u201d, \u201cGray\u201d, \u201cLight Gary\u201d, \u201cWhite\u201d, \u201cBrown\u201d, \u201cRed\u201d, \u201cOrange\u201d, \u201cYellow\u201d, \u201cGreen\u201d, \u201cBlue\u201d, \u201cViolet\u201d, \u201cMagenta\u201d, \u201cCyan\u201d};\nconst int colorNumber = 14;\n

    \u81ea\u5b9a\u4e49\u989c\u8272

    \u989c\u8272\u4f1a\u88ab\u52a0\u5165\u989c\u8272\u5e93\uff0cRGB\u7684\u53d6\u503c\u8303\u56f4\u90fd\u662f[0, 1]\u800c\u4e0d\u662f[0, 256)

    DefineColor(\"Color Name\", R, G, B);\n
    "},{"location":"docs/1-cs/c-libgraphics/#libgraphics","title":"libgraphics\u5176\u5b83\u5e38\u7528\u7684\u4e1c\u897f","text":""},{"location":"docs/1-cs/code-style/","title":"Pythons' Code Style Guide","text":"

    :material-circle-edit-outline: \u7ea6 517 \u4e2a\u5b57 :fontawesome-solid-code: 71 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/1-cs/code-style/#pr","title":"PR","text":""},{"location":"docs/1-cs/code-style/#first-prototypes-and-implementations-then","title":"First prototypes, and implementations then","text":""},{"location":"docs/1-cs/code-style/#every-pr-should-be-meaningful-an-integral-element","title":"Every PR should be meaningful (an integral element)","text":""},{"location":"docs/1-cs/code-style/#split-to-the-smallest-elements","title":"Split to the smallest elements","text":"

    \u2705 each PR can be described within one sentence.

    "},{"location":"docs/1-cs/code-style/#git-add-instead-of-git-add","title":"git add , instead of git add .","text":""},{"location":"docs/1-cs/code-style/#require-review-before-each-merging-by-setting-up-protecting-your-branch","title":"require review before each merging, by setting up \u2018protecting your branch\u2019","text":""},{"location":"docs/1-cs/code-style/#prs-title-same-as-git-commit-message","title":"PRs title - same as git commit message

    format [label] name + summary of change

    admitted labels: Git Commit Style Guide

    ","text":""},{"location":"docs/1-cs/code-style/#pr-message-same-as-git-commit-message","title":"PR message - same as git commit message","text":""},{"location":"docs/1-cs/code-style/#file-management","title":"File management","text":""},{"location":"docs/1-cs/code-style/#oop","title":"oop

    Encompass each function (except main) into a related class.

    ","text":""},{"location":"docs/1-cs/code-style/#write-prototypes-first","title":"write prototypes first","text":""},{"location":"docs/1-cs/code-style/#avoid-using-hyphen-or-underscore-in-file-naming-make-files-into-folders-instead","title":"avoid using hyphen or underscore in file naming, make files into folders instead.

    \u2705 Do models/models.py

    \u274c Don't models_main.py

    ","text":""},{"location":"docs/1-cs/code-style/#naming","title":"Naming","text":""},{"location":"docs/1-cs/code-style/#avoid-abbreviations-and-use-full-spellings","title":"avoid abbreviations and use full spellings

    \u2705 Do path_checkpoint.

    \u274c Don't path_ckpt.

    ","text":""},{"location":"docs/1-cs/code-style/#my-own-habit","title":"(my own habit:) ","text":""},{"location":"docs/1-cs/code-style/#classs-private-members-should-start-with-an-underscore-_-to-separate-with-the-input-parameters","title":"Class's private members should start with an underscore _ to separate with the input parameters.

    e.g., the correct private number name should be

    def __init__(self, foo):\n    self._foo = foo     # not recommended\n

    instead of 

    def __init__(self, foo):\n    self.foo = foo      # recommended\n

    And whenever an outer function requires a private member of a class, it is not recommended to directly use the private member from the class like

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\nfoo = Foo()\nfoo._bar                # not recommnded\n

    nor

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\n    @property\n    def get_bar(self):\n        return self._bar\n\nfoo = Foo()\nfoo.get_bar()\n

    instead, using a @property decorator is recommonded.

    class Foo:\n    def __init__(self, bar):\n        self._bar = bar\n\n    @property\n    def bar(self):\n        return self._bar\n\nfoo = Foo()\nfoo.bar\n
    ","text":""},{"location":"docs/1-cs/code-style/#spacing","title":"Spacing","text":"

    From top to down - In every comment: 1 space-line between each section, i.e., - Except the file top, no more than 2 space-line

    "},{"location":"docs/1-cs/code-style/#type-hints","title":"Type Hints","text":""},{"location":"docs/1-cs/code-style/#write-type-hints-no-need-to-write-types-in-the-comment","title":"write type hints, no need to write types in the comment

    \u2705 Do

    def foo(bar: int) -> str:\n    \"\"\"\n    Args:\n        bar: \n    Returns:\n        str: \n    \"\"\"\n    pass\n

    \u274c Don't

    def foo(bar: int) -> str:\n    \"\"\"\n    Args:\n        bar (int): \n    Returns:\n        str (str): \n    \"\"\"\n    pass\n
    ","text":""},{"location":"docs/1-cs/code-style/#try-to-use-the-typing-library","title":"try to use the typing library.

    Usual usage: when you want to indicat the element type of a Dict / a List / etc.

    from typing import Dict\n\ntyping.Dict[str, Union[int, float]]\n

    Supported types: - Dict[x, y] - Union[x, y, ...] -

    After Python 3.10, this feature is included as an internal feature, with all types written as lower cases.

    dict[str, int | float]\n

    But to preserve the extenability to lower versions, I believe the importing method would be better.

    ","text":""},{"location":"docs/1-cs/code-style/#comments","title":"Comments","text":""},{"location":"docs/1-cs/code-style/#where-should-comments-appear","title":"Where should comments appear? ","text":""},{"location":"docs/1-cs/code-style/#formats","title":"Formats ","text":""},{"location":"docs/1-cs/code-style/#file-docstring","title":"file docstring

    No space between the docstring and the imports.

    ","text":""},{"location":"docs/1-cs/code-style/#be-sure-to-make-every-doc-a-sentence","title":"Be sure to make every doc a sentence

    \u2705 Do # a comment.

    \u274c Don't # a comment..

    ","text":""},{"location":"docs/1-cs/code-style/#can-omit-the-but-keep-congruent","title":"Can omit 'the' but keep congruent

    \u2705 Do 

    # comment 1.\n# comment 2.\n# comment 3.\n

    \u274c Don't

    # comment 1.\n# the comment 2.\n# comment 3.\n
    ","text":""},{"location":"docs/1-cs/code-style/#imports","title":"Imports","text":""},{"location":"docs/1-cs/code-style/#order","title":"Order
    1. import all Python default libs, in alphabetical order (of the package name instead of the folder name), and add an empty line.
    2. import all 3rd party libs in alphabetical order, and add an empty line.
    3. import all libs defined in this project.

    One way to automatically sort the imports in VSCode (Don't sing an alphabet song every time you add an import): 1. Open the setting.json. 2. Add or change the following setting

    ```json\n\"editor.codeActionsOnSave\": {\n    \"source.organizeImports\": true,\n},\n```\n
    ","text":""},{"location":"docs/1-cs/code-style/#importing-names","title":"Importing Names

    \u2705 Do use import x, x.y to avoid the conflict of namespace, e.g.,

    import torch\nimport transformers\n\ntorch.nn.Module\ntransformers.Trainer\n

    \u274c Don't use from x import y.

    The only examptions are those well-established ones, e.g., from typing import Dict, List, Optional, Sequence, Union.

    ","text":""},{"location":"docs/1-cs/code-style/#references","title":"References","text":"

    This code style guide is an examplanation of the Google's Python Style Guide.

    "},{"location":"docs/1-cs/architecture/","title":"\u7d22\u5f15","text":"

    :material-circle-edit-outline: \u7ea6 318 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u6253\u7b97\u7a0d\u5fae\u5199\u4e00\u70b9\u662f\u56e0\u4e3a\u81ea\u5df1\u5b66\u4f53\u7cfb\u7684\u65f6\u5019\u6ca1\u627e\u5230\u7279\u522b\u5b8c\u6574\u7b14\u8bb0\u8d44\u6599 + \u6ca1\u4e0a\u8ba1\u7ec4\uff0c\u81ea\u5df1\u5b8c\u5168\u6ca1\u7406\u89e3\uff0c\u5355\u7eaf\u786c\u80cc\u901f\u6210\u7684\uff0c\u8bb0\u4e00\u4e0b\u81ea\u5df1\u901f\u6210\u770b\u4e86\u54ea\u4e9b\u4e1c\u897f

    \u5f53\u7136\u9996\u5148\u82b1\u4e86\u4e24\u4e2a\u4e0b\u5348\u8fc7\u4e86\u4e00\u904d\u9a6c\u5fb7\u8ba1\u7ec4\u7684\u667a\u4e91 + xyx\u8ba1\u7ec4\u7b14\u8bb0\uff0c\u8fb9\u5b66\u8fb9\u52a8\u7b14

    \u8fd8\u6709\u6284 A4 \u7684\u89c4\u5212\u8bf7\u89c1\u6211 github \u90a3\u4e2a ZJU \u8d44\u6e90\u4ed3\u5e93

    \u53c2\u8003\u8d44\u6599

    "},{"location":"docs/1-cs/architecture/chap2/","title":"chap2: Memory Hierachy Design","text":"

    :material-circle-edit-outline: \u7ea6 3017 \u4e2a\u5b57 :fontawesome-solid-code: 28 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap2/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap2/#cache","title":"cache \u57fa\u7840\u6982\u5ff5","text":"

    \u8fd9\u5757\u5e38\u8003\u5927\u9898\uff0c\u6bd4\u5982\u8ba1\u7b97\u5730\u5740\u957f\u5ea6\uff0c\u8ba1\u7b97 AMAT\uff0c\u8ba1\u7b97 miss \u6b21\u6570\u7b49\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#cache_1","title":"cache \u7684\u5206\u7c7b\u548c\u5730\u5740\u7684\u8ba1\u7b97\u65b9\u6cd5","text":"

    Warning

    \u8fd9\u4e2a\u8868\u8bb0\u4e0d\u6e05\u4e86\u6253\u7b97\u7b49\u4e0a\u8ba1\u7ec4\u518d\u8865\u3002

    \u7c7b\u522b \u89e3\u91ca \u6807\u8bb0\u9879\u7ed3\u6784 \u5730\u5740\u8ba1\u7b97 \u4f18\u70b9 \u7f3a\u70b9 direct-mapping \u76f4\u63a5\u6620\u5c04 fully associative \u5168\u5173\u8054 2^n-set associative 2^n\u8def\u7ec4\u5173\u8054 "},{"location":"docs/1-cs/architecture/chap2/#cache-write","title":"cache write \u7684\u5904\u7406\u65b9\u6cd5","text":"write \u7b56\u7565 \u89e3\u91ca \u7ecf\u5e38\u642d\u914d\u7684 write-miss \u7b56\u7565 \u89e3\u91ca write through \u6bcf\u6b21\u5199\u6570\u636e\u65f6\u65e2\u5199\u5728cache\u4e5f\u5199\u5728main memory\u3002\u597d\u5904\u662fcache\u548cmain memory\u603b\u662f\u4e00\u81f4\u7684\uff0c\u4f46\u662f\u5f88\u6162\u3002\u53ef\u4ee5\u901a\u8fc7\u5f15\u5165\u4e00\u4e2awrite buffer\u6765\u6539\u8fdb\u3002 write around\uff08\u4e5f\u53ebnon-allocate\uff09 \u8003\u8651\u5230\u65e2\u7136\u672c\u6765\u5c31\u8981\u53bb\u4e00\u6b21main memory\uff0c\u4e0d\u5982\u76f4\u63a5\u5199\u5728\u91cc\u9762\uff0c\u4e0d\u518d\u62ff\u5230cache\u91cc\u4e86\u3002 write back \u53ea\u5c06\u4fee\u6539\u540e\u7684\u5185\u5bb9\u653e\u5728cache\u91cc\uff0c\u8be5block\u8981\u88ab\u8986\u76d6\u7684\u65f6\u5019\u518d\u5199\u56de\u5185\u5b58\u3002\u8fd9\u79cd\u60c5\u51b5\u9700\u8981\u4e00\u4e2a\u989d\u5916\u7684dirty bit\u6765\u8bb0\u5f55\u8fd9\u4e2acache\u662f\u5426\u88ab\u66f4\u6539\u8fc7\uff0c\u4ece\u800c\u76f4\u5230\u88ab\u8986\u76d6\u524d\u662f\u5426\u9700\u8981\u88ab\u5199\u56de\u5185\u5b58\u3002 write allocate \u50cfread miss\u4e00\u6837\u5148\u628ablock\u62ff\u5230cache\u91cc\u518d\u5199\u5165"},{"location":"docs/1-cs/architecture/chap2/#cache-miss-3c","title":"cache miss \u7684\u79cd\u7c7b \uff08\u7b80\u79f0\u4e3a3C\uff09","text":"\u79cd\u7c7b \u89e3\u91ca compulsory miss \u51b7\u542f\u52a8\u5931\u914d\uff0c\u521a\u4e0a\u7535cache\u662f\u7a7a\u7684\uff0c\u6240\u4ee5\u4e0d\u8bba\u4ec0\u4e48\u8bbf\u95ee\u90fd\u8981miss\u4e00\u6b21\u3002cache\u8d8a\u5927compulsory miss\u8d8a\u591a\u3002 capacity miss cache\u5757\u7684\u5927\u5c0f\u4e0d\u6ee1\u8db3\u7a0b\u5e8f\u5c40\u90e8\u6027\u65f6\u53d1\u751f\u7684\u5931\u914d\uff0c\u79f0\u4e3a\u5bb9\u91cf\u5931\u914d\u3002cache\u5757\u5927\u5c0f\u589e\u5927\uff0c\u5bb9\u91cf\u5931\u914d\u7387\u51cf\u5c0f\uff0c\u4e0e\u5173\u8054\u5ea6\u65e0\u5173\u3002 conflict miss \u5728\u91c7\u7528\u7ec4\u5173\u8054\u548c\u76f4\u63a5\u6620\u50cf\u65b9\u5f0f\u7684cache\u4e2d\uff0c\u4e3b\u5b58\u7684\u5f88\u591a\u5757\u90fd\u6620\u5c04\u5230cache\u7684\u540c\u4e00\u5757\uff0c\u5982\u679c\u67d0\u5757\u672c\u6765\u5728cache\u4e2d\uff0c\u521a\u88ab\u66ff\u6362\u51fa\u53bb\uff0c\u53c8\u88ab\u8bbf\u95ee\u5230\u3002\u6709\u70b9\u50cf OS \u91cc\u9875\u66ff\u6362\u65f6\u8bb2\u5230\u7684\u201c\u6296\u52a8\u201d\u3002\u5173\u8054\u5ea6\u8d8a\u5927\uff0cConflict\u5931\u914d\u8d8a\u5c0f\u3002"},{"location":"docs/1-cs/architecture/chap2/#cache_2","title":"cache \u4f18\u5316\u65b9\u6cd5","text":"

    \u8fd9\u5757\u5e38\u8003\u9009\u62e9\u3002

    \u603b\u7ed3\u6027\u7684\u56fe

    \u63a5\u4e0b\u6765\u5177\u4f53\u8bb2\u89e3\u6bcf\u4e00\u79cd\u4f18\u5316\u65b9\u6cd5\u3002

    \u9996\u5148\u56db\u5927\u7c7b\u4f18\u5316\u7684\u601d\u8def\u662f\u5982\u4f55\u4ea7\u751f\u7684\uff1f\u6765\u81ea\u4e8e\u8861\u91cf\u5185\u5b58\u6027\u80fd\u7684\u516c\u5f0f\uff1a

    \\[ Average\\space Memory\\_access\\space Time\\space (AMAT) = Hit\\_time + Miss\\_rate \\times Miss\\_penalty \\]

    \u9996\u5148\u8fd9\u4e2a\u516c\u5f0f\u7684\u610f\u601d\u662f\uff0c\u5f53 CPU \u9700\u8981\u5185\u5b58\u8bbf\u95ee\u7684\u65f6\u5019\uff0c\u8bbf\u95ee\u65f6\u95f4\u7684\u8ba1\u7b97\u65b9\u6cd5\u662f\uff1a - \u5982\u679c\u5728 cache \u91cc\u627e\u5230\u4e86\uff0c\u5373\u53d1\u751f cache hit\uff0c\u90a3\u4e48\u9700\u8981\u7684\u65f6\u95f4\u53ea\u6709 cache \u7684\u8bbf\u95ee\u7528\u65f6\u5373hit_time\u3002 - \u5982\u679c\u5728 cache \u91cc\u6ca1\u627e\u5230\uff08\u6b64\u65f6\u5df2\u7ecf\u7528\u4e86\u4e00\u4e2a hit_time\uff0c\u8fd9\u5c31\u662f\u4e3a\u4ec0\u4e48 hit_time \u662f 100% \u8981\u7528\u6389\u7684\uff09\uff0c\u90a3\u4e48\u5c31\u9700\u8981\u53bb\u5185\u5b58\u91cc\u627e\uff0c\u53bb\u5185\u5b58\u91cc\u627e\u7684\u7528\u65f6\u662f\u8fd9\u79cd\u60c5\u51b5\u6240\u5360\u7684\u767e\u5206\u6bd4 miss_rate \u4e58\u4e0a\u53bb\u5185\u5b58\u91cc\u627e\u4e00\u6b21\u7684\u8017\u65f6 miss_penalty\u3002

    Note

    \u5f53\u7136\u9898\u76ee\u91cc\u8fd8\u53ef\u80fd\u4f1a\u8bf4 \"cache \u548c memory \u662f\u540c\u65f6\u8bbf\u95ee\u7684\"\uff0c\u610f\u601d\u5c31\u662f cache \u548c memory \u4e00\u8d77\u627e\uff0c\u5982\u679c cache \u91cc\u627e\u5230\u4e86\uff0c\u5c31\u628a memory \u8bbf\u95ee\u6390\u6389\uff0c\u8fd9\u6837\u5728 miss \u7684\u60c5\u51b5\u4e0b\u662f\u6bd4\u5148\u5728 cache \u91cc\u627e\u5b8c\u518d\u53bb memory \u627e\u66f4\u5feb\u7684\u3002\u8fd9\u6837\u7684\u6761\u4ef6\u4e0b\u8ba1\u7b97 AMAT \u5c31\u9700\u8981\u628a hit_time \u4e58\u4e0a\u4e00\u4e2a hit_rate\uff0c\u4e0d\u518d\u662f 100% \u7528\u6389\u4e86\u3002

    \u603b\u4e4b\uff0cAMAT \u7684\u8868\u8fbe\u5f0f\u7ed9\u6211\u4eec\u63d0\u4f9b\u4e86\u4e09\u79cd\u4f18\u5316\u7684\u5927\u65b9\u5411\uff0c\u5373 (1)\u964d\u4f4e hit_time (2)\u51cf\u5c0f miss_rate (3)\u51cf\u5c0f miss_penalty\u3002\u6b64\u5916\u8fd8\u6709\u4e00\u4e2a\u5927\u65b9\u5411\u53eb (4)\u505a\u5e76\u884c\u7684 cache\uff0c\u5728\u6709\u7684\u8001\u5e08\u7684 PPT \u91cc\u7b2c(4)\u9879\u597d\u50cf\u4f1a\u62c6\u51fa\u4e24\u7c7b\u6765\u8bb2\uff0c\u4e0d\u8fc7\u6211\u4eec\u8fd9\u91cc\u5c31\u6309\u603b\u5171\u56db\u79cd\u5927\u65b9\u5411\u6765\u5199\uff0c\u8ddf\u56fe\u4e00\u81f4\uff0c\u6bd4\u8f83\u8212\u670d\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#miss-penalty","title":"Miss Penalty","text":"

    Multilevel Caches

    \u7ecf\u5178\u7684\u5185\u5b58\u6a21\u578b\u662f

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [cache] - [\u5185\u5b58] - [\u5916\u5b58]\n

    \u8fd9\u4e2a\u65b9\u6cd5\u662f\u628a\u5b83\u53d8\u6210

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [\u5c0fcache] - [\u5927cache] - [\u5185\u5b58] - [\u5916\u5b58]\n
    \u6bd4\u5982\u5c0f cache \u6ca1\u627e\u5230\u7684\u5148\u4ece\u5927 cache \u627e\uff0c\u5927 cache \u6ca1\u627e\u5230\u7684\u518d\u53bb\u5185\u5b58\u627e\u3002\u6b64\u7c7b\u53ef\u80fd\u51fa AMAT \u7684\u8ba1\u7b97\u9898\uff0c\u628a\u5404\u79cd rate \u62ce\u6e05\u4ee5\u540e\u5c31\u50cf\u4f55\u8001\u5e08\u8bf4\u7684\u201c\u5f53\u6210\u521d\u4e2d\u7269\u7406\u9898\u505a\u5c31\u884c\u201d\u3002

    Early Resart & Critical Word 1st

    \u4f17\u6240\u5468\u77e5\uff08\u81f3\u5c11\u4f60\u73b0\u5728\u77e5\u9053\u4e86\uff09cache \u7684\u4e00\u4e2a block \u7ecf\u5e38\u662f\u542b\u6709\u591a\u4e2a word \u7684\uff08\u4f60\u53ef\u80fd\u4f1a\u604d\u7136\u5927\u609f\u6709\u4e9b\u9898\u76ee\u91cc\u8bf4\u7684\u201ccache \u6309 word \u7f16\u5740\u201d\u662f\u4ec0\u4e48\u610f\u601d\uff09\uff0c\u800c block \u5f80\u5f80\u662f\u5927\u4e8e cache \u548c\u5185\u5b58\u4e4b\u95f4\u7684\u6570\u636e\u7ebf\u4f4d\u5bbd\u7684\uff0c\u4e5f\u5c31\u662f\u8bf4\u60f3\u8981\u66ff\u6362\u4e00\u4e2a block\uff0c\u9700\u8981\u5728 cache \u548c\u5185\u5b58\u4e4b\u95f4\u4f20\u9001\u597d\u51e0\u8d9f\u624d\u80fd\u628a\u4e00\u4e2a block \u66ff\u6362\u5b8c\u3002

    \u4f46\u662f miss \u53d1\u751f\u65f6 CPU \u9700\u8981\u7684\u53ef\u80fd\u53ea\u6709\u4e00\u4e2a word\uff0c\u90a3\u4e48\u53ef\u4ee5\u5148\u628a CPU \u9700\u8981\u7684\u8fd9\u4e2a word \u5199\u56de\u6765\uff0c\u8ba9 CPU \u5148\u7ee7\u7eed\u8dd1\u8d77\u6765\uff0c\u5728 CPU \u7ee7\u7eed\u8dd1\u7684\u540c\u65f6\u518d\u628a\u5269\u4e0b\u7684 word \u5199\u8fdb cache\u3002

    Priority to Read Miss

    \u5728\u4f7f\u7528 write buffer \u7684\u60c5\u51b5\u4e0b\uff0c\u5982\u679c write \u7684\u6570\u636e\u5f88\u5feb\u5c31\u8981 read\uff0c\u53ef\u4ee5\u5148\u4e0d\u5c06 buffer \u7684\u6570\u636e\u5199\u8fdb\u5185\u5b58\uff0c\u800c\u662f\u7b49\u5230read\u7684\u65f6\u5019\u76f4\u63a5\u4ecebuffer\u91cc\u8bfb\uff0c\u8bfb\u591a\u6b21\u4e4b\u540e\u518d\u4e00\u6b21\u4ecebuffer\u91cc\u5199\u5185\u5b58\u3002

    \u5176\u4e2d\uff0cwrite buffer \u662f\u4e00\u4e2a\u53ef\u4ee5\u8bbe\u5728 cache \u548c\u5185\u5b58\u4e4b\u95f4\u7684\u7ed3\u6784\uff0c\u610f\u601d\u662f\uff0c\u5047\u8bbe\u5185\u5b58\u53ea\u6709\u4e00\u4e2a\u8bfb\u5199\u7aef\u53e3\uff0c\u5199\u5165\u5185\u5b58\u975e\u5e38\u6162\uff0c\u90a3\u4e48 cache \u53ef\u4ee5\u5c06\u9700\u8981\u5199\u5230\u5185\u5b58\u7684\u4e1c\u897f\u5148\u642c\u5230 write buffer \u91cc\uff0c\u7136\u540e cache \u5148\u8dd1\u7740\uff0c\u5185\u5b58\u53bb\u6162\u6162\u5199\u5165\u3002

    Merging Write Buffer

    \u540c\u6837\u662f\u4f7f\u7528 write buffer \u7684\u60c5\u51b5\u3002merging write buffer \u5c31\u662f\u5c06\u5728\u591a\u884c\u53ef\u4ee5\u4e00\u6b21\u5199\u56de\u7684\u5185\u5bb9\u5408\u5e76\u5230\u4e00\u884c\uff0c\u4ee5\u53ef\u4ee5\u4e00\u6b21\u5199\u56de\u3002write buffer \u7684\u5185\u5bb9\u662f\u6309 byte \u7f16\u5740\u7684\uff0c\u4f46\u5185\u5b58\u6570\u636e\u7ebf\u4f4d\u5bbd\u4e00\u822c\u5927\u4e8e byte\uff0c\u6bd4\u5982\u4e00\u6b21\u53ef\u4ee5\u5199\u56de\u4e00\u6574\u4e2a word\uff0c\u90a3\u4e48\u5047\u5982 write buffer \u91cc\u73b0\u5728\u6709\u56db\u884c mem[200], mem[400], mem[208], mem[408]\uff0c\u5199\u56de\u5185\u5b58\u5c31\u9700\u8981\u56db\u6b21\u3002\u4f46\u662f\u5982\u679c\u6211\u4eec\u628a\u5728\u540c\u4e00\u4e2a word \u91cc\u7684 byte \u5408\u5e76\u4e00\u4e0b\uff0c\u53d8\u6210 mem[200] mem[208] \u548c mem[400] mem[408] \u4e24\u884c\uff0c\u4e24\u6b21\u5199\u56de\uff0c\u5c31\u4f1a\u53d8\u5feb\u3002

    Victim Caches

    \u662f\u4e00\u79cd\u51cf\u5c11 conflict miss \u7684\u65b9\u6cd5\uff0c\u5373\u66ff\u6362\u51fa\u53bb\u7684\u9875\u5148\u653e\u8fdb\u8fd9\u4e2a victim cache \u7ed3\u6784\u3002victim cache \u4e0e cache \u662f\u5168\u76f8\u5173\u7684\uff0c\u6709\u70b9\u50cf\u4e00\u4e2a\u4e8c\u7ea7 cache\uff0c\u662f\u4e00\u4e2a\u6bd4\u4e00\u7ea7 cache \u6162\u7684 cache\u3002\u8fd9\u6837\u5982\u679c\u53d1\u751f conflict miss\uff0c\u4ece\u8fd9\u4e2a victim cache \u91cc\u53d6\u6570\u636e\u6bd4\u4ece\u5185\u5b58\u91cc\u53d6\u66f4\u5feb\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#miss-rate","title":"Miss Rate","text":"

    \u8fd9\u4e00\u680f\u7684\u524d\u4e09\u4e2a\u65b9\u6cd5\u90fd\u4e0d\u662f\u5f88\u806a\u660e\uff0c\u672c\u8d28\u4e0a\u662f\u5728 cache \u7684\u4e09\u79cd\u8bbe\u8ba1\u65b9\u6cd5\u4e2d\u53bb\u6743\u8861\uff0c\u800c\u6211\u4eec\u77e5\u9053 cache \u7684\u4e09\u79cd miss \u8fd8\u662f\u6b64\u6d88\u5f7c\u957f\u7684\uff0c\u54ea\u4e00\u79cd\u8bbe\u8ba1\u65b9\u6cd5\u90fd\u4e0d\u80fd\u5b8c\u7f8e\u89e3\u51b3\u3002\u4e0d\u8fc7\u6574\u4f53\u800c\u8a00\uff0cfrom \u738b\u9053\u8ba1\u7ec4\uff0c\u4f7f\u7528\u5408\u9002\u7684 2^n \u8def\u7ec4\u5173\u8054\u65f6\uff0c\u6700\u597d\u7684\u60c5\u51b5\u80fd\u591f\u51e0\u4e4e\u517c\u5177\u76f4\u63a5\u6620\u5c04\u7684\u6548\u7387\u548c\u5168\u5173\u8054\u7684\u547d\u4e2d\u7387\u3002

    Larger Block Size

    \u628a cache \u7684\u6bcf\u4e2a\u5757\u8bbe\u8ba1\u5f97\u66f4\u5927\uff0c\u8fd9\u6837\u6bcf\u4e2a\u5757\u5b58\u5f97\u4e1c\u897f\u591a\u4e86\uff0c\u5f53\u7136 miss_rate \u5c31\u4e0b\u964d\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0cmiss_penalty \u4e0a\u5347\u4e86\uff0c\u56e0\u4e3a\u5199\u8d77\u6765\u53d8\u6162\u4e86\u3002

    Larger Cache Size

    \u628a cache \u7684\u5757\u6570\u589e\u591a\uff0c\u8fd9\u6837\u5b58\u5f97\u4e1c\u897f\u4e5f\u591a\u4e86\uff0cmiss_rate \u5c31\u4e5f\u4e0b\u964d\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0c\u51b7\u542f\u52a8 compulsory miss \u4e0a\u5347\u4e86\uff1b\u5982\u679c\u4e0d\u662f\u76f4\u63a5\u6620\u5c04\uff0c\u67e5\u627e\u65f6\u95f4\u4e5f\u4e0a\u5347\u4e86\u3002

    Higher Associativity

    \u63d0\u5347\u7ec4\u5173\u8054\u6570\uff0c\u8fd9\u6837\u51cf\u5c11 cache \u91cc\u9762\u7684\u4e1c\u897f\u88ab\u66ff\u6362\u51fa\u53bb\u7684\u6982\u7387\uff0c\u51cf\u5c11 conflict miss\u3002\u7f3a\u70b9\u4e5f\u5f88\u660e\u663e\uff0c\u67e5\u627e\u65f6\u95f4\u589e\u52a0\u3002

    Way-predicting Cache

    \u5728\u7ec4\u5173\u8054\u8bbe\u8ba1\u4e2d\uff0c\u4f7f cache \u5177\u6709\u9884\u6d4b\u9700\u8981\u67e5\u627e\u7684 tag \u7684\u80fd\u529b\u3002\u56e0\u4e3a\u53bb\u67e5\u9700\u8981\u7684\u6570\u636e\u5728\u7ec4\u91cc\u54ea\u4e2a tag \u6bd4\u8f83\u6162\uff0c\u6240\u4ee5\u5148\u731c\u4e00\u4e2a tag \u5728 cache \u91cc\u627e\u7740\uff0c\u7b49 tag \u51c6\u5907\u597d\u540e\u5982\u679c\u731c\u5bf9\u4e86\uff0c\u90a3\u4e48\u8282\u7ea6\u4e86\u65f6\u95f4\uff0c\u5c31\u53ef\u4ee5\u76f4\u63a5 hit\u3002

    Pseudo-associative Caches

    \u65e2\u662f\u76f4\u63a5\u6620\u5c04\u53c8\u662f\u7ec4\u5173\u8054\u6620\u5c04\u7684 cache\u3002\u9996\u5148\u628a cache \u5f53\u4f5c\u4e00\u4e2a\u76f4\u63a5\u6620\u5c04 cache\uff0c\u7b2c\u4e00\u6b21\u67e5\u7684\u65f6\u5019\u5c31\u8fd9\u4e48\u67e5\uff0c\u6700\u5feb\u3002\u4f46\u662f\u8fd9\u79cd cache \u53c8\u540c\u65f6\u662f\u4e00\u4e2a\u7ec4\u5173\u8054\u6620\u5c04\uff0c\u5728 cache \u5757\u4e2d\u653e\u4e00\u4e2a\u989d\u5916\u7684\u6807\u5fd7\u8868\u793a\u4e0e\u4e4b\u5173\u8054\u7684\u5176\u5b83\u5757\uff0c\u5982\u679c miss \u4e86\u518d\u53bb\u67e5\u8fd9\u4e9b\u5757\u3002\u8fd9\u6837\u6709\u4e00\u4e2a\u5c0f\u7684 hit_time \u548c2^n - 1\u4e2a\u5927\u7684 pseudo_hit_time\uff0c\u4f46\u662f\u5e73\u5747\u6765\u8bf4 miss_rate \u6bd4\u76f4\u63a5\u6620\u5c04\u5c0f\uff0chit_time \u6bd4\u7ec4\u5173\u8054\u6620\u5c04\u5c0f\u3002

    Compiler Techniques Reduce Cache Misses

    \u7528\u8f6f\u4ef6\u65b9\u6cd5\uff0c\u4f18\u5316\u4ee3\u7801\u3002\u8fd9\u91cc\u6709\u56db\u4e2a\u4f8b\u7a0b\uff0c\u5206\u522b\u53eb Merging Arrays, Loop Interchange, Blocking, \u548c Loop Merging\u3002\u7b80\u5355\u7684\u76f4\u63a5\u7528\u6587\u5b57\u63cf\u8ff0\u4e86\u3002

    Merging Arrays

    \u6bd4\u5982\u6211\u4eec\u9700\u8981\u8bbf\u95ee\u7684\u662fa[100], b[100], \u5728\u540c\u4e00\u4e2a\u5faa\u73af\u91cc\u8fde\u7eed\u8bbf\u95eea[i] b[i]\u5373\u4e0b\u6807\u76f8\u540c\u7684\u9879\uff0ccache\u5982\u679c\u4e00\u6b21\u6027\u653e\u4e0d\u4e0b\u4e24\u4e2a\u6570\u7ec4\uff0c\u5c31\u4f1a\u4e24\u4e2a\u6570\u7ec4\u4ea4\u66ff\u4ece\u5185\u5b58\u91cc\u53d6\u51fa\u6765\u653e\u5230cache\u91cc\u3002\u8fd9\u65f6\u5019\u53ef\u4ee5\u8bbe\u8ba1\u6210\u4e00\u4e2a\u7ed3\u6784\u4f53\u6570\u7ec4struct ab { a[100], b[100] }\uff0c\u8fd9\u6837 cache \u53ef\u4ee5\u628a a \u548c b \u76f8\u90bb\u5730\u62ff\u8fdb\u6765\u3002\u51cf\u5c11miss\u3002

    Loop Interchange

    e.g.

    /* Before: \u5916\u884c\u5185\u5217\uff0c\u4e00\u884c\u53ef\u4ee5\u4e00\u6b21\u88ab\u653e\u8fdb\u5185\u5b58 */\nfor (k = 0; k < 100; k = k+1)\nfor (j = 0; j < 100; j = j+1)\nfor (i = 0; i < 5000; i = i+1)\nM[i][j] = 2 * M[i][j];\n/* After: \u5916\u5217\u5185\u884c */\nfor (k = 0; k < 100; k = k+1)\nfor (i = 0; i < 5000; i = i+1)\nfor (j = 0; j < 100; j = j+1)\nM[i][j] = 2 * M[i][j];\n

    \u4fee\u6539\u540e\u7684cache\u547d\u4e2d\u7387\u53d8\u9ad8\u4e86\uff0c\u56e0\u4e3a\u4ea4\u6362\u540e\u5bf9\u5185\u5b58\u7684\u8bbf\u95ee\u662f\u8fde\u7eed\u7684\u3002\u4e00\u822c\u662f\u884c\u5bf9\u9f50\u7684\uff0c\u6700\u4f4e\u7ef4\u662f\u76f8\u90bb\u7684\u3002

    Blocking

    \u9002\u5f53\u62c6\u5206\u8fd0\u7b97\uff0c\u4ee5\u914d\u5408cache\u5927\u5c0f\u3002e.g. \u77e9\u9635\u76f8\u4e58\u4f8b\u5b50\u3002

    /* Before */\nfor (i = 0; i < N: i += 1)\nfor (j = 0; j < N; j += 1) {\nr = 0;      for (k = 0; k < N; k +=1 )\nr = r + y[i][k] * z[k][j];  }\n/* After */\nfor (jj = 0 ; jj < N; jj = jj+B)\nfor (kk = 0; kk < N; kk = kk +B) {\n// ...\u8bb0\u4e0d\u6e05\u4e86\nfor (ii = 0; ii < B; ii ++) {\n// \u603b\u4e4b\u8fd9\u4e2a\u5185\u5c42\u5faa\u73af\u53ea\u5904\u7406\u4e00\u4e2a B * B \u7684 block\uff0c\u5176\u4e2d block \u662f cache \u80fd\u653e\u4e0b\u7684\u5927\u5c0f\n}\n}\n
    \u90a3\u4e48\u4f18\u5316\u524d cache \u9700\u8981\u66ff\u6362\u66f4\u591a\u6b21\uff0c\u56e0\u4e3a\u4e0d\u8bba\u662f\u884c\u5faa\u73af\u8fd8\u662f\u5217\u5faa\u73af\uff0c\u8d85\u8fc7 B \u4e4b\u540e cache \u90fd\u8981\u91cd\u65b0\u5199\u4e00\u904d\u3002\u7136\u540e\u4e0b\u6b21\u5199\u5230\u8fd9\u4e2a block \u65f6\u518d\u6362\u8fdb\u6765\u4e00\u6b21\u3002

    \u4f18\u5316\u540e\u6bcf\u6b21\u5bf9\u6bcf\u4e00\u4e2a block \u4e00\u6b21\u6027\u5b8c\u6210\u64cd\u4f5c\u3002

    Loop Merging

    \u6bd4\u5982\u6709\u4e24\u4e2a\u5faa\u73af\u7684\u5faa\u73af\u8d77\u6b62\u6761\u4ef6\u4e00\u6837\uff0c\u90a3\u4e48\u5c31\u4e0d\u8981\u5f00\u4e24\u4e2a\u5faa\u73af\u4e86\uff0c\u5408\u5e76\u5230\u4e00\u4e2a\u5faa\u73af\u91cc\u5b8c\u6210\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#parallelism","title":"Parallelism","text":"

    Non-blocking Caches

    cache miss\u65f6, \u7b49\u5f85\u5185\u5b58\u5199\u56de\u65f6\u7ee7\u7eed\u505a\u522b\u7684\u6ca1\u6709\u51b2\u7a81\u7684\u4e8b\u60c5\uff0c\u4e0d\u5fc5\u8981\u8ba9\u6240\u6709\u7684\u8d44\u6e90\u90fd\u7b49\u5f85\u5185\u5b58\u3002\u53ef\u4ee5\u8ba9\u522b\u7684\u5757\u5148\u5b8c\u6210\u522b\u7684\u6307\u4ee4\u7684\u9700\u6c42\u3002\u6bd4\u5982\u5728\u5904\u7406write miss\u7684\u65f6\u5019\uff0c\u5141\u8bb8\u5904\u7406read hit\u3002

    \u4e3b\u8981\u7528\u4e8eout of order\uff08\u4e71\u5e8f\uff09\u7684\u5904\u7406\u5668\u4e0a\u3002

    ppt \u7ed9\u7684\u5b9a\u4e49\u662f\uff1aallows cache to continues to supply hits while processing read misses (hit under miss, hit under multiple miss)

    Hardware Prefetching of Instr/Data

    \u53ef\u4ee5\u7531\u786c\u4ef6\u63a7\u5236\u6570\u636e\u9884\u53d6\uff0c\u4e00\u79cd\u7c7b\u4f3c branch-prediction \u7684\u505a\u6cd5\u3002\u9884\u6d4b\u5e76\u63d0\u524d\u53d6\u51fa\u53ef\u80fd\u9700\u8981\u7528\u5230\u7684\u6570\u636e\u653e\u5230cache\u91cc\u3002

    \u4f7f\u7528prefetching\u7684\u524d\u63d0\u662f\u6307\u4ee4\u662f\u5e76\u884c\u7684\uff0ccache \u4e5f\u662f non-blocking \u7684\u3002

    Compiler Controlled Prefetching

    \u4e0a\u9762\u4e00\u6761\u9884\u53d6\u65b9\u6cd5\uff0c\u4e5f\u53ef\u4ee5\u7531\u7a0b\u5e8f\u5458\u548c\u7f16\u8bd1\u5668\u624b\u52a8\u6307\u5b9a\u54ea\u4e9b\u5185\u5bb9\u5e94\u8be5\u88ab\u653e\u5230cache\u3002

    "},{"location":"docs/1-cs/architecture/chap2/#hit-time","title":"Hit Time","text":"

    Small & Simple Caches

    \u6bd4\u5982\u5c31\u9488\u5bf9 cache \u672c\u8eab\uff0c\u51cf\u5c0f cache \u7684\u590d\u6742\u5ea6\u4ee5\u51cf\u5c0f\u7ec4\u5408\u903b\u8f91\u7684\u5ef6\u8fdf\u3002\u5f53\u7136\u7531\u4e8e\u6211\u4eec\u4e4b\u524d\u8ba8\u8bba\u8fc7\u7684 cache \u4e09\u4e2a\u6307\u6807\u7684\u76f8\u4e92\u5236\u7ea6\uff0c\u662f\u53ef\u80fd\u4f1a\u5bfc\u81f4\u5176\u5b83\u4e24\u4e2a\u6307\u6807\u53d8\u4e0d\u597d\u7684\u3002

    Avoiding Address Translation

    \u8fd9\u91cc\u9700\u8981\u5206\u522b\u56de\u5fc6\u4e00\u4e0b cache \u6807\u8bb0\u4f4d\u7684\u7ed3\u6784\u548c OS \u91cc\u7684\u9875\u8868\u9879\u3002\u4e00\u822c\u672c\u8bfe\u7a0b\u4e2d\u4f7f\u7528\u7684 cache \u8bbe\u8ba1\u89c4\u5219\u90fd\u662f \"physically tagged, virtually indexed\"(PTVI)\uff0c\u610f\u601d\u662f\uff0c\u7528\u4e8e\u67e5\u627e cache block \u7684 tag \u6574\u4e2a\u5168\u90fd\u5728 page offset \u91cc\uff0c\u8fd9\u5757 offset \u5b57\u6bb5\u5bf9\u4e8e\u865a\u62df\u5730\u5740\u548c\u7269\u7406\u5730\u5740\u6765\u8bf4\u662f\u5b8c\u5168\u4e00\u6837\u7684\uff0c\u53ea\u6709 page number \u9700\u8981\u9001\u8fdb tlb \u53bb\u5bfb\u627e\u7269\u7406\u5e27\u53f7\u3002\u5982\u56fe\u3002

    \u5982\u679c\u4e4b\u524d\u7684\u505a\u6cd5\u662f cache \u7b49\u5230\u7269\u7406\u5e27\u53f7\u627e\u51fa\u6765\u3001\u5730\u5740\u7ffb\u8bd1\u5b8c\u518d\u53bb\u67e5\u627e\uff0c\u5c31\u592a\u6162\u4e86\u3002\u65e2\u7136 tag \u4e0d\u7528\u7b49\u5230\u5730\u5740\u7ffb\u8bd1\u5c31\u80fd\u62ff\u5230\uff0c\u53ef\u4ee5\u4f7f\u5730\u5740\u7ffb\u8bd1\u548c cache \u67e5\u627e\u540c\u65f6\u8fdb\u884c\u3002

    Pipelined Cache Access

    \u56e0\u4e3a cache management unit \u7684\u64cd\u4f5c\u5206\u4e3a\u597d\u591a\u6b65\uff0c\u53ef\u4ee5\u628a\u6bcf\u6b65\u53bb\u50cf\u6d41\u6c34\u7ebf\u4e00\u6837\u5e76\u884c\u3002\u7f3a\u70b9\u662f\u4f1a\u589e\u52a0\u7cfb\u7edf\u5f00\u9500\uff0c\u5bfc\u81f4 hit_time \u589e\u52a0\uff0c\u4f46\u662f\u597d\u5904\u662f\u524d\u9762\u7684\u6307\u4ee4 miss \u65f6\uff0c\u4e0b\u4e00\u6761\u6307\u4ee4\u53ef\u4ee5\u5e76\u884c\u3002

    Multi-banked Cache

    \u5c06\u591a\u8def\u7ec4\u5173\u8054\u7684\u6bcf\u4e00\u8def\u7684\u67e5\u627e\u5e76\u884c\u3002

    ppt \u7ed9\u7684\u5b9a\u4e49\u662f\uff1acache is divided into independent banks that can support simultateous accesses like interleaved memory banks.

    Trace Cache

    \u6838\u5fc3\u903b\u8f91\u662f\u7f13\u5b58\u903b\u8f91\u4e0a\u7684\u6307\u4ee4\u6d41\uff0c\u800c\u4e0d\u662f\u7f13\u5b58\u7269\u7406\u5730\u5740\u7684\u6307\u4ee4\u6d41\uff0c\u4ece\u800c\u52a0\u5feb\u6307\u4ee4\u7684\u9884\u53d6\u3002\u6bd4\u5982\u5206\u652f\u6307\u4ee4\u4e2d\u4e0d\u53bb\u9884\u6d4b\u91cc cache \u4e0d\u4f1a\u547d\u4e2d\u7684\u5206\u652f\uff0c\u8fd9\u6837\u8282\u7701\u4e86 cache \u7a7a\u95f4\uff0c\u4e5f\u8ba9\u76f8\u90bb\u7684\u6307\u4ee4\u5728 cache \u4e2d\u4e5f\u76f8\u90bb\u3002\u6211\u7684\u7406\u89e3\u5b83\u7684\u610f\u601d\u662f\u628a prediction \u7684\u529f\u80fd\u9001\u7ed9\u4e86 cache\uff0c\u5982\u679c\u5206\u652f\u9884\u6d4b\u9884\u6d4b\u5230\u4e86\u67d0\u4e2a\u8df3\u8f6c\u6307\u4ee4\u4f1a\u53d1\u751f\uff0c\u90a3\u4e48 cache \u5c31\u53bb\u9884\u53d6\u53d1\u751f\u7684\u5206\u652f\u540e\u9762\u7684\u6570\u636e\u3002

    "},{"location":"docs/1-cs/architecture/chap3/","title":"chap3: Instruction-level Parallelism (ILP)","text":"

    :material-circle-edit-outline: \u7ea6 1058 \u4e2a\u5b57 :fontawesome-solid-code: 9 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap3/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap3/#ilp","title":"ILP \u57fa\u7840\u6982\u5ff5","text":"

    Note

    \u662f\u5199\u5f97\u7b80\u5355\u70b9\u4e86\u54c8\u3002\u5199\u4e0d\u52a8\u4e86\u3002\u8981\u4e0d\u5927\u5bb6\u770b\u8ba1\u7ec4\u738b\u9053\u597d\u4e86\u3002

    \u4e09\u79cd\u7ade\u4e89

    \u6d41\u6c34\u7ebf\u7c7b\u578b

    \u770b\u7684\u65f6\u5019\u6ce8\u610f\u603b\u7ed3\u4e00\u4e0b\u6bcf\u4e00\u79cd\u7684 CPI \u662f\u5927\u4e8e\u7b49\u4e8e\u8fd8\u662f\u5c0f\u4e8e 1\u3002\u6211\u603b\u7ed3\u4e0d\u51fa\u6765\u4e86\u3002

    "},{"location":"docs/1-cs/architecture/chap3/#ilp_1","title":"ILP \u5728\u4f53\u7cfb\u91cc\u5b66\u7684\u4e09\u79cd\u7b97\u6cd5","text":"

    Note

    \u672c\u6765\u8fd9\u5757\u8be5\u5199\u7684\u4f46\u662f\u6211\u5199\u4e0d\u52a8\u4e86

    \u76f4\u63a5\u53bb bing \u641c\u7d22 (1)Scoreboard, (2)Tomasulo, (3)Tomasulo w speculation, \u53bb\u627e\u4e00\u4e2a\u5357\u5927\u540c\u5b66\u5199\u7684\u77e5\u4e4e\u5e16\u5b50\uff0c\u6211\u662f\u770b\u8fd9\u5957\u5e16\u5b50\u770b\u61c2\u7684\u3002\u8fd8\u6709 lab \u91cc\u8fd9\u5757\u7684\u5b9e\u9a8c\u4e5f\u80fd\u5e2e\u52a9\u7406\u89e3\u3002

    \u8bf7\u518d\u7ed3\u5408\u8fd9\u5f20\u56fe\u8bb0\u5fc6\u4e00\u4e0b\uff1a

    \u8fd8\u6709\u4e00\u4e2a\u4e0a\u8ff0\u8d44\u6599\u4f3c\u4e4e\u6ca1\u8bb2\u5230\u7684\u70b9\uff0c\u5173\u4e8e ISSUE \u65f6\u673a\uff0c\u6211\u8bb0\u5f97\u662f - Scoreboard: \u9700\u8981\u7684 Function Unit \u4e3a\u7a7a\uff0c\u4e14\u9700\u8981\u5199\u7684 Reg State \u6ca1\u6709\u522b\u7684\u6307\u4ee4\u8fd8\u51c6\u5907\u5199\uff08\u907f\u514d WAW\uff09\u65f6\u3002 - Tomasulo: Reservation Station \u6709\u7a7a\u65f6\u3002 - Tomasulo w ROB (\u5373 w speculation): Reservation Station \u548c ROB \u90fd\u7a7a\u65f6\u3002

    Warning

    \u4f46\u662f\u4e0a\u8ff0 Tomasulo w ROB \u4f3c\u4e4e\u8ddf\u6211\u8003\u7684\u4e00\u4e2a\u671f\u672b\u9898\u4e0d\u517c\u5bb9\uff0c\u4e0d\u77e5\u9053\uff0c\u7b49\u540e\u4eba\u6765\u4e3a\u6211\u6307\u51fa

    "},{"location":"docs/1-cs/architecture/chap3/#branch-prediction","title":"Branch prediction","text":"

    \u56de\u5fc6 control hazard\uff0c\u6d41\u6c34\u7ebf CPU \u9047\u5230\u8df3\u8f6c\u8bed\u53e5\u5982\u679c\u5224\u65ad\u6761\u4ef6\u8fd8\u6ca1\u5c31\u7eea\uff0c\u5c31\u9700\u8981\u7b49\u64cd\u4f5c\u6570\u624d\u80fd\u7ee7\u7eed\u5f80\u4e0b\u8d70\u3002\u6211\u4eec\u60f3\u8ba9 CPU \u968f\u4fbf\u5148\u731c\u4e00\u4e2a\u5f80\u4e0b\u8d70\u7740\uff0c\u5982\u679c\u7b49\u64cd\u4f5c\u6570\u51c6\u5907\u597d\u53d1\u73b0\u731c\u9519\u4e86\uff0c\u5927\u4e0d\u4e86\u518d\u6390\u6389\uff0c\u731c\u5bf9\u4e86\u90a3\u5c31\u8282\u7ea6\u65f6\u95f4\u4e86\u3002

    \u731c\u7684\u6839\u636e\u6709\u4ec0\u4e48\u5462\uff0c\u786e\u5b9e\u6709\u6839\u636e\uff0c\u7edf\u8ba1\u8868\u660e\u5927\u90e8\u5206\u7a0b\u5e8f\u91cc\u53d1\u751f\u8df3\u8f6c\uff08branch taken\uff09\u548c\u4e0d\u53d1\u751f\u8df3\u8f6c\uff08branch not taken\uff09\u7684\u6570\u76ee\u662f\u4e25\u91cd\u4e0d\u6210\u6bd4\u4f8b\u7684\uff0c\u7ecf\u5e38\u5176\u4e2d\u4e00\u4e2a\u53ef\u80fd\u80fd\u5360\u5230 90% \u591a\u7684\u60c5\u51b5\u3002\u90a3\u4e48\uff0c\u5047\u8bbe\u5982\u679c\u77e5\u9053\u4e4b\u524d\u5f88\u591a\u8df3\u8f6c\u8bed\u53e5\u90fd\u8df3\u4e86\uff0c\u63a5\u4e0b\u6765\u53d1\u751f\u7684\u8df3\u8f6c\u8bed\u53e5\u4e5f\u5927\u6982\u7387\u4f1a\u8df3\u3002

    \u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u8bbe\u8ba1\u4e00\u4e2a\u72b6\u6001\u673a\uff0c\u6709\u56db\u79cd\u7f16\u7801 00(\u5f88\u53ef\u80fd\u8df3) 01(\u5e94\u8be5\u8df3\u5427) 10(\u5e94\u8be5\u4e0d\u8df3\u5427) 11(\u5f88\u53ef\u80fd\u4e0d\u8df3)\uff0c\u5982\u679c\u72b6\u6001\u673a\u5728 00 \u548c 01 \u72b6\u6001\u5c31\u9884\u6d4b\u4e0b\u4e00\u6b21\u4e5f\u8df3\u8f6c\uff0c\u5982\u679c\u72b6\u6001\u673a\u5728 10 \u548c 11 \u5c31\u9884\u6d4b\u4e0b\u4e00\u6b21\u4e0d\u8df3\u8f6c\u3002

    \u800c\u72b6\u6001\u8f6c\u79fb\u662f\u8fd9\u6837\u53d1\u751f\u7684\uff1a

    Note

    \u6211\u77e5\u9053 mkdocs \u5e94\u8be5\u6e32\u4e0d\u4e86 mermaid\uff0c\u4f46\u662f\u6211\u61d2\uff0c\u8bf7\u5927\u5bb6\u8111\u6e32\u4e00\u4e0b\u3002\u3002\u6216\u8005\u770b\u81ea\u5df1\u8001\u5e08 ppt\u3002\u3002\u662f\u4e00\u4e2a\u6709\u56db\u4e2a\u72b6\u6001\u7684\u7ea2\u7ea2\u84dd\u84dd\u7684\u72b6\u6001\u673a

    graph LR\n00 --(\u672c\u6b21\u8df3\u4e86)--> 00\n00 --(\u672c\u6b21\u6ca1\u8df3)--> 01\n01 --(\u672c\u6b21\u8df3\u4e86)--> 00\n01 --(\u672c\u6b21\u6ca1\u8df3)--> 10\n10 --(\u672c\u6b21\u8df3\u4e86)--> 01\n10 --(\u672c\u6b21\u6ca1\u8df3)--> 11\n11 --(\u672c\u6b21\u8df3\u4e86)--> 10\n11 --(\u672c\u6b21\u6ca1\u8df3)--> 11\n

    \u8ba1\u7b97\u9898\u4f1a\u8003\u4f7f\u7528\u8fd9\u6837\u7684 branch prediction\uff0c\u9884\u6d4b\u5931\u8bef\u7684\u6982\u7387\u662f\u591a\u5c11\u3002

    "},{"location":"docs/1-cs/architecture/chap5/","title":"chap5: Thread-level Parallelism","text":"

    :material-circle-edit-outline: \u7ea6 381 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/architecture/chap5/#_1","title":"\u76ee\u5f55","text":""},{"location":"docs/1-cs/architecture/chap5/#cache","title":"cache \u4e00\u81f4\u6027\u7684\u6982\u5ff5","text":"

    \u4e0d\u77e5\u9053\u600e\u4e48\u63cf\u8ff0\u7684\u4e24\u4e2a\u672f\u8bed

    Note

    \u8ba1\u7ec4\u738b\u9053\u6709\u4e00\u7ae0\u4e13\u95e8\u8bb2\u3002\u5176\u5b83\u8bf7\u901a\u8fc7\u738b\u9053\u5b66\u4e60\uff0c\u8fd8\u6709\u59dc\u8001\u5e08 ppt \u4e5f\u6709\u4e00\u4e2a\u5c0f\u603b\u7ed3\u7684\u8868\u683c\u3002

    \u6982\u5ff5 \u5168\u540d \u7279\u70b9 \u4f18\u70b9 UMA uniform memory access \u6bcf\u4e2a\u8282\u70b9\u5230 memory \u7684\u8bbf\u95ee\u65f6\u95f4\u4e00\u81f4 NUMA non-uniform memory access \u6bcf\u4e2a\u8282\u70b9\u5230 memory \u7684\u8bbf\u95ee\u65f6\u95f4\u4e0d\u4e00\u81f4\uff0c\u5230\u81ea\u5df1\u7684\u5feb\uff0c\u5230\u522b\u4eba\u7684\u6162 \u6269\u5c55\u5230\u66f4\u5927\u89c4\u6a21\u4e0a\u7684\u53ef\u6269\u5c55\u6027\u5f3a

    cache \u4e00\u81f4\u6027\u7684\u672f\u8bed

    \u5982\u679c CPU \u6709\u591a\u4e2a\u6838\uff0c\u6216\u8005\u5982\u679c CPU \u662f\u5206\u5e03\u5f0f\u7684\uff0c\u5b83\u4eec\u5171\u7528\u4e00\u4e2a cache\uff0c\u90a3\u4e48\u5c31\u9700\u8981\u4f7f cache \u5bf9\u6240\u6709\u6838/\u8282\u70b9\u7684\u8bfb\u5199\u4fdd\u6301\u4e00\u81f4\u6027\uff0c\u6bd4\u5982\u4e00\u4e2a\u6838/\u8282\u70b9\u5199\u7684\u4e1c\u897f\u5bf9\u5176\u5b83\u6838/\u8282\u70b9\u53ef\u89c1\uff0c\u5176\u5b83\u6838/\u8282\u70b9\u770b\u89c1\u7684\u90fd\u662f\u6700\u65b0\u7684\u3002

    \u672f\u8bed \u4e00\u53e5\u8bdd\u5b9a\u4e49\uff08\u5728 ppt \u4e0a\u53d1\u73b0\u7684\uff0c\u4f46\u662f\u4e2a\u4eba\u611f\u89c9\u4e0d\u592a\u51c6\u786e\uff09 \u5173\u6ce8\u7684\u65b9\u9762\u662f\uff08\u8fd9\u680f from \u8bfe\u672c\u66f4\u51c6\u786e\uff0c\u4f46\u4e0d\u662f\u4e00\u53e5\u8bdd\u5b9a\u4e49\uff09 coherence Memory accesses executed by each processor were kept in order. reads and writes to the same location consistency Memory accesses among different processors were interleaved. reads and writes wrt other memory locations"},{"location":"docs/1-cs/architecture/chap5/#cache_1","title":"\u8fbe\u6210 cache \u4e00\u81f4\u6027\u4e24\u4e2a\u534f\u8bae","text":"

    Note

    \u806a\u660e\u7684\u8bfb\u8005\u5df2\u7ecf\u53d1\u73b0\u6211\u5df2\u7ecf\u4e0d\u60f3\u5199\u4e86

    Snooping\u534f\u8bae

    Note

    \u8bf7\u901a\u8fc7\u81ea\u5df1\u73ed\u8001\u5e08 ppt \u5b66\u4e60\uff1aMOESI \u72b6\u6001\u673a + \u4f8b\u9898\u8868\u683c \u4e24\u4e2a\u56fe

    Directory\u534f\u8bae

    Note

    \u8bf7\u901a\u8fc7\u81ea\u5df1\u73ed\u8001\u5e08 ppt \u5b66\u4e60: \u4f8b\u9898\u8868\u683c \u4e00\u4e2a\u56fe

    "},{"location":"docs/1-cs/compiler/","title":"Compiler","text":"

    :material-circle-edit-outline: \u7ea6 56 \u4e2a\u5b57

    \u662f ZJU \u7f16\u8bd1\u539f\u7406\u7b14\u8bb0\u3002\u4f5c\u4e3a xyx \u4e8b\u65e0\u5de8\u7ec6\u7248\u672c\u7684\u7b14\u8bb0\uff08\u53ef\u5728\u672c\u7ad9\u9996\u9875\u627e\u5230\uff09\u7684\u8865\u5145\uff0c\u6211\u505a\u4e86\u4e00\u4e9b\u6211\u505a\u9898\u65f6\u9700\u901f\u67e5\u7684\u8d44\u6599\u7684\u6574\u7406\u3002

    \u8fdb\u5ea6\uff1a

    "},{"location":"docs/1-cs/compiler/parsing/","title":"Parsing","text":"

    :material-circle-edit-outline: \u7ea6 788 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    \u672c\u9875\u5b8c\u6210\u4e86\u5173\u4e8e LL(1), LR(0), SLR (aka. SLR(1)), LR(1), LALR(1) \u6587\u6cd5\u7684\u4e00\u4e9b\u5e38\u7528\u533a\u522b\u7684\u6574\u7406\u3002\u7531\u4e8e\u4f5c\u8005\u4e5f\u5b66\u5f97\u4e0d\u597d\uff0c\u5982\u679c\u6709\u9519\uff0c\u8bf7\u5411\u6211\u6307\u51fa\uff08\u53ef\u60dc\u8bc4\u8bba\u533a\u6211\u8fd8\u6ca1\u7814\u7a76\u597d\u600e\u6837\u914d\uff0c\u4e00\u5b9a\u5c3d\u5feb\u914d\u4e0a\uff0c\u53ef\u4ee5\u5148\u5176\u5b83\u9014\u5f84\u8054\u7cfb\u6211\uff09\u3002

    \u672c\u9875\u9762\u5199\u4f5c\u65f6\u7684\u7279\u70b9\u662f\u5c3d\u91cf\u7528\u81ea\u7136\u8bed\u8a00\u6765\u63cf\u8ff0\u7279\u70b9\uff0c\u800c\u4e0d\u662f latex \u6570\u5b66\u516c\u5f0f\u548c\u56fe\u50cf\u3002\u539f\u56e0\u662f\u6211\u5728\u5176\u5b83\u8d44\u6599\u641c\u5230\u7684\u8bb2\u89e3\u90fd\u4e8b\u65e0\u5de8\u7ec6\u7528\u5927\u91cf\u516c\u5f0f\u548c\u56fe\u50cf\uff0c\u4f7f\u7406\u89e3\u53d8\u5f97\u5bb9\u6613\uff0c\u4f46\u4e0d\u9002\u5408\u901f\u67e5\u548c\u8bb0\u5fc6\u3002\u76f4\u767d\u4e00\u70b9\u8bf4\u5c31\u662f\u7b14\u8005\u4e0d\u60f3\u770b\u5230\u5b83\u4eec\uff0c\u4e00\u770b\u5c31\u5934\u75bc\u3002\u56e0\u6b64\u4e5f\u9020\u6210\u4e86\u672c\u6587\u6863\u7684\u4e00\u4e2a\u7f3a\u70b9\uff1a\u4e0d\u662f\u4e3a\u521d\u5b66\u8005\u8bbe\u8ba1\u7684\u3002\u521d\u5b66\u8005\u63a8\u8350\u9605\u8bfb xyx \u7684\u7b14\u8bb0\u3002\u505a\u9898\u65f6\u901f\u67e5\u8bb0\u5fc6\u53ef\u4ee5\u770b\u672c\u6587\u6863\u3002

    \u600e\u6837\u5224\u65ad\u6587\u6cd5\u662f...\u4e0d\u662f...

    \u6587\u6cd5 \u5224\u65ad\u662f \u5224\u65ad\u4e0d\u662f LL(1) (\u4e0d\u542b\u5de6\u9012\u5f52 && \u5bf9\u4e8e\u6587\u6cd5\u4e2d\u6bcf\u4e00\u4e2a non-terminal\uff0c\u5b83\u7684\u4ea7\u751f\u5f0f\u7684 SELECT set\uff08\u5373\u5f00\u5934\u7684 terminal \u4e0e\u5f00\u5934\u7684 non-terminal \u7684 FIRST\uff09\u4e24\u4e24\u4e0d\u4ea4\uff0c\u4e14\u4e0d\u80fd\u540c\u65f6\u63a8\u51fa\u7a7a\u4e32) || \u4ea7\u751f\u5f0f lhs \u4e24\u4e24\u4e0d\u76f8\u540c \u542b\u5de6\u9012\u5f52 || \u9047\u5230\u4e0b\u4e00\u4e2a\u8981\u626b\u63cf\u7684 terminal \u8f93\u5165\u65f6\uff0c\u6709\u8d85\u8fc7\u4e00\u79cd derive \u65b9\u6cd5 LR(0) \u6784\u9020\u51fa LR(0) items DFA\uff0c\u5982\u679c\u4e0d\u5b58\u5728 shift-reduce & reduce-reduce conflicts LR(0) items DFA \u5b58\u5728 shift-reduce | reduce-reduce conflicts SLR (aka. SLR(1)) \u6784\u9020\u51fa LR(0) items DFA\uff0c\u9996\u5148\u5176\u4e0d\u5b58\u5728 reduce-reduce \u51b2\u7a81\uff0c\u4e14\u5b58\u5728 shift-reduce \u51b2\u7a81\uff08\u5426\u5219\u5c31\u4e3a LR(0) \u8bed\u6cd5\u4e86\uff09\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u6709 shift-reduce \u51b2\u7a81\u7684\u5730\u65b9\uff0c\u72b6\u6001\u91cc\u9762\u6709\u53ef shift \u89c4\u5219\u4e5f\u6709\u53ef reduce \u89c4\u5219\uff0c\u5982\u679c reduce \u540e\u5f97\u5230\u7684 non-terminal \u7684 FOLLOW set \u4e0e\u53ef shift \u89c4\u5219\u65b0\u7eb3\u5165\u7684 terminal \u90fd\u6ca1\u6709\u4ea4 shift-reduce conflict \u4e2d\u5982\u679c reduce \u540e\u5f97\u5230\u7684 non-terminal \u7684 FOLLOW set \u4e0e\u53ef shift \u89c4\u5219\u65b0\u7eb3\u5165\u7684 terminal \u6709\u4ea4 LR(1) \u6784\u9020\u51fa LR(1) items DFA\uff0c\u5982\u679c\u4e0d\u5b58\u5728 shift-reduce & reduce-reduce conflicts LR(1) items DFA\uff0c\u5982\u679c\u5b58\u5728 shift-reduce | reduce-reduce conflicts LALR(1) \u6784\u9020\u51fa LR(1) items DFA\uff0c\u5982\u679c\u5408\u5e76\u540c\u5fc3\u96c6\u540e\u6ca1\u6709\u4ea7\u751f reduce-reduce conflicts\uff08\u4e00\u5b9a\u4e0d\u4f1a\u4ea7\u751f shift-reduce conflicts\uff0c\u540c\u5fc3\u96c6\u4e0d\u957f\u90a3\u6837\uff09 LR(1) items DFA \u5982\u679c\u5408\u5e76\u540c\u5fc3\u96c6\u540e\u4ea7\u751f\u4e86 reduce-reduce conflicts

    \u5927\u5bb6\u7684 items DFA \u600e\u4e48\u753b...

    \u6587\u6cd5 items DFA LL(1) \u5b83\u6ca1\u6709\u2026 LR(0) \u5148\u753b NFA\uff1a\u6240\u6709 shift \u7684\u60c5\u51b5\u9760\u8bfb\u53d6 non-terminal/terminal \u8f6c\u6362\uff0c\u6240\u6709 reduce \u7684\u60c5\u51b5\u7a7a\u8f6c\u79fb\u3002\u7136\u540e\u753b DFA\uff1a\u628a\u7a7a\u8f6c\u79fb\u5408\u5e76\u3002 SLR (aka. SLR(1)) \u540c\u753b LR(0)\u3002\u53ea\u662f\u591a\u5224\u65ad\u4e00\u4e0b shift-reduce conflict \u7684 FOLLOW \u548c terminal \u91cd\u5408\u60c5\u51b5\uff0c\u4f46\u8fd9\u4e2a\u53ea\u4f53\u73b0\u5728 parse table\uff0c\u4e0d\u5c5e\u4e8e DFA \u5173\u5fc3\u7684\u4e8b\u3002 LR(1) \u5176\u5b83\u6b65\u9aa4\u540c\u753b LR(0)\uff0c\u53ea\u662f\u591a\u4e86\u5728\u6240\u6709 items \u540e\u9762\u7528\u9017\u53f7\u9694\u5f00\u4e00\u4e2a lookahead symbol\u3002lookahead \u7684\u9009\u62e9\u5f88\u50cf\u9009\u62e9\u4e86\u5bf9\u5e94\u4ea7\u751f\u5f0f\uff08\u4e0d\u8bba\u662f lhs/rhs\uff09\u7684 FOLLOW set\uff0c\u5373\u5bf9\u5e94\u4ea7\u751f\u5f0f\u4e4b\u540e\u63a5\u7684 terminal \u662f\u4ec0\u4e48\u3002 LALR(1) \u540c\u753b LR(1)\u3002\u53ea\u662f\u9700\u8981\u5408\u5e76\u6240\u6709\u540c\u5fc3\u96c6\uff0c\u540c\u5fc3\u96c6\u662f\u6307\u4ea7\u751f\u5f0f\u76f8\u540c\u4f46\u662f\u53ea\u6709 lookahead symbol \u4e0d\u540c\u7684\u90a3\u4e9b\u72b6\u6001\u3002

    \u5927\u5bb6\u7684 parse table \u600e\u4e48\u753b...

    \u6587\u6cd5 parse table LL(1) non-terminals, nullable, FIRST, FOLLOW LR(0) states, shift&reduce, goto SLR (aka. SLR(1)) states, shift&reduce, goto LR(1) states, shift&reduce, goto LALR(1) states, shift&reduce, goto"},{"location":"docs/1-cs/database/","title":"DBMS","text":"

    :material-circle-edit-outline: \u7ea6 360 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/database/#whats-this","title":"what's this","text":"

    \u8fd9\u91cc\u662f\u6570\u636e\u5e93\u7cfb\u7edf\u7684\u7406\u8bba\u8bfe\u3002

    content table:

    "},{"location":"docs/1-cs/database/#brief-intro-to-dbms-course","title":"Brief intro to DBMS course","text":"

    \u4e00\u4e9b\u4e0e\u8003\u8bd5\u6709\u5173\u7684\u504f\u95e8\u4e1c\u897f\u3002

    \u4e00\u4e2a\u671f\u672b\u8003\u70b9\uff1a\u6570\u636e\u5e93\u5b66\u79d1\u7684\u56db\u4e2a\u56fe\u7075\u5956

    \u4eba\u7269 \u5e74\u4efd \u8d21\u732e Charles William Bachman 1973 \u6570\u636e\u5e93\u7ba1\u7406\u7cfb\u7edf DBMS \u7684\u5f00\u53d1\u3002\u4f7f\u7528\u5de5\u7a0b\u65b9\u6cd5\u6765\u8bbe\u8ba1\u548c\u5b9e\u73b0\u6570\u636e\u5e93\u7ba1\u7406\u3002 Edgar Frank \"Ted\" Codd 1981 \u5173\u7cfb\u6570\u636e\u5e93\u7406\u8bba\uff0c\u63d0\u51fa\u4e86\u5173\u7cfb\u6a21\u578b\u7684\u6982\u5ff5\uff0c\u8bbe\u8ba1\u4e86\u5173\u7cfb\u6570\u636e\u5e93\u7684\u6570\u5b66\u57fa\u7840\uff0c\u5e76\u53d1\u660e\u4e86SQL\u3002 Raj Reddy 1994 \u5206\u5e03\u5f0f\u6570\u636e\u5e93\u7cfb\u7edf\u3002\u63d0\u51fa\u4e86\u4e00\u79cd\u540d\u4e3aDAI\uff08distributed artificial intelligence\uff09\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u6a21\u578b\u3002\u4f7f\u6570\u636e\u53ef\u4ee5\u5728\u591a\u53f0\u8ba1\u7b97\u673a\u4e4b\u95f4\u5171\u4eab\u548c\u5206\u5e03 Mike Ralph Stonebraker 2014 \u9762\u5411\u5bf9\u8c61\u6570\u636e\u5e93\u7cfb\u7edf\u3002\u63d0\u51fa\u4e86\u4e00\u79cd\u540d\u4e3a O-ODBS (object-oriented database system) \u7684\u65b0\u578b\u6570\u636e\u5e93\u7cfb\u7edf\u67b6\u6784\uff0c\u5c06\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\u548c\u6570\u636e\u5e93\u7cfb\u7edf\u76f8\u7ed3\u5408\u3002\u4f7f\u6570\u636e\u5e93\u7cfb\u7edf\u53ef\u4ee5\u66f4\u597d\u652f\u6301\u590d\u6742\u5e94\u7528\u548c\u66f4\u5927\u89c4\u6a21\u6570\u636e\u3002"},{"location":"docs/1-cs/database/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"

    \u5b8c\u6574\u8d44\u6599

    \u4e13\u9898\u5e16\u5b50

    "},{"location":"docs/1-cs/database/ERmodel/","title":"E-R model","text":"

    :material-circle-edit-outline: \u7ea6 2 \u4e2a\u5b57

    "},{"location":"docs/1-cs/database/SQL/","title":"SQL Grammar","text":"

    :material-circle-edit-outline: \u7ea6 172 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/1-cs/database/SQL/#_1","title":"\u5173\u7cfb\u4ee3\u6570","text":"

    5 \u79cd\u57fa\u672c\u64cd\u4f5c

    \u6269\u5c55\u64cd\u4f5c

    "},{"location":"docs/1-cs/database/SQL/#sql","title":"SQL \u8bed\u6cd5","text":"

    select

    select distinct

    where

    and / or

    order by

    insert to

    update delete

    JOIN \u8bed\u53e5

    \u8fde\u63a5\uff1a\u7528\u4e8e\u628a\u591a\u4e2a\u8868\u7684\u884c\u7ed3\u5408\u8d77\u6765\u3002

    SQL \u4e2d\u51e0\u79cd join \u7684\u7c7b\u578b

    "},{"location":"docs/1-cs/database/design/","title":"Database Design \u6570\u636e\u5e93\u8bbe\u8ba1","text":"

    :material-circle-edit-outline: \u7ea6 3119 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    \u8fd9\u7ae0\u5173\u6ce8\u5982\u4f55\u5728\u78c1\u76d8 disk \u4e0a\u5b9e\u73b0\u4e00\u4e2a database\u3002

    "},{"location":"docs/1-cs/database/design/#storage-structure","title":"Storage Structure \u5b58\u50a8\u7ed3\u6784","text":"

    \u9996\u5148\u9700\u8981\u4ecb\u7ecd storage hierarchy\u3002\u4e00\u4e2a\u4ece\u9876\uff08\u5bb9\u91cf\u6700\u5c0f\u6700\u5feb\u7684\uff09\u5411\u4e0b\uff08\u5bb9\u91cf\u6700\u5927\u6700\u6162\u7684\uff09\u7684\u56fe\u793a\u5982\u4e0b\uff0c

        /\\   Primary storage \u4e3b\u5b58\u50a8\u5668: CPU register \u5bc4\u5b58\u5668, cache \u7f13\u5b58, main memory \u4e3b\u5b58\n   /--\\  Secondary storage \u4e8c\u7ea7\u5b58\u50a8\u5668: flash memory \u95ea\u5b58, magnetic disk \u78c1\u76d8\n  /----\\ Teriary storage \u4e09\u7ea7\u5b58\u50a8\u5668: optical disk \u5149\u76d8, magnetic tape \u78c1\u5e26\n --------\n
    \u5176\u4e2d\u6700\u9876\u5c42 primary storage \u662f volatile\uff08\u6613\u5931\u7684\uff09\uff0c\u610f\u601d\u662f\u5982\u679c\u8ba1\u7b97\u673a\u65ad\u7535\u91cd\u542f\uff0c\u5c31\u4f1a\u4e22\u5931\uff1b\u4e0b\u9762\u4e24\u5c42\u90fd\u662f non-volatile\uff08\u4e0d\u6613\u5931\u7684\uff09\uff0c\u610f\u601d\u662f\u5373\u4f7f\u8ba1\u7b97\u673a\u65ad\u7535\uff0c\u4e5f\u4e0d\u4f1a\u4e22\u5931\u3002

    \u4e0b\u9762\u4f9d\u6b21\u7b80\u5355\u4ecb\u7ecd\u6bcf\u4e2a\u5b58\u50a8\u5668\uff1a

    "},{"location":"docs/1-cs/database/design/#performance-measures-of-disk","title":"Performance Measures of Disk \u78c1\u76d8\u6027\u80fd\u8ba1\u7b97","text":"

    \u6d4b\u91cf\u78c1\u76d8\u7684\u6027\u80fd\u9700\u8981\u4e00\u4e9b\u91cf\u5316\u6307\u6807\uff0c\u901a\u5e38\u6211\u4eec\u8003\u8651\u6570\u636e\u6570\u636e\u8bbf\u95ee\u7684\u7528\u65f6\u548c\u3002

    "},{"location":"docs/1-cs/database/design/#_1","title":"\u78c1\u76d8\u6027\u80fd\u4f18\u5316","text":""},{"location":"docs/1-cs/database/design/#raid","title":"RAID","text":"

    !!! (\u8fd9\u5757\u5728 db \u548c os \u91cc\u90fd\u4e0d\u8003\uff0c\u4f46\u662f\u90fd\u4f1a\u7ecf\u5e38\u63d0\u5230\uff0c\u5f88\u795e\u79d8\uff0c\u6240\u4ee5\u987a\u4fbf\u505a\u4e00\u4e0b\u7b14\u8bb0)

    RAID \u5168\u79f0\u662f redundant arrays of independent disk \u72ec\u7acb\u78c1\u76d8\u5197\u4f59\u9635\u5217\u3002\u5b83\u7684\u6765\u5386\u662f\u56e0\u4e3a\uff0c\u8fc7\u53bb\u7684\u7cfb\u7edf\u8bbe\u8ba1\u8005\u4eec\u8ba4\u4e3a\u4f7f\u7528\u591a\u4e2a\u5c0f\u578b\u3001\u5ec9\u4ef7\u78c1\u76d8\u7ec4\u6210\u7684\u5b58\u50a8\u7cfb\u7edf\u662f\u4e00\u4e2a\u66f4\u7ecf\u6d4e\u9ad8\u6548\u7684\u9009\u9879\uff0c\u6240\u4ee5\u539f\u6765 RAID \u4e2d\u7684 I \u662f inexpensive \u7684\u610f\u601d\u3002\u4f46\u73b0\u5728\u6240\u6709\u78c1\u76d8\u5728\u7269\u7406\u5c3a\u5bf8\u4e0a\u90fd\u5f88\u5c0f\uff0c\u5bb9\u91cf\u66f4\u5927\u7684\u78c1\u76d8\u5b9e\u9645\u4e0a\u5177\u6709\u66f4\u4f4e\u7684\u6bcf\u5146\u5b57\u8282\u6210\u672c\u3002\u5f00\u53d1\u8005\u4f7f\u7528 RAID \u7cfb\u7edf\u73b0\u5728\u4e3b\u8981\u56e0\u5176\u66f4\u9ad8\u7684\u53ef\u9760\u6027\u548c\u6027\u80fd\uff0c\u548c\u7ba1\u7406\u64cd\u4f5c\u7b80\u4fbf\u3002

    !!! TODO

    \u901a\u8fc7\u5e76\u884c\u6765\u52a0\u901f

    "},{"location":"docs/1-cs/database/design/#file-system","title":"File System \u6587\u4ef6\u7cfb\u7edf","text":"

    \u6570\u636e\u5e93\u662f\u5b58\u50a8\u5728\u4e00\u7cfb\u5217\u7684\u6587\u4ef6\u4e2d\u7684\uff0c\u6587\u4ef6\u5185\u90e8\uff0c\u6bcf\u4e2a\u6587\u4ef6\u4e2d\u6709\u4e00\u7cfb\u5217\u7684 records \u8bb0\u5f55\uff0c\u6bcf\u4e2a record \u542b\u6709\u4e00\u7cfb\u5217\u7684 fields \u57df\u3002

    \u5728\u8bbe\u8ba1\u65f6\uff0c\u4e00\u822c\u6709\u4e00\u4e9b\u5047\u8bbe\uff1a\uff081\uff09\u5047\u8bbe\u8bb0\u5f55\u7684\u957f\u5ea6\u662f\u56fa\u5b9a\u7684\uff0c\uff082\uff09\u5047\u8bbe\u6bcf\u4e2a\u6587\u4ef6\u91cc\u53ea\u6709\u4e00\u79cd\u8bb0\u5f55\uff0c\uff083\uff09\u5047\u8bbe\u4e0d\u540c\u7684\u6587\u4ef6\u88ab\u7528\u4e8e\u4e0d\u540c\u7684\u5173\u7cfb\u3002

    "},{"location":"docs/1-cs/database/design/#_2","title":"\u8bb0\u5f55\u7684\u7c7b\u578b","text":"

    \u8bb0\u5f55\u5206\u4e3a

    "},{"location":"docs/1-cs/database/design/#_3","title":"\u8bb0\u5f55\u7684\u6392\u5e03","text":"

    \u4e00\u4e2a\u65b0\u7684\u8bb0\u5f55\u8981\u63d2\u5165\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u6709\u51e0\u79cd\u7b97\u6cd5\u6765\u51b3\u5b9a\u63d2\u5165\u5230\u6587\u4ef6\u7684\u54ea\u4e2a\u4f4d\u7f6e\uff1a

    \u6bcf\u4e2a\u6587\u4ef6\u88ab\u5212\u5206\u4e3a\u56fa\u5b9a\u957f\u5ea6\u7684 blocks\u3002block \u662f\u6570\u636e\u5b58\u53d6\u548c\u7a7a\u95f4\u5206\u914d\u7684\u57fa\u672c\u5355\u4f4d\u3002

    \u4e00\u4e2a block \u5305\u542b\u591a\u6761\u8bb0\u5f55\u3002\u5728\u4f20\u7edf\u7684\u6570\u636e\u5e93\u4e2d\uff0c\u8bb0\u5f55\u7684\u957f\u5ea6\u4e0d\u80fd\u8d85\u8fc7 block\uff0c\u6bcf\u6761\u8bb0\u5f55\u4e00\u5b9a\u90fd\u662f\u5b8c\u6574\u7684\u3002\u8bb0\u5f55\u4e4b\u95f4\u7528\u94fe\u8868\u6765\u8fde\u63a5\u3002

    \u8bb0\u5f55\u5206\u4e3a\u5b9a\u957f\u8bb0\u5f55\u548c\u53d8\u957f\u8bb0\u5f55\u4e24\u79cd\u3002

    slotted page structure \u5206\u69fd\u9875

    \u5178\u578b\u7684\u53d8\u957f\u8bb0\u5f55\u6709\u5982\u4e0b\u7279\u70b9\uff1a

    \u5b58\u50a8\u7f13\u51b2\u533a\u7684\u7ba1\u7406

    "},{"location":"docs/1-cs/database/design/#index","title":"Index \u7d22\u5f15","text":"

    \u6570\u636e\u5e93\u4e2d\u5f15\u5165\u7d22\u5f15\u6982\u5ff5\uff0c\u662f\u4e3a\u4e86\u52a0\u5feb\u67e5\u627e\u901f\u5ea6\u3002

    \u5728\u5f15\u5165\u7d22\u5f15\u7684\u65f6\u5019\uff0c\u9700\u8981\u5173\u6ce8\u7684\u56e0\u7d20\u90fd\u6709\u5982\u4e0b\u51e0\u79cd

    \u4e00\u822c\u6765\u8bf4\uff0c\u952e\u7684\u6392\u5217\u65b9\u5f0f\u5206\u4e3a ordered index \u987a\u5e8f\u7d22\u5f15\u548c hased index \u4e24\u79cd\u3002

    \u800c\u7d22\u5f15\u6307\u5411\u6570\u636e\u7684\u65b9\u5f0f\u53c8\u5206\u4e3a\uff1a

    "},{"location":"docs/1-cs/database/design/#b","title":"B+ \u6811","text":"

    \u4ecb\u7ecd\u5e38\u7528\u7684 B+ \u6811\u6570\u636e\u7ed3\u6784\u3002\u4e0e fds \u4e2d\u5b9a\u4e49\u76f8\u540c\uff0c\u4f46\u662f\u518d\u4ecb\u7ecd\u4e00\u6b21\u3002

    B+ \u6811\u662f\u4e00\u79cd\u5e73\u8861\u7684\uff08\u6bcf\u5c42\u90fd\u662f\u6ee1\u7684\uff09\u591a\u5206\u6811\uff08\u4e0d\u6b62\u4e24\u4e2a\u8282\u70b9\uff09\u3002\u4e00\u4e2a m \u9636\u7684 B+ \u6811\u6ee1\u8db3\u5982\u4e0b\u6761\u4ef6\uff1a

    \u5728\u5b9e\u73b0\u4e2d\uff0cB+ \u6811\u7684\u4e00\u4e2a\u8282\u70b9\u7684\u5927\u5c0f\u548c\u4e00\u4e2a\u78c1\u76d8\u533a\u5757\u4e00\u6837\u5927\uff08\u901a\u5e38\u662f 4 KB\uff09\uff0c\u800c\u7d22\u5f15\u7684\u89c4\u6a21\u4e00\u822c\u5728 100 \u5de6\u53f3\u3002

    B+ Tree Visualization \u662f\u4e00\u4e2a B+ \u6811\u53ef\u89c6\u5316\u7684\u5de5\u5177\u3002

    \u4ecb\u7ecd\u67e5\u8be2\u3001\u63d2\u5165\u548c\u5220\u9664\u64cd\u4f5c\u3002

    \u5f53 B+ \u6811\u4e2d\u7684\u8282\u70b9 TODO \u5177\u4f53\u7684\u6761\u4ef6\u662f\u4ec0\u4e48\uff0c\u6211\u4eec\u8fd9\u91cc\u8bb0\u4f5c\u7834\u574f\u4e86 B+ \u6811\u3001\u5143\u7d20\u8fc7\u591a\u6216\u5143\u7d20\u8fc7\u5c11\uff0c\u5c31\u9700\u8981\u8003\u8651\u66f4\u65b0\u7d22\u5f15\u3002

    \u5206\u522b\u5206\u6790\u51e0\u79cd\u6570\u636e\u64cd\u4f5c\u4e0b\uff0cB+ \u6811\u7684\u6027\u80fd\uff1a

    B+ \u6811\u7684\u76f8\u5173\u8ba1\u7b97

    \u9ad8\u5ea6\u7684\u4f30\u8ba1\uff1a\u53ef\u4ee5\u5206\u6790\u9ad8\u5ea6\u7684\u4e0a\u4e0b\u754c

    size \u5927\u5c0f\u7684\u4f30\u8ba1\uff1a\u4e5f\u662f\u5206\u6790\u9ad8\u5ea6\u7684\u4e0a\u4e0b\u754c

    "},{"location":"docs/1-cs/database/design/#hash","title":"Hash \u7d22\u5f15","text":""},{"location":"docs/1-cs/database/normalforms/","title":"\u6570\u636e\u5e93\u5173\u7cfb\u6a21\u5f0f","text":"

    :material-circle-edit-outline: \u7ea6 1976 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f

    \u4e3a\u4ec0\u4e48\u6211\u4eec\u9700\u8981\u5173\u7cfb\u6a21\u5f0f\uff1f

    \u5728\u8bbe\u8ba1\u6570\u636e\u5e93\u7684\u65f6\u5019\uff0c\u6211\u4eec\u753b\u5b8c E-R \u56fe\uff0c\u8981\u628a\u56fe\u8f6c\u5316\u6210\u8868\u7684\u5f62\u5f0f\u5316\u5b9a\u4e49\uff08\u6bd4\u5982 Student(sid, course, department) \u8fd9\u79cd\u683c\u5f0f\uff09\u3002\u8fd9\u5c31\u9700\u8981\u6211\u4eec\u5bf9\u4e00\u4e9b\u5c5e\u6027\u8fdb\u884c\u8fdb\u4e00\u6b65\u7ea6\u675f\uff0c\u6bd4\u5982\u8981\u5173\u6ce8\u8fd9\u4e9b\u95ee\u9898\uff1a\uff081\uff09\u5728\u4e24\u4e2a\u8868\u91cc\u7684\u952e\u8c01\u51b3\u5b9a\u8c01\uff1f\u8981\u4fdd\u8bc1\u53ea\u6709 candidate key \u7684\u5c5e\u6027\u624d\u80fd\u51b3\u5b9a\u5176\u5b83\u5c5e\u6027\u3002\uff082\uff09\u6709\u4e9b\u8868\u8be5\u5408\u5728\u4e00\u8d77\uff0c\u8fd8\u662f\u62c6\u6210\u591a\u4e2a\u8868\uff1f\u5982\u679c\u8868\u5408\u5f97\u592a\u591a\uff0c\u6709\u4e9b\u4fe1\u606f\u53ef\u80fd\u51fa\u73b0\u592a\u591a\u6b21\uff0c\u4ea7\u751f\u4fe1\u606f\u5197\u4f59\u3001\u63d2\u5165\u5f02\u5e38\u3001\u66f4\u65b0\u56f0\u96be\u3002\uff083\uff09\u6709\u4e9b\u5c5e\u6027\u867d\u7136\u4e0d\u662f\u4e3b\u952e\uff0c\u4f46\u53c8\u51b3\u5b9a\u5176\u5b83\u5173\u7cfb\u7684\u503c\uff0c\u8fd9\u79cd\u60c5\u51b5\u53eb\u505a\u6709\u51fd\u6570\u4f9d\u8d56\u3002

    \u6240\u4ee5\u6211\u4eec\u5f15\u5165\u5173\u7cfb\u4ee3\u6570\uff0c\u6765\u6307\u5bfc\u6211\u4eec\u4ece E-R \u56fe\u5230\u5efa\u7acb\u5f62\u5f0f\u5316\u5b9a\u4e49\u7684\u8fd9\u4e00\u6b65\u9aa4\u3002\u5176\u5b9e\u4e3b\u8981\u7275\u626f\u5230\u7684\u6b65\u9aa4\u5c31\u662f\u5173\u7cfb\u5206\u89e3\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5148\u4ecb\u7ecd\u5206\u89e3\uff0c\u7136\u540e\u4ecb\u7ecd\u5176\u4f9d\u8d56\u7684\u7406\u8bba\u51fd\u6570\u4f9d\u8d56\u7684\u5b9a\u4e49\uff1b\u7136\u540e\u4ecb\u7ecd 6 \u79cd\u6307\u5bfc\u5173\u7cfb\u6a21\u5f0f\u7684\u8303\u5f0f\uff0c\u8fd9\u4e9b\u6bcf\u79cd\u8303\u5f0f\u5c42\u5c42\u9012\u8fdb\uff0c\u662f\u4e00\u4e9b\u5bf9\u6570\u636e\u5e93\u5173\u7cfb\u8d8a\u6765\u8d8a\u4e25\u683c\u7684\u7ea6\u675f\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_2","title":"\u5206\u89e3","text":"

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u662f\u4e0d\u597d\u7684\uff0c\u6211\u4eec\u5e0c\u671b\u628a\u5b83\u5206\u89e3\u6210\u597d\u7684\u5173\u7cfb\u3002

    \u4ecb\u7ecd\u4e00\u4e0b decomposition \u5206\u89e3\u5206\u4e3a\u4e24\u7c7b

    \u8fd9\u4e2a\u5206\u89e3\u7684\u7406\u8bba\uff0c\u662f\u57fa\u4e8e (1) functional dependencies \u51fd\u6570\u4f9d\u8d56 (2) multivalued dependencies \u591a\u503c\u4f9d\u8d56 \u4e24\u4e2a\u7406\u8bba\u7684\u3002

    \u6839\u636e\u5206\u89e3\u7406\u8bba\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u518d\u4e0b\u4e00\u6b65\u8981\u4ecb\u7ecd\u7684\u516d\u4e2a\u8303\u5f0f\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_3","title":"\u51fd\u6570\u4f9d\u8d56","text":"

    \u6982\u5ff5\u533a\u522b

    \u51fd\u6570\u4f9d\u8d56\uff1a

    \u90e8\u5206\u51fd\u6570\u4f9d\u8d56\uff1a\u8bbe X, Y \u662f\u5173\u7cfb R \u7684\u4e24\u4e2a\u5c5e\u6027\u96c6\u5408\uff0c\u5b58\u5728 X->Y, \u82e5 X' \u662f X \u7684\u771f\u5b50\u96c6\uff0c\u5b58\u5728 X\u2018->Y\uff0c\u5219\u79f0 Y \u90e8\u5206\u4f9d\u8d56\u4e8e\u51fd\u6570 X\u3002

    \u4f20\u9012\u51fd\u6570\u4f9d\u8d56\uff1a\u8bbe X, Y, Z \u662f\u5173\u7cfb R \u4e2d\u4e92\u4e0d\u76f8\u540c\u7684\u5c5e\u6027\u96c6\u5408\uff0c

    \u5b8c\u5168\u51fd\u6570\u4f9d\u8d56\uff1a

    \u6211\u770b\u4e0d\u61c2\u3002\u3002\u3002\u3002\u3002\u3002

    \u51fd\u6570\u4f9d\u8d56\u662f\u6765\u81ea\u4e8e\u5e94\u7528\u5c42\u9762\u7684\u89c4\u5b9a\uff08Functional dependencies are constraints on the set of legal relations\uff09\uff0c\u5148\u6709\u51fd\u6570\u4f9d\u8d56\uff0c\u518d\u6709\u6570\u636e\u5e93\u4e2d\u7684\u503c\u3002\u51fd\u6570\u4f9d\u8d56\u8981\u6c42\u4e24\u4e2a\u503c

    \u901a\u8fc7

    \u51fd\u6570\u4f9d\u8d56\u53ef\u4ee5\u88ab\u8bc1\u4f2a\uff08\u5bf9\u4e8e\u5355\u4e2a\uff09\uff0c\u4e0d\u80fd\u88ab\u8bc1\u5b9e\uff08\u5bf9\u4e8e\u6240\u6709\uff09\u3002

    !!! \u672c\u8282\u4ee5\u4e0b latex \u9e1f\u8bed\u5168\u90fd\u4e0d\u8003

    \u5f62\u5f0f\u5316\u7684\u5b9a\u4e49\u91cc\u51fd\u6570\u4f9d\u8d56\u662f\u6307\uff0c\u5728\u4e00\u4e2a\u5173\u7cfb R \u4e2d\uff0c\u5982\u679c\u5c5e\u6027\uff08\u7ec4\uff09Y \u7684\u503c\u662f\u7531\u5c5e\u6027\uff08\u7ec4\uff09X \u7684\u503c\u51b3\u5b9a\u7684\uff0c\u5c31\u79f0 Y \u5bf9 X \u6709\u51fd\u6570\u4f9d\u8d56\u3002\u8003\u8651\u5230\u672c\u8eab\u51fd\u6570\u7684\u5b9a\u4e49\u662f X \u4e2d\u7684\u5143\u7d20\u5728 Y \u4e2d\u6709\u552f\u4e00\u786e\u5b9a\u7684\u503c\uff0c\u90a3\u4e48\u8fd9\u91cc\u7684\u4f9d\u8d56\u5c31\u662f\u6307\uff0c\u4e24\u4e2a\u5143\u7d20\u5982\u679c\u5728 X \u4e2d\u7684\u503c\u4e00\u6837\uff0c\u90a3\u4e48\u5728 Y \u4e2d\u7684\u503c\u4e5f\u4e00\u6837\u3002

    \u5f62\u5f0f\u5316\u5b9a\u4e49\uff1a\u8bbe \\(R(U)\\) \u662f\u5c5e\u6027\u96c6\u5408 \\(U={A_1, A_2, ..., A_n}\\) \u4e0a\u7684\u4e00\u4e2a\u5173\u7cfb\u6a21\u5f0f\uff0cX, Y \u662f U \u4e0a\u7684\u4e24\u4e2a\u5b50\u96c6\uff0c\u82e5\u5bf9 \\(R(U)\\) \u7684\u4efb\u4e00\u4e2a\u53ef\u80fd\u7684\u5173\u7cfb \\(r\\)\uff0c\\(r\\) \u4e2d\u4e0d\u5b58\u5728\u4e24\u4e2a\u5728 X \u4e2d\u5c5e\u6027\u503c\u76f8\u7b49\uff0c\u5728 Y \u4e2d\u5c5e\u6027\u503c\u4e0d\u7b49\u7684\u5143\u7ec4\u3002\u5373\u79f0\u4e3a\u201cX \u51fd\u6570\u51b3\u5b9a Y\u201d\u6216\u201cY \u51fd\u6570\u4f9d\u8d56 X\u201d\uff0c\u8ba1\u4f5c X -> Y\u3002

    Armstrong \u516c\u7406\u7cfb\u7edf\u662f\u63cf\u8ff0\u6570\u636e\u5e93\u4e2d\u7684\u6240\u6709\u51fd\u6570\u4f9d\u8d56\u5173\u7cfb\u7684\u4e00\u7cfb\u5217 references\uff08\u63a8\u7406\u89c4\u5219\uff09\uff0c\u5728 1974 \u5e74\u7531 William W. Armstrong \u8bbe\u8ba1\u3002

    Armstrong \u516c\u7406\u7cfb\u7edf\u6709\u4e09\u5927\u516c\u7406\uff08\u81ea\u53cd\u5f8b\uff0c\u589e\u5e7f\u5f8b\uff0c\u4f20\u9012\u5f8b\uff09\uff0c\u548c\u4e00\u4e9b\u5f15\u7406\u3002

    \u516c\u7406

    !!! \u5bf9\u4e0d\u8d77\uff0c\u6211\u662f\u61d2\u72d7\uff0c\u6211\u4e0d\u60f3\u6572 latex \u5199\u5f62\u5f0f\u5316\u5b9a\u4e49\u4e86\uff0c\u7528\u4eba\u8bdd\u7ed9\u5927\u5bb6\u8bb2\u5427\u3002

    \u8bbe F \u4e3a R(U) \u7684\u4e00\u7ec4\u51fd\u6570\u4f9d\u8d56\uff0c\u8bb0\u4e3a R(U, F)\u3002

    \u5f15\u7406

    !!! \u5b66\u4e0d\u52a8\u4e86\u5149\u62a5\u4e2a\u83dc\u540d\u5427

    \u6b63\u5219\u8986\u76d6

    "},{"location":"docs/1-cs/database/normalforms/#normal-form-6","title":"Normal Form \u8303\u5f0f\uff1a6 \u4e2a\u8303\u5f0f","text":"

    \u63a5\u4e0b\u6765\u6211\u4eec\u4ecb\u7ecd\u6570\u636e\u5e93\u8bbe\u8ba1\u7684\u516d\u5927\u8303\u5f0f\u3002\u5982\u524d\u6587\u6240\u8ff0\uff0c\u516d\u4e2a\u8303\u5f0f\u662f\u5bf9\u6570\u636e\u5e93\u5173\u7cfb\u5c5e\u6027\u5c42\u5c42\u9012\u8fdb\u3001\u8d8a\u6765\u8d8a\u4e25\u683c\u7684\u7ea6\u675f\u3002

    \u7cbe\u7b80\u7248\u5982\u4e0b\uff08\u7528\u4e8e\u8003\u524d\u7a81\u51fb\uff09\uff1a

    \u540d\u79f0 \u4ecb\u7ecd \u8303\u4f8b \u8303\u56f4 \u7b2c\u4e00\u8303\u5f0f 1NF \u5927\uff0c\u9010\u4e2a\u5305\u542b\u4e0b\u65b9\u7684 \u7b2c\u4e8c\u8303\u5f0f 2NF \u7b2c\u4e00\u8303\u5f0f 3NF Buckus-Codd NF \u7b2c\u4e94\u8303\u5f0f 5NF \u7b2c\u516d\u8303\u5f0f 6NF \u5c0f\uff0c\u9010\u4e2a\u88ab\u4e0a\u65b9\u7684\u5305\u542b

    \u63a5\u4e0b\u6765\u662f\u8be6\u7ec6\u4ecb\u7ecd\u3002

    First Normal Form \u7b2c\u4e00\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u6ca1\u6709\u91cd\u590d\u7684\u5217\u3002

    \u7b2c\u4e00\u8303\u5f0f\u7684\u542b\u4e49\uff1aatomicity \u539f\u5b50\u6027\u3002\u5373\u4e0d\u80fd\u518d\u7ee7\u7eed\u62c6\u5206\uff0c\u5c5e\u6027\u4e0d\u80fd\u518d\u5411\u4e0b\u62c6\u5206\u3002\u5f53\u4e00\u4e2a\u5173\u7cfb\u6a21\u5f0f R \u7684\u6240\u6709\u5c5e\u6027\u90fd\u662f atomic \u7684\uff0c\u8fd9\u4e2a\u5173\u7cfb\u6a21\u578b\u5c31\u662f\u7b2c\u4e00\u8303\u5f0f\u3002

    \u6bd4\u5982\uff0cstring \u5e94\u5f53\u88ab\u5f53\u4f5c\u4e0d\u53ef\u5206\u5272\u7684\u3002\u6bd4\u5982 ZJU \u7684\u5b66\u53f7\u7b2c\u4e00\u4f4d\u770b\u672c\u79d1\u751f\u7814\u7a76\u751f\uff0c\u540e\u9762\u4e24\u4f4d\u770b\u5e74\u7ea7\uff0c\u4f46\u8fd9\u4e24\u4e2a\u4fe1\u606f\u5982\u679c\u9700\u8981\u662f\u5e94\u5f53\u88ab\u663e\u793a\u5730\u4fdd\u5b58\u5728\u6570\u636e\u5e93\u4e2d\uff0c\u800c\u4e0d\u662f\u9700\u8981\u7684\u65f6\u5019\u53bb\u5b66\u53f7\u4e2d\u5206\u6790\u67e5\u627e\u7684\u3002\u5982\u679c\u8fd9\u6837\u505a\uff0c\u76f8\u5f53\u4e8e\u628a\u89e3\u6790\u5b57\u7b26\u4e32\u7684\u5de5\u4f5c\u7ed9\u4e86\u5e94\u7528\u7a0b\u5e8f\uff0c\u800c\u5b57\u7b26\u4e32\u67e5\u627e\u662f\u4e00\u4e2a\u6bd4\u6570\u636e\u5e93\u67e5\u8be2\u6162\u7684\u6b65\u9aa4\uff0c\u8fd9\u6837\u7ed3\u679c\u5f88\u4e0d\u597d\u3002

    \u7b2c\u4e00\u8303\u5f0f\u6ca1\u6709\u6d88\u9664\u5197\u4f59\uff0c\u5b83\u6d88\u9664\u7684\u662f\u5217\u91cc\u91cd\u590d\u7684\u4fe1\u606f\u3002\u5b83\u628a\u8868\u683c\u91cc\u5197\u4f59\u7684\u5217\u62c6\u5206\u6210\u4e86\u591a\u4e2a\u884c\u3002

    Second Normal Form \u7b2c\u4e8c\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u5b9e\u4f53\u7684\u5c5e\u6027\u5b8c\u5168\u4f9d\u8d56\u4e8e\u4e3b\u5173\u952e\u5b57\u3002

    \u7b2c\u4e8c\u8303\u5f0f\u662f\u57fa\u4e8e fully functional dependency \u5b8c\u5168\u51fd\u6570\u4f9d\u8d56\u7684\u3002\u610f\u601d\u662f\uff0c\u7b2c\u4e8c\u8303\u5f0f\u7528\u4e8e\u90a3\u4e9b\u6709\u590d\u5408\u952e\u503c\u7684\u5173\u7cfb\uff0c\u6bd4\u5982\u5f53\u4e00\u4e2a\u5173\u7cfb\u7684\u4e3b\u952e\u662f\u591a\u4e2a\u5217\u7684\u590d\u5408\u65f6\u3002

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u672c\u6765\u5c31\u6ca1\u6709\u590d\u5408\u7684\u5c5e\u6027\uff0c\u90a3\u672c\u6765\u5c31\u662f 2NF \u7684\u3002

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u6709\u590d\u5408\u7684\u5c5e\u6027\uff0c\u6bd4\u5982 AB -> C\uff0c\u90a3\u4e48 2NF \u4f1a\u628a AB \u62c6\u5f00\u3002

    TODO\uff1a\u600e\u4e48\u62c6\u5462

    Third Normal Form \u7b2c\u4e09\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u4e0d\u4f9d\u8d56\u4e8e\u5176\u5b83\u975e\u5c5e\u6027\u3002

    A relation is in the third normal form, if there is no transitive dependency for non-prime attributes as well as it is in the second normal form.

    \u5982\u679c\u4e00\u4e2a\u5173\u7cfb\u5728\u7b2c\u4e09\u8303\u5f0f\u91cc\uff0c\u5b83\u5e94\u5f53\u5bf9\u4e8e\u975e\u4e3b\u952e\u5c5e\u6027\u6ca1\u6709\u4f20\u9012\u4f9d\u8d56\uff0c\u5e76\u4e14\u5728\u7b2c\u4e8c\u8303\u5f0f\u91cc\u3002

    Boyce-Cudd Normal Form BCNF\u8303\u5f0f

    \u7b80\u800c\u8a00\u4e4b\uff1a\u6bcf\u4e2a\u4f9d\u8d56\u5173\u7cfb\u4e2d\uff0c\u88ab\u4f9d\u8d56\u7684\u90fd\u662f\u4e3b\u952e

    A relation is in BCNF if it is already 3NF, and if for any functional dependency say P->Q, P should be a super key.

    \u6bd4\u8f83 3NF \u548c BCNF \u7684\u533a\u522b\uff1a

    3NF BCNF \u4e0d\u5e94\u6709 \u5f31 \u5f3a \u51cf\u5c11\u4e86\u5197\u4f59 \u4fdd\u7559\u4e86\u6240\u6709\u51fd\u6570\u4f9d\u8d56 \u53ef\u80fd\u6709\u7684\u51fd\u6570\u4f9d\u8d56\u6ca1\u6709\u88ab\u4fdd\u5b58

    Fifth Normal Form \u7b2c\u4e94\u8303\u5f0f

    Sixth Normal Form \u7b2c\u516d\u8303\u5f0f

    \u505a\u9898\u7684\u65f6\u5019\u4f3c\u4e4e\u53ea\u4f1a\u8ba9\u5199\uff1a\u7b26\u5408 1NF \u7684\uff0c3NF \u7684\uff0cBCNF \u7684\u4e09\u79cd\u5206\u89e3\u3002

    "},{"location":"docs/1-cs/database/normalforms/#_4","title":"\u51fd\u6570\u4f9d\u8d56","text":""},{"location":"docs/1-cs/database/normalforms/#_5","title":"\u95ed\u5305","text":""},{"location":"docs/1-cs/database/normalforms/#_6","title":"\u6700\u5c0f\u8986\u76d6","text":""},{"location":"docs/1-cs/database/normalforms/#references","title":"References","text":""},{"location":"docs/1-cs/database/query/","title":"Query Process \u67e5\u8be2\u5904\u7406","text":"

    :material-circle-edit-outline: \u7ea6 1202 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    \u67e5\u8be2\u5904\u7406\u7684\u57fa\u672c\u6b65\u9aa4\u662f\uff1a\uff081\uff09Parsing and translation \u89e3\u6790\u548c\u7ffb\u8bd1 \uff082\uff09Optimization \u4f18\u5316 \uff083\uff09Evaluation \u8bc4\u4f30\u3002

    \u6211\u4eec\u6700\u5173\u6ce8\u7684\u5176\u5b9e\u662f\u4f18\u5316\u6b65\u9aa4\u3002\u4f18\u5316\u4e00\u6b65\u662f\u57fa\u4e8e\u4ee5\u4e0b\u5047\u8bbe\uff1a\u4e00\u79cd SQL \u67e5\u8be2\u53ef\u80fd\u5bf9\u5e94\u4e86\u591a\u79cd\u7b49\u4ef7\u7684\u5173\u7cfb\u4ee3\u6570\u8868\u8fbe\u5f0f\u3002\u53ef\u4ee5\u901a\u8fc7\u4f30\u8ba1\u6bcf\u79cd\u4f18\u5316\u65b9\u6cd5\u7684 cost \u6765\u8bc4\u4f30\u65b9\u6cd5\u7684\u597d\u574f\u3002\u67e5\u8be2\u4f18\u5316\u4f1a\u9009\u62e9\u6700\u8282\u7ea6\u7684\u65b9\u5f0f\u8fdb\u884c\u67e5\u8be2\u3002

    \u90a3\u4e48\u95ee\u9898\u5c31\u89c4\u7ea6\u6210\u4e86\u4ece\u6240\u6709\u7b49\u4ef7\u7684\u5173\u7cfb\u4ee3\u6570\u8868\u8fbe\u5f0f\u4e2d\uff0c\u9009\u62e9 cost \u6700\u5c0f\u7684\u4e00\u4e2a\u3002\u90a3\u4e48\u95ee\u9898\u5c31\u53d8\u6210\u4e86\u5982\u4f55\u8ba1\u7b97 cost\uff01

    Cost is generally measured as total elapsed time for answering query. Many factors contribute to the time cost: disk access + CPU + network communication. \u4f46\u662f\u524d\u9762\u8ba8\u8bba\u8fc7\uff0c\u4e00\u4e2a\u67e5\u8be2\u88ab\u6267\u884c\u7684\u65f6\u5019\u9700\u8981\u88ab\u52a0\u8f7d\u5230\u78c1\u76d8\u4e0a\uff0c\u800c\u78c1\u76d8\u8bfb\u5199\u975e\u5e38\u6162\uff1bCPU \u65f6\u95f4\u53ef\u4ee5\u5ffd\u7565\u4e0d\u8ba1\uff1b\u53ea\u8981\u4e0d\u662f\u7f51\u7edc\u5e94\u7528\u5c31\u4e0d\u7528\u7ba1\u7f51\u7edc\u4f20\u8f93\u5f00\u9500\u3002\u6240\u4ee5\u76ee\u524d\u6211\u4eec\u5173\u6ce8\u7684 cost \u6700\u5927\u7684\u6765\u6e90\u5c31\u662f\u78c1\u76d8\u8bbf\u95ee\u65f6\u95f4\uff0c\u5176\u4e2d\u5305\u542b seek, block read, block write \u7684\u7528\u65f6\u3002\u56e0\u6b64\u5b9a\u4e49\u4ee5\u4e0b cost \u8ba1\u7b97\u65b9\u6cd5\uff1a

    \u5728 B \u4e2a block \u4e2d\u67e5\u8be2 S \u6b21\u7684\u65f6\u95f4 = B * \u8f6c\u79fb\u5230\u4e00\u4e2a block \u7684\u65f6\u95f4 + S * \u4e00\u6b21\u67e5\u8be2\u7684\u65f6\u95f4\u3002

    \u800c\u67e5\u8be2\u4e2d\uff0c\u8bfb\u5199\u8017\u65f6\u66f4\u591a\uff0c\u5176\u4e2d\u5199\u6bd4\u8bfb\u66f4\u8017\u65f6\u3002\u6240\u4ee5\u6211\u4eec\u5e0c\u671b\u67e5\u627e\u548c\u67e5\u8be2\u7684\u65f6\u95f4\u90fd\u66f4\u5c11\u3002

    \uff08TODO\uff1a\u8fd9\u91cc\u8ba1\u7b97\u7684\u65f6\u5019\u8981\u57fa\u4e8e\u4e24\u4e2a\u5047\u8bbe\uff0ccost \u4f9d\u8d56\u4e8e\u4e3b\u5b58\u4e2d\u7f13\u51b2\u533a\u7684\u5927\u5c0f\uff0c\u66f4\u591a\u7684\u5185\u5b58\u53ef\u4ee5\u51cf\u5c11 disk access\uff1b\u53e6\u5916\u901a\u5e38\u8003\u8651\u6700\u574f\u7684\u60c5\u51b5\uff0c\u5373\u4e3b\u5b58\u53ea\u63d0\u4f9b\u6700\u5c11\u7684\u5185\u5b58\u6765\u5b8c\u6210\u67e5\u8be2\u5de5\u4f5c\uff09

    \u63a5\u4e0b\u6765\u6765\u4f30\u8ba1\u5173\u7cfb\u4ee3\u6570\u5404\u4e2a\u64cd\u4f5c\u7684 cost

    Select \u9009\u62e9\u7684 cost \u8ba1\u7b97

    \u6709\u4e09\u79cd select \u7684\u7b97\u6cd5

    Sort \u6392\u5e8f\u7684 cost \u4f30\u8ba1

    sort \u64cd\u4f5c\u4e00\u822c\u4f7f\u7528\u5916\u90e8\u5f52\u5e76\u6392\u5e8f\u3002\u5bf9\u4e8e\u4e00\u4e2a\u5927\u5c0f\u4e3a M \u7684\u5185\u5b58\uff0cb_r \u8868\u793a block \u7684\u6570\u91cf\u3002sort \u5206\u4e3a\u4ee5\u4e0b\u4e24\u4e2a\u6b65\u9aa4\uff1a(1) create sorted runs\uff0c\u6570\u636e\u4ece\u78c1\u76d8\u8bfb\u5165\u5185\u5b58\u4e2d\uff0c\u56e0\u4e3a\u5185\u5b58\u5927\u5c0f\u662f M\uff0c\u6bcf\u6b21\u80fd\u5904\u7406 M \u4e2a\u6570\u636e\u9879 (2) merge the runs\u3002

    \u9700\u8981\u7684 merge pass \u7684\u603b\u6570 \\(\\lceil log_{M-1}(b_r/M) \\rceil\\)\u3002

    \u521b\u5efa\u548c\u6bcf\u6b21 run \u7684\u8fc7\u7a0b\u4e2d disk access \u7684\u6570\u91cf 2br\u3002

    \u5916\u90e8\u6392\u5e8f\u4e2d\u603b\u7684 disk access \u6b21\u6570 \\((2\\lceil log_{M-1}(b_r/M) \\rceil+1)b_r\\)

    Join \u8fde\u63a5\u7684 cost \u4f30\u8ba1

    \u4ee5\u4e0b\u6709\u51e0\u79cd\u5b9e\u73b0 join \u7684\u7b97\u6cd5 (1) nested-loop join (2) block nested-loop join (3) indexed nested-loop join (4) merge-join (5) hash-join\u3002

    \u5bf9\u6bd4\uff1a

    Nested-loop Join: Simple but inefficient for large datasets due to \ud835\udc42 ( \u2223 \ud835\udc45 \u2223 \u00d7 \u2223 \ud835\udc46 \u2223 ) O(\u2223R\u2223\u00d7\u2223S\u2223) complexity. Block Nested-loop Join: Optimized version of nested-loop join that processes blocks to reduce I/O operations. Merge Join: Efficient for sorted relations, with complexity dominated by the sort operations. Hash Join: Very efficient for large datasets, especially when one relation can fit into memory, with \ud835\udc42 ( \u2223 \ud835\udc45 \u2223 + \u2223 \ud835\udc46 \u2223 ) O(\u2223R\u2223+\u2223S\u2223) complexity assuming good hashing.

    Duplicated Deletion \u91cd\u590d\u6d88\u9664

    \u6392\u5e8f\u548c\u6295\u5f71\u53ef\u4ee5\u6d88\u9664\u91cd\u590d

    \u8003\u5f97\u4e0d\u591a\u3002

    Aggregation \u805a\u5408

    \u4e5f\u53ef\u4ee5\u7528\u6392\u5e8f\u6216\u6295\u5f71\u6765\u505a\u3002

    "},{"location":"docs/1-cs/database/query/#query-optimization","title":"Query Optimization \u67e5\u8be2\u4f18\u5316","text":"

    \u5bf9\u7ed9\u5b9a\u67e5\u8be2\uff0c\u4f18\u5316\u7684\u65b9\u6cd5\u6709\uff1a

    !!! TODO \u4e0b\u9762\u7684\u51e0\u4e2a\u4e13\u9898\u7a76\u7adf\u662f\u4ec0\u4e48\u903b\u8f91\u6392\u7684

    "},{"location":"docs/1-cs/database/query/#equivalent-expressions","title":"Equivalent expressions","text":""},{"location":"docs/1-cs/database/query/#statistics-for-cost-estimation","title":"Statistics for Cost Estimation","text":""},{"location":"docs/1-cs/database/transaction/","title":"Transaction \u4e8b\u52a1","text":"

    :material-circle-edit-outline: \u7ea6 1318 \u4e2a\u5b57 :fontawesome-solid-code: 7 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/1-cs/database/transaction/#_1","title":"\u7b80\u4ecb","text":"

    \u4e8b\u52a1\u662f\u7a0b\u5e8f\u6267\u884c\u7684\u57fa\u672c\u5355\u4f4d\uff0c\u4f1a\u5f15\u8d77\u4e00\u4e9b\u6570\u636e\u9879\u7684\u66f4\u65b0\u3002\u6211\u4eec\u5b9a\u4e49\u4e8b\u52a1\u6709\u4ee5\u4e0b\u56db\u4e2a\u57fa\u672c\u5c5e\u6027\uff1a

    \u4e3a\u4e86\u4fdd\u8bc1\u4e8b\u52a1\u7684\u8fd9\u4e9b\u5c5e\u6027\uff0c\u4e00\u822c\u4e3b\u8981\u9700\u8981\u8003\u8651\u4e24\u4e2a\u95ee\u9898\uff1a

    \u4e8e\u662f\uff0c\u6211\u4eec\u8003\u8651\u628a\u4e00\u4e2a\u4e8b\u52a1\u5206\u4e3a\u591a\u4e2a\u72b6\u6001\u6765\u5b8c\u6210\u3002\u4e00\u4e2a\u4e8b\u52a1\u6709\u4e94\u79cd\u72b6\u6001\uff1a

    \u4e00\u4e2a\u8f6c\u5316\u7684\u72b6\u6001\u56fe\u5982\u4e0b

    graph LR\n\nA[[active]] --> P[[Partially commited]]\nP --(single step)--> C[[commited]]\nA --> F[[failed]]\nP --> F\nF --(single step)--> B[[aborted]]\n

    \u6211\u4eec\u4e3b\u8981\u9700\u8981\u4fdd\u8bc1 partially commited \u5230 commited\uff0c\u548c failed \u5230 abort\uff0c\u8fd9\u4e24\u6b65\u90fd\u662f\u539f\u5b50\u6027\u7684\u3002

    "},{"location":"docs/1-cs/database/transaction/#_2","title":"\u8c03\u5ea6","text":"

    \u8fd9\u6837\u5c31\u6d89\u53ca\u5230\u8c03\u5ea6\u6982\u5ff5\u3002Schedules \u8c03\u5ea6\u662f\u4e00\u7cfb\u5217\u7528\u4e8e\u6307\u5b9a\u5e76\u53d1\u4e8b\u52a1\u6267\u884c\u987a\u5e8f\u7684\u6307\u4ee4\u3002\u5b83\u9700\u8981\uff081\uff09\u5305\u542b\u4e8b\u52a1\u4e2d\u7684\u6240\u6709\u6307\u4ee4\uff0c\uff082\uff09\u4fdd\u8bc1\u5355\u4e2a\u4e8b\u52a1\u4e2d\u7684\u6307\u4ee4\u7684\u76f8\u5bf9\u987a\u5e8f\u3002

    \u5982\u679c\u4e8b\u52a1\u662f\u826f\u6784\u7684\u4e14\u662f\u4e24\u9636\u6bb5\u7684\uff0c\u90a3\u4e48\u4efb\u4f55\u4e00\u4e2a\u5408\u6cd5\u7684\u8c03\u5ea6\u90fd\u662f\u9694\u79bb\u7684 \u5177\u4f53\u7684\u6570\u5b66\u63a8\u5230\u8fc7\u7a0b\u53ef\u4ee5\u53c2\u7167<<\u4e8b\u52a1\u5904\u7406:\u6982\u5ff5\u4e0e\u6280\u672f>>\u8fd9\u672c\u4e66\u76847.5.8.2\u8282\u6b64\u4e66\u4e43\u662f\u5173\u4e8e\u6570\u636e\u5e93\u4e8b\u52a1\u7684\u5723\u7ecf\uff0c\u65e0\u9700\u89e3\u91ca(\u4e2d\u6587\u7ffb\u8bd1\u867d\u7136\u6666\u6da9\uff0c\u4e5f\u80fd\u575a\u6301\u8bfb\u4e0b\u53bb,\u5f3a\u70c8\u63a8\u8350

    "},{"location":"docs/1-cs/database/transaction/#_3","title":"\u4e32\u884c","text":"

    \u5982\u679c\u4e00\u4e2a\u8c03\u5ea6\u4e0e\u4e00\u4e2a\u4e32\u884c\u8c03\u5ea6\uff08serial\uff09\u7b49\u4ef7\uff0c\u90a3\u4e48\u79f0\u8fd9\u4e2a\u8c03\u5ea6\u662f serializable \u53ef\u4e32\u884c\u5316\u7684\u3002

    \u53ef\u4e32\u884c\u5316\u5efa\u7acb\u5728\u4e00\u4e2a\u5047\u8bbe\u4e0a\uff1a\u4e8b\u52a1\u4e0d\u4f1a\u7834\u574f\u6570\u636e\u5e93\u7684\u4e00\u81f4\u6027\uff0c\u53ea\u8003\u8651\u6709\u8bfb\u5199\u4e24\u79cd\u64cd\u4f5c\u3002

    \u6211\u4eec\u8bf4\u4e00\u4e2a\u8c03\u5ea6\u662f conflict serializable \u51b2\u7a81\u53ef\u4e32\u884c\u5316\u7684\uff0c\u5f53\uff1a

    "},{"location":"docs/1-cs/database/transaction/#-","title":"-","text":""},{"location":"docs/1-cs/database/transaction/#_4","title":"\u5e76\u53d1\u5904\u7406","text":"

    \u540c\u65f6\u6267\u884c\u591a\u4e2a\u4e8b\u52a1\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8fd0\u884c\u7684\u6548\u7387\uff0c\u51cf\u5c11\u5e73\u5747\u6267\u884c\u65f6\u95f4\u3002

    \u5e76\u53d1\u63a7\u5236\u7684\u5904\u7406\u673a\u5236\u662f\uff0c\u8ba9\u5e76\u53d1\u7684\u4e8b\u52a1\u72ec\u7acb\u8fdb\u884c\uff0c\u63a7\u5236\u5e76\u53d1\u7684\u4e8b\u52a1\u4e4b\u95f4\u7684\u4ea4\u6d41\u3002

    "},{"location":"docs/1-cs/database/transaction/#_5","title":"\u6545\u969c\u6062\u590d","text":"

    \u6545\u969c\u7684\u79cd\u7c7b\u6709\uff1a

    checkpoint

    Recovery algorithms are techniques to ensure database consistency and transaction atomicity and durability despite failures. \u6545\u969c\u6062\u590d\u7b97\u6cd5\u5c31\u662f\u4fdd\u969c\u6570\u636e\u5e93 ACD\uff08\u4e0d\u77e5\u9053\u4e3a\u4ec0\u4e48\u6ca1\u6709 I\uff09\u7279\u6027\u7684\u65b9\u6cd5\u3002

    \u6545\u969c\u6062\u590d\u7b97\u6cd5\u6709\u4e24\u4e2a\u90e8\u5206\uff1a

    \u6545\u969c\u6062\u590d\u7b97\u6cd5\u5177\u6709 Idempotent(\u5e42\u7b49\u6027): An recovery algorithm is said to be idempotent if executing it several times gives the same result as executing it once. \u610f\u601d\u662f\u7b97\u6cd5\u6062\u590d\u591a\u6b21\u7684\u6548\u679c\u662f\u4e00\u6837\u7684\uff0c\u56e0\u4e3a\u6062\u590d\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u4e5f\u53d1\u751f crash\u3002

    Log-based Recovery \u57fa\u4e8e\u65e5\u5fd7\u7684\u6062\u590d\u6cd5

    log records \u65e5\u5fd7\u8bb0\u5f55\uff1a

    \u65e5\u5fd7\u8bb0\u5f55\u662f\u8bb0\u5f55\u5728 stable storage\uff08\u7a33\u5b9a\u5b58\u50a8\u5668\uff09\u4e0a\u7684\uff0c\u4e00\u7cfb\u5217\u8bb0\u5f55\u6570\u636e\u5e93\u600e\u6837\u88ab\u6210\u529f\u4fee\u6539\u7684\u4fe1\u606f\u3002log \u7531\u4e00\u4e32 log records \u7ec4\u6210\u3002\u5b83\u6709\u4ee5\u4e0b\u51e0\u79cd\u683c\u5f0f

    checkpoint \u4e4b\u95f4\u7684\u95f4\u9694\u5e94\u5f53\u901a\u8fc7\u65e5\u5fd7\u91cf\u6765\u786e\u5b9a\u3002

    \u4e24\u79cd\u7b56\u7565 - Redo:

    In the redo phase, the system replays updates of all transactions by scaning the log forward from the last checkpoint. The log records that are replayed include log records for transactions that were rolled back befored system crash, and those that had not committed when the system crash occurred. \n\u5728 redo \u9636\u6bb5\u91cc\uff0c\u7cfb\u7edf\u6839\u636e\u91cd\u65b0\u626b\u63cf\u4e0a\u4e00\u6b21 checkpoint \u4e4b\u540e\u7684\u6240\u6709\u8bb0\u5f55\uff0c\u91cd\u65b0\u6267\u884c\u4e0a\u4e00\u6b21 checkpoint \u4e4b\u540e\u7684\u6240\u6709 transaction\u3002\u8fd9\u91cc\u7684 log \u8bb0\u5f55\u5305\u62ec\u5728 crash \u4e4b\u524d\u6b63\u5728\u56de\u6eda\u7684\u90a3\u4e9b\u8bb0\u5f55\uff0c\u4e5f\u5305\u62ec crash \u65f6\u8fd8\u6ca1\u6709\u63d0\u4ea4\u7684\u90a3\u4e9b\u8bb0\u5f55\u3002Redo \u9636\u6bb5\u4e5f\u4f1a\u5224\u65ad\u6240\u6709 transaction \u662f\u5426\u5b8c\u6210\u4e86\uff0c\u662f\u5426\u9700\u8981 roll back\u3002\u6ca1\u5b8c\u6210\u7684 transaction \u4f1a\u88ab\u6807\u8bb0\u4e3a\u6216\u8005 \\<Ti abort\\> \u6216\u8005 \\<Ti commit\\> \u7684\u6807\u8bb0\u3002\u5177\u4f53\u6765\u8bf4\u6267\u884c\u7684\u6b65\u9aa4\u6709\u4e0b\u9762\u51e0\u6761\uff1a\n\n-\n
    "},{"location":"docs/1-cs/database/xml/","title":"XML \u6587\u4ef6","text":"

    :material-circle-edit-outline: \u7ea6 14 \u4e2a\u5b57

    "},{"location":"docs/1-cs/database/xml/#_1","title":"\u5b9a\u4e49\u548c\u57fa\u672c\u7ed3\u6784","text":""},{"location":"docs/1-cs/database/xml/#document-schema","title":"Document Schema","text":""},{"location":"docs/1-cs/database/xml/#_2","title":"\u67e5\u8be2","text":""},{"location":"docs/1-cs/oop/course/","title":"Courses \u542c\u8bfe","text":"

    :material-circle-edit-outline: \u7ea6 1567 \u4e2a\u5b57 :fontawesome-solid-code: 91 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f

    "},{"location":"docs/1-cs/oop/course/#cs106bcs106l","title":"\u5173\u4e8eCS106B\u548cCS106L","text":"

    CS106B\u504f\u7b80\u5355\uff0c\u76f8\u5f53\u4e8eZJU\u7684\u6570\u636e\u7ed3\u6784+C++\u7684STL\u7528\u6cd5\u4e00\u5757\u8bb2\uff0c\u53e6\u5916\u518d\u8bb2\u4e00\u4e9bFDS\u7684\u7b97\u6cd5\u3002 CS106L\u662f\u4e13\u95e8\u8bb2C++\u8fdb\u9636\u7279\u6027\u7684\u3002

    \u56e0\u4e3a\u5728\u542cCS106B\u4e4b\u524d\u5b66\u8fc7FDS\uff0cCS106B\u82b1\u4e00\u5929\u901f\u901a\u4e86\u4e00\u4e0b\uff0c\u91cd\u590d\u5185\u5bb9\u6709\u70b9\u591a\uff0c\u622a\u4e0b\u4e86\u4e00\u5e45\u56fe\u3002

    CS106L\u63d0\u4f9b\u7684C++\u5b66\u4e60\u8def\u7ebf\u56fe

    "},{"location":"docs/1-cs/oop/course/#zju","title":"ZJU\u8bfe\u7a0b","text":""},{"location":"docs/1-cs/oop/course/#_1","title":"\u8bfe\u7a0b\u53c2\u8003\u8d44\u6599","text":"

    CPP Reference Standard C++ CppCon

    "},{"location":"docs/1-cs/oop/course/#_2","title":"\u4e0a\u8bfe\u5fc3\u5f97","text":"

    \u6211\u8ddf\u7684\u662fcx\u8001\u5e08\u7684\u73ed\uff0c\u5e94\u8be5\u662f\u6559\u5f97\u6700\u597d\u7684\u4e00\u6863orz \u4f46\u662f\u4e0a\u8bfe\u5185\u5bb9\u4ecd\u4e0d\u80fd\u8986\u76d6\u4f5c\u4e1a\u548c\u671f\u672b\u7684\u5185\u5bb9\uff0c\u89c9\u5f97\u542c\u8bfe\u5185\u5bb9\u53ea\u80fd\u8d77\u5230\u4e00\u4e2a\u9aa8\u67b6\u4f5c\u7528\uff0c\u8bfe\u540e\u9700\u8981\u82b1\u4e0a\u8bfe2\u81f33\u500d\u7684\u65f6\u95f4\u81ea\u5b66\u81ea\u5df1\u6574\u7406\u7b14\u8bb0\uff0c\u591a\u8bfb\u591a\u5199\u4ee3\u7801\uff0c\u4e0d\u7136\u671f\u672b\u4f1a\u9047\u5230\u6ca1\u89c1\u8fc7\u7684\u7279\u6027\uff0c\u4f1a\u6709\u70b9\u60e8orz\uff08\u50cf\u6211\u4e00\u6837\uff09

    "},{"location":"docs/1-cs/oop/course/#_3","title":"\u9762\u5411\u5bf9\u8c61\u56db\u5927\u7279\u6027","text":""},{"location":"docs/1-cs/oop/course/#_4","title":"\u7c7b\u548c\u5bf9\u8c61/\u6784\u9020\u51fd\u6570\u548c\u6790\u6784\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#class-struct","title":"class \u4e0e struct \u7684\u6bd4\u8f83","text":""},{"location":"docs/1-cs/oop/course/#_5","title":"\u7c7b\u7684\u7ed3\u6784\uff1a\u6570\u636e\u6210\u5458\u548c\u6210\u5458\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#_6","title":"\u7c7b\u7684\u58f0\u660e\u683c\u5f0f","text":"
    class Name\n{\n    public:\n        public_data;\n        public_functions;\n    protected:\n        protected_data;\n        protected_functions;\n    private:\n        private_data;\n        private_functions;\n}\n
    "},{"location":"docs/1-cs/oop/course/#_7","title":"\u4e60\u60ef","text":""},{"location":"docs/1-cs/oop/course/#_8","title":"\u7c7b\u5916\u5b9a\u4e49","text":"

    \u8fd4\u56de\u7c7b\u578b \u7c7b\u540d::\u6210\u5458\u51fd\u6570\u540d\uff08\u53c2\u6570\u8868\uff09 { // \u51fd\u6570\u4f53 }

    "},{"location":"docs/1-cs/oop/course/#_9","title":"\u5185\u8054\u51fd\u6570\u548c\u5916\u8054\u51fd\u6570","text":""},{"location":"docs/1-cs/oop/course/#_10","title":"\u5bf9\u8c61","text":"

    \u53ef\u4ee5\u628a\u76f8\u540c\u6570\u636e\u7ed3\u6784\u548c\u76f8\u540c\u64cd\u4f5c\u96c6\u7684\u5bf9\u8c61\u770b\u4f5c\u5c5e\u4e8e\u540c\u4e00\u7c7b\u3002\u5bf9\u8c61\u662f\u7c7b\u7684\u5b9e\u4f8b\u3002

    "},{"location":"docs/1-cs/oop/course/#_11","title":"\u5bf9\u8c61\u7684\u5b9a\u4e49","text":""},{"location":"docs/1-cs/oop/course/#_12","title":"\u5bf9\u8c61\u4e2d\u6210\u5458\u7684\u8bbf\u95ee","text":"

    \u5bf9\u8c61\u540d.\u6570\u636e\u6210\u5458\u540d\uff08\u662f \u5bf9\u8c61\u540d.\u7c7b\u540d::\u6210\u5458\u540d \u7684\u7f29\u5199\uff09 \u5bf9\u8c61\u540d.\u6210\u5458\u51fd\u6570\u540d\uff08\u53c2\u6570\u8868\uff09 

    class Sample\n{\npublic:\nint k;\nint geti(){return i;}\nint getj(){return j;}\nint getk(){return k;}\nprivate:\nint i;\nprotected:\nint j;\n};\nint main()\n{\nSample a;\na.i;        // \u975e\u6cd5\na.j:        // \u975e\u6cd5\na.k;        // \u5408\u6cd5\n}\n

    "},{"location":"docs/1-cs/oop/course/#_13","title":"\u7c7b\u7684\u4f5c\u7528\u57df","text":""},{"location":"docs/1-cs/oop/course/#_14","title":"\u6784\u9020\u51fd\u6570\u4e0e\u6790\u6784\u51fd\u6570","text":"

    \u7c7b\u7684\u6784\u9020\u51fd\u6570\u662f\u7c7b\u7684\u4e00\u4e2a\u7279\u6b8a\u6210\u5458\u51fd\u6570\uff0c\u6ca1\u6709\u8fd4\u56de\u7c7b\u578b\uff08\u4e0d\u662fvoid\uff09\uff0c\u53ef\u4ee5\u6709\u53c2\u6570\uff0c\u51fd\u6570\u540d\u548c\u7c7b\u540d\u4e00\u6837\u3002\u5f53\u521b\u5efa\u7c7b\u7684\u4e00\u4e2a\u65b0\u5bf9\u8c61\u65f6\uff0c\u81ea\u52a8\u8c03\u7528\u6784\u9020\u51fd\u6570\uff0c\u5b8c\u6210\u521d\u59cb\u5316\u5de5\u4f5c\u3002

    "},{"location":"docs/1-cs/oop/course/#namespace","title":"Namespace","text":""},{"location":"docs/1-cs/oop/course/#namespace_1","title":"\u4ec0\u4e48\u662fnamespace\uff1f","text":"

    \u662f\u5355\u4e00\u7684\u5168\u5c40\u540d\u5b57\u7a7a\u95f4\u3002\u9632\u6b62\u5728\u4e00\u4e2a\u7a7a\u95f4\u4e2d\u76f8\u540c\u7684\u540d\u5b57\u5f15\u8d77\u51b2\u7a81\u3002 \u4f8b\u5b50\uff1a 

    namespace myown1\n{\nstring user_name = \"myown1\";\n}\nnamespace myown2\n{\nstring user_name = \"myown2\";\n}\nint main()\n{\n// using namespace myown1; \ncout << \"\\\\n\" << \"Hello, \"\n<< myown1::user_name\n<< \"...and goodbye!\\\\n\"\ncout << \"\\\\n\" << \"Hello, \"\n<< myown2::user_name\n<< \"...and goodbye!\\\\n\"\nreturn 0;\n}\n

    \u5173\u952e\u8bcdusing\u5c06\u4e00\u4e2a\u540d\u5b57\u7a7a\u95f4\u53d8\u4e3a\u53ef\u89c1\uff0c\u4e0d\u4f1a\u8986\u76d6\u5f53\u524d\u7684namespace\u3002

    "},{"location":"docs/1-cs/oop/course/#_15","title":"\u7ee7\u627f\u4e0e\u6d3e\u751f\u7c7b","text":" \u76ee\u7684 \u4ee3\u7801\u7684\u91cd\u7528\u548c\u4ee3\u7801\u7684\u6269\u5145 \u7ee7\u627f\u79cd\u7c7b \u5355\u7ee7\u627f/\u591a\u7ee7\u627f \u7ee7\u627f\u5185\u5bb9 \u9664\u6784\u9020\u51fd\u6570/\u6790\u6784\u51fd\u6570/\u79c1\u6709\u6210\u5458\u5916\u7684\u6240\u6709\u6210\u5458"},{"location":"docs/1-cs/oop/course/#_16","title":"\u7ee7\u627f\u7684\u8bbf\u95ee\u63a7\u5236","text":"

    \u6d3e\u751f\u7c7b\u7ee7\u627f\u4e86\u57fa\u7c7b\u4e2d\u9664\u6784\u9020\u51fd\u6570\u548c\u6790\u6784\u51fd\u6570\u4e4b\u5916\u7684\u6240\u6709\u6210\u5458\u3002\u6d3e\u751f\u7c7b\u7684\u6210\u5458\u5305\u62ec\uff1a - \u7ee7\u627f\u57fa\u7c7b\u7684\u6210\u5458 - \u6d3e\u751f\u7c7b\u5b9a\u4e49\u65f6\u58f0\u660e\u7684\u6210\u5458

    \u4ece\u5df2\u6709\u7c7b\u6d3e\u751f\u51fa\u65b0\u7c7b\u65f6\uff0c\u53ef\u4ee5\u5728\u6d3e\u751f\u7c7b\u5185\u5b8c\u6210\u4ee5\u4e0b\u51e0\u79cd\u529f\u80fd\uff1a - \u589e\u52a0\u65b0\u7684\u6570\u636e\u6210\u5458 - \u589e\u52a0\u65b0\u7684\u6210\u5458\u51fd\u6570 - \u91cd\u65b0\u5b9a\u4e49\u57fa\u7c7b\u4e2d\u5df2\u6709\u7684\u6210\u5458\u51fd\u6570 - \u53ef\u4ee5\u6539\u53d8\u73b0\u6709\u6210\u5458\u7684\u5c5e\u6027

    \u58f0\u660e\u4e00\u4e2a\u6d3e\u751f\u7c7b\u7684\u4e00\u822c\u683c\u5f0f 

    class \u6d3e\u751f\u7c7b\u540d:\u7ee7\u627f\u65b9\u5f0f \u57fa\u7c7b\u540d\n{\n// \u6d3e\u751f\u7c7b\u65b0\u589e\u7684\u6570\u636e\u6210\u5458\u548c\u6210\u5458\u51fd\u6570\n};\n

    \u4e09\u79cd\u7ee7\u627f\u65b9\u5f0f 

    class employee: public person\n{};\n// default\nclass employee: private person\n{};\nclass employee: protected person\n{};\n

    \u57fa\u7c7b\u6210\u5458\u5728\u6d3e\u751f\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027

    \u5728\u57fa\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027 \u7ee7\u627f\u65b9\u5f0f \u5728\u6d3e\u751f\u7c7b\u4e2d\u7684\u8bbf\u95ee\u5c5e\u6027 \u89e3\u91ca private public inaccessible \u57fa\u7c7b\u4e2dprivate\u7684\u5bf9\u8c61\u5728\u7c7b\u5916\u5f53\u7136\u4e0d\u53ef\u8bbf\u95ee private private inaccessible private protected inaccessible public public public \u57fa\u7c7b\u4e0d\u7ba1 public private private public protected protected protected public protected \u6743\u9650\u4f1a\u88ab\u7ee7\u627f\u65b9\u5f0f\u7f29\u5c0f\u800c\u4e0d\u4f1a\u653e\u5927 protected private private protected protected protected

    \u6d3e\u751f\u7c7b\u5bf9\u57fa\u7c7b\u7684\u8bbf\u95ee\u89c4\u5219 - \u5185\u90e8\u8bbf\u95ee\uff1a\u7531\u6d3e\u751f\u7c7b\u4e2d\u65b0\u589e\u6210\u5458\u5bf9\u57fa\u7c7b\u7ee7\u627f\u6765\u7684\u6210\u5458\u7684\u8bbf\u95ee\u3002 - \u5bf9\u8c61\u8bbf\u95ee\uff1a\u5728\u6d3e\u751f\u7c7b\u5916\u90e8\uff0c\u901a\u8fc7\u6d3e\u751f\u7c7b\u7684\u5bf9\u8c61\u5bf9\u4ece\u57fa\u7c7b\u7ee7\u627f\u6765\u7684\u6210\u5458\u7684\u8bbf\u95ee\u3002

    \u57fa\u7c7b\u6210\u5458 private\u6210\u5458 public\u6210\u5458 protected\u6210\u5458 \u5185\u90e8\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u53ef\u8bbf\u95ee \u53ef\u8bbf\u95ee \u5bf9\u8c61\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee \u4e0d\u53ef\u8bbf\u95ee

    \u79c1\u6709\u7ee7\u627f\u4e3e\u4f8b 

    class Point\n{\npublic:\nvoid InitP(float x = 0, float y = 0)\n{\nthis->X = x;\nthis->Y = y;\n}\nvoid Move(float offX, float offY)\n{\nX += offX;\nY += offY;\n}\nfloat GetX() const{return X;}\nfloat GetY() const{return Y;}\nprivate:\nfloat X, Y;\n};\nclass Rectangle: private Point // \u6d3e\u751f\u7c7b\u58f0\u660e\n{\npublic: //\u65b0\u589e\u5916\u90e8\u63a5\u53e3\nvoid InitR(float x, float y, float w, float h)\n{\nInitR(x, y);\nW = w;\nH = h;\n} // \nvoid Move(float xOff, float yOff)\n{\nPoint::\n}\n}\n

    "},{"location":"docs/1-cs/oop/final_review/","title":"ZJU \u671f\u672b\u590d\u4e60","text":"

    :material-circle-edit-outline: \u7ea6 1500 \u4e2a\u5b57 :fontawesome-solid-code: 36 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 5 \u5206\u949f

    \u9762\u5411\u671f\u672b\u9898\u7684\u76f8\u4f3c\u77e5\u8bc6\u70b9\u805a\u7c7b

    "},{"location":"docs/1-cs/oop/final_review/#_1","title":"\u6784\u9020\u987a\u5e8f","text":"

    \uff081\uff09main\u51fd\u6570\u4ee5\u5916\u7684\u5bf9\u8c61\uff0c\u5168\u5c40\u7c7b\u5b9a\u4e49\u540e\u76f4\u63a5\u5b9a\u4e49\u7684\u7c7b\u5bf9\u8c61 \uff082\uff09main\u51fd\u6570\u5185\u7684\u5bf9\u8c61 \uff083\uff09\u7236\u7c7b\u6784\u9020 \uff084\uff09\u5b50\u7c7b\u7c7b\u6210\u5458 \uff085\uff09\u5b50\u7c7b\u6784\u9020 \u6790\u6784\u987a\u5e8f\u76f8\u53cd

    "},{"location":"docs/1-cs/oop/final_review/#_2","title":"\u4ec0\u4e48\u65f6\u5019\u751f\u6210\u9ed8\u8ba4\u6784\u9020\u51fd\u6570\uff1f","text":"

    \u5982\u679c\u5df2\u7ecf\u6709\u6784\u9020\u51fd\u6570\uff0c\u7f16\u8bd1\u5668\u4e0d\u4f1a\u751f\u6210\u9ed8\u8ba4\u6784\u9020\u51fd\u6570 \u6ca1\u6709\u7684\u65f6\u5019\u4e5f\u4e0d\u4e00\u5b9a\u4f1a\u751f\u6210 \u9700\u8981\u7528\u624d\u751f\u6210

    "},{"location":"docs/1-cs/oop/final_review/#_3","title":"\u91cd\u8f7d\u89c4\u5219","text":"

    \u4e0d\u80fd\u91cd\u8f7d\u7684\u6709\uff1a - \u4f5c\u7528\u57df\u64cd\u4f5c\u7b26:: - \u6761\u4ef6\u64cd\u4f5c\u7b26?:\uff08\u5e94\u8be5\u662f\u95ee\u53f7\u8868\u8fbe\u5f0f\uff1f\uff09 - \u70b9\u64cd\u4f5c\u7b26\u3001\u7c7b\u6210\u5458\u6307\u9488 - \u9884\u5904\u7406\u7b26\u53f7#

    \u53ea\u80fd\u91cd\u8f7d\u4e3a\u53cb\u5143\u4e0d\u80fd\u6210\u5458\u51fd\u6570\uff1a - <<\u548c>> \u539f\u56e0\u662f\u6210\u5458\u51fd\u6570\u91cd\u8f7d\uff0c\u53ea\u80fd\u5e26\u4e00\u4e2a\u53c2\u6570\uff0clhs\u5fc5\u987b\u662f\u6210\u5458\u81ea\u8eab

    \u4f46\u662f\u6d41\u64cd\u4f5c\u7b26\u5de6\u8fb9\u662fcin\u6216cout\uff0c\u91cd\u8f7d\u4e3a\u53cb\u5143\u51fd\u6570\u65f6\uff0c\u53ef\u4ee5\u6bd4\u6210\u5458\u51fd\u6570\u591a\u8bf4\u660e\u4e00\u4e2a\u5f62\u53c2\u505alhs

    \u91cd\u8f7d\u548c\u91cd\u5199\u90fd\u662f\u591a\u6001\uff1a \u91cd\u8f7d\uff1a\u8fd0\u884c\u65f6\u591a\u6001 \u91cd\u5199\uff1a\u7f16\u8bd1\u65f6\u591a\u6001

    static\u548cvirtual\u53ea\u80fd\u6709\u4e00\u4e2a

    \u6790\u6784\u51fd\u6570\u4e0d\u80fd\u5e26\u53c2\u6570

    "},{"location":"docs/1-cs/oop/final_review/#_4","title":"\u5b50\u7c7b\u548c\u7236\u7c7b\u6307\u9488","text":""},{"location":"docs/1-cs/oop/final_review/#static_castdynamic_cast","title":"static_cast\u548cdynamic_cast","text":""},{"location":"docs/1-cs/oop/final_review/#_5","title":"\u5f15\u7528","text":"

    \u4ec0\u4e48\u65f6\u5019\u5fc5\u987b\u7528\u5e38\u5f15\u7528\uff08const &\uff09\uff1a\u5f15\u7528\u578b\u53c2\u6570\u5e94\u5f53\u5728\u80fd\u5b9a\u4e49\u4e3aconst\u7684\u60c5\u51b5\u4e0b\u5c3d\u91cf\u5b9a\u4e49\u4e3aconst\u3002

    \u4f7f\u7528\u5f15\u7528\u7684\u4e3b\u8981\u539f\u56e0\uff1a \u7a0b\u5e8f\u80fd\u591f\u4fee\u6539\u8c03\u7528\u51fd\u6570\u4e2d\u7684\u6570\u636e\u5bf9\u8c61 \u901a\u8fc7\u4f20\u9012\u5f15\u7528\u800c\u4e0d\u662f\u6574\u4e2a\u6570\u636e\u5bf9\u8c61\uff0c\u53ef\u4ee5\u63d0\u9ad8\u7a0b\u5e8f\u7684\u8fd0\u884c\u901f\u5ea6

    \u53ea\u4f7f\u7528\u4f20\u9012\u8fc7\u6765\u7684\u503c\u800c\u4e0d\u4fee\u6539 \u9700\u8981\u4fee\u6539\u4f20\u9012\u8fc7\u6765\u7684\u503c \u5185\u7f6e\u6570\u636e\u7c7b\u578b\uff08\u5c0f\u578b\u7ed3\u6784\uff09 \u6309\u503c\u4f20\u9012 \u6307\u9488\u4f20\u9012 \u6570\u7ec4 \u6307\u9488\u4f20\u9012 \u6307\u9488\u4f20\u9012 \u8f83\u5927\u7684\u7ed3\u6784\uff09 \u6307\u9488\u6216\u5f15\u7528 \u6307\u9488\u6216\u5f15\u7528 \u7c7b/\u5bf9\u8c61 \u5f15\u7528\u4f20\u9012 \u5f15\u7528\u4f20\u9012

    \u5f15\u7528\u548c\u6307\u9488\u7684\u533a\u522b\uff1a \u53ef\u4ee5\u628a\u5f15\u7528\u7406\u89e3\u6210\u4e00\u4e2a\u5e38\u91cf\u6307\u9488\uff0c\u56e0\u6b64\u5f15\u7528\u58f0\u660e\u65f6\u5c31\u5fc5\u987b\u521d\u59cb\u5316\uff0c\u4e00\u7ecf\u58f0\u660e\u4e0d\u80fd\u518d\u548c\u5176\u5b83\u5bf9\u8c61\u7ed1\u5b9a\u3002

    Copy constructor must pass its first argument by reference

    "},{"location":"docs/1-cs/oop/final_review/#_6","title":"\u7c7b\u5185\u9759\u6001\u6210\u5458\u7684\u521d\u59cb\u5316","text":"

    const static\u53ef\u4ee5\u5728\u7c7b\u5185\u76f4\u63a5\u521d\u59cb\u5316\uff0c\u975econst static\u6210\u5458\u9700\u8981\u5728\u7c7b\u5916\u521d\u59cb\u5316\u3002

    \u53ef\u4ee5\u8c03\u7528\u9ed8\u8ba4\u521d\u59cb\u5316A::n\uff0c\u81ea\u52a8\u521d\u59cb\u5316\u4e3a0\u3002\u6b64\u65f6\u8c03\u7528\u9ed8\u8ba4\u6784\u9020\u4e0d\u80fd\u7528n()\uff0c\u5426\u5219\u8ba4\u4e3a\u662f\u4e2a\u51fd\u6570\u3002\u6216\u8005\u5e26\u521d\u59cb\u503c\u521d\u59cb\u5316A::n(9)

    static\u548cconst - \u6ca1\u6709static\u5c31\u662fconst\u7684\u8bf4\u6cd5

    const\u7684\u51e0\u79cd\u5f62\u5f0f 

    const int& fun(int& a); // \u4fee\u9970\u8fd4\u56de\u503c \nint& fun(const int& a); // \u4fee\u9970\u5f62\u53c2 \nint& fun(int& a) const {} // const\u6210\u5458\u51fd\u6570\n

    const\u8fd4\u56de\u503c\uff1a\u662f\u4fee\u9970\u8fd4\u56de\u503c\u5f15\u7528\u7c7b\u578b\u7684\u65f6\u5019\uff0c\u4e3a\u4e86\u907f\u514d\u8fd4\u56de\u503c\u88ab\u4fee\u6539\u7684\u60c5\u51b5

    \u8fd4\u56de\u503c\u662f\u5f15\u7528\u7684\u51fd\u6570\uff0c\u8fd9\u4e2a\u5f15\u7528\u5fc5\u7136\u4e0d\u662f\u4e34\u65f6\u5bf9\u8c61\u7684\u5f15\u7528\uff0c\u4e00\u5b9a\u662f\u6210\u5458\u53d8\u91cf\u6216\u8005\u51fd\u6570\u53c2\u6570\u3002\uff08\u53ea\u8981\u53c2\u6570\u4e0d\u9700\u8981\u4fee\u6539\u4e00\u5b9a\u52a0\u4e0aconst\uff09

    const\u53c2\u6570\u5fc5\u987b\u4f20\u7b7e\u540d\u540e\u5e26const\u7684\u51fd\u6570\uff1a\u8981\u628athis\u6307\u9488\u53d8\u6210const

    \u600e\u6837\u6784\u6210\u91cd\u8f7d - \u4e0d\u91cd\u8f7d\u7684 

    const int& fun(int& a); // \u53c2\u6570\u5217\u8868\u6ca1\u6709\u53d8 \nint& fun(const int a); // \u56e0\u4e3a\u662f\u503c\u4f20\u9012\uff0c\u4e0d\u662fconst\u7684\u4e5f\u80fdtype conversion\n

    "},{"location":"docs/1-cs/oop/final_review/#inline-function","title":"inline function","text":"

    \u4ee3\u66ff\u5b8f\u7684\u4e00\u79cd\u64cd\u4f5c\uff0c\u5728\u7f16\u8bd1\u9636\u6bb5\u628a\u6240\u6709\u51fd\u6570\u540d\u66ff\u6362\u6210inline function\u7684\u5b9e\u73b0 \u6bd4\u51fd\u6570\u7684\u4f18\u70b9\uff1a\u4e0d\u7528\u9891\u7e41\u8fdb\u6808\u51fa\u6808 \u6bd4\u5b8f\u7684\u4f18\u70b9\uff1a\u6709\u7c7b\u578b\u68c0\u67e5\uff0c\u80fd\u5199\u591a\u884c\uff0c\u80fd\u64cd\u4f5c\u7c7b\u7684\u79c1\u6709\u6210\u5458 inline\u5173\u952e\u5b57\u53ea\u6709\u51fa\u73b0\u5728\u51fd\u6570\u7684\u5b9a\u4e49\u800c\u4e0d\u662f\u58f0\u660e\u524d\u65f6\u624d\u6709\u7528\u3002 \u9759\u6001\u7ed1\u5b9a\u00a0Static\u00a0Binding \u3002\u80fd\u591f\u660e\u786e\u8fd0\u884c\u7684\u662f\u54ea\u4e2a\u7c7b\u7684\u65b9\u6cd5\u65f6\u4f1a\u53d1\u751f\u9759\u6001\u7ed1\u5b9a \u3002\u53d1\u751f\u5728\u7f16\u8bd1\u65f6\u523b\uff0c\u6240\u4ee5\u53c8\u53eb\u65e9\u7ed1\u5b9a \u52a8\u6001\u7ed1\u5b9aDynamic\u00a0Binding \u3002\u51fa\u73b0\u591a\u6001\uff0c\u7f16\u8bd1\u5668\u4e0d\u80fd\u660e\u786e\u5230\u5e95\u4f7f\u7528\u54ea\u4e2a\u7c7b\u7684\u65b9\u6cd5\u65f6\u53d1\u751f\u52a8\u6001\u7ed1\u5b9a \u3002\u53d1\u751f\u5728\u8fd0\u884c\u65f6\u523b\uff0c\u6240\u4ee5\u53c8\u53eb\u665a\u7ed1\u5b9a \u3002\u53ea\u6709\u5b58\u5728\u00a0virtual\u00a0\u65e6\u901a\u8fc7\u6307\u9488\u8bbf\u95ee\u65f6\uff0c\u624d\u4f1a\u53d1\u751f\u52a8\u6001\u7ed1\u5b9a

    static binding \u7f16\u8bd1\u65f6 

    class Animal { public: void eat() { cout << \"Animal eats\" << endl; } }; class Dog : public Animal { public: void eat() { cout << \"Dog eats\" << endl; } };\n

    dynamic binding \u8fd0\u884c\u65f6 

    class Animal { public: virtual void eat() { cout << \"Animal eats\" << endl; } }; class Dog : public Animal { public: void eat() { cout << \"Dog eats\" << endl; } };\n
    \u200b

    \u5728\u4e0b\u9762\u7684\u60c5\u51b5\u4e0b\uff0c\u6784\u9020\u51fd\u6570\u4f1a\u88ab\u8c03\u7528\uff1a - \u5bf9\u4e8e\u5168\u5c40\u5bf9\u8c61\uff0c\u5728main()\u4e24\u6570\u8fd0\u884c\u4e4b\u524d\uff0c\u6216\u8005\u5728\u540c\u4e00\u4e2a\u7f16\u8bd1\u5355\u5143\u5185\u5b9a\u4e49\u7684\u4efb\u4e00\u51fd\u6570\u6216\u5bf9\u8c61 \u88ab\u4f7f\u7528\u4e4b\u524d\u3002\u5728\u540c\u4e00\u4e2a\u7f16\u8bd1\u5355\u5143\u5185\uff0c\u5b83\u4eec\u7684\u6784\u9020\u4e24\u6570\u6309\u7167\u58f0\u660e\u7684\u987a\u5e8f\u521d\u59cb\u5316\u3002 - \u5bf9\u4e8e static\u00a0local\u00a0variables\uff0c\u00a0\u5728\u7b2c\u4e00\u6b21\u8fd0\u884c\u5230\u5b83\u7684\u58f0\u660e\u7684\u65f6\u5019. - \u5bf9\u4e8e automatic\u00a0storage\u00a0duration\u00a0\u7684\u5bf9\u8c61\uff0c\u5728\u5176\u58f0\u660e\u88ab\u8fd0\u884c\u65f6\u3002 - \u5bf9\u4e8e dynamic\u00a0storage\u00a0duration\u00a0\u7684\u5bf9\u8c61\uff0c\u5728\u5176\u7528\u00a0new\u00a0\u8868\u8fbe\u5f0f\u521b\u5efa\u65f6\u3002

    "},{"location":"docs/1-cs/oop/final_review/#_7","title":"\u667a\u80fd\u6307\u9488","text":"
    std::unique_ptr<T> //\u72ec\u5360\u8d44\u6e90\u6240\u6709\u6743\u7684\u6307\u9488\u3002 \nstd::shared_ptr<T> //\u5171\u4eab\u8d44\u6e90\u6240\u6709\u6743\u7684\u6307\u9488\u3002 \nstd::weak_ptr<T> //\u5171\u4eab\u8d44\u6e90\u7684\u89c2\u5bdf\u8005\uff0c\u9700\u8981\u548cstd::shared_ptr \u4e00\u8d77\u4f7f\u7528\uff0c\u4e0d\u5f71\u54cd\u8d44\u6e90\u7684\u751f\u547d\u5468\u671f\u3002\n

    \u4f7f\u7528\u88f8\u6307\u9488 \u6240\u4ee5\u9ed8\u8ba4\u53c2\u6570\u662f\u548c\u865a\u8868\u65e0\u5173\u4e0e\u5f53\u524d\u7c7b\u578b\u6709\u5173\u5417 \u662f\u7684 \u9ed8\u8ba4\u53c2\u6570\u4e0d\u8fdb\u865a\u8868 \u2192 upcasting\u7684\u65f6\u5019

    "},{"location":"docs/1-cs/oop/final_review/#upcasting","title":"upcasting","text":""},{"location":"docs/1-cs/oop/templates/","title":"\u6a21\u677fTemplate \u548c \u6807\u51c6\u6a21\u677f\u5e93STL","text":"

    :material-circle-edit-outline: \u7ea6 1186 \u4e2a\u5b57 :fontawesome-solid-code: 361 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f

    \u9700\u6c42\uff1a\u8ba9\u6211\u4eec\u7684\u4ee3\u7801\u72ec\u7acb\u4e8e\u5177\u4f53\u7684\u7c7b\u578b\u5de5\u4f5c\u3002

    \u6211\u4eec\u5199\u51fa\u4e00\u4e2a\u9002\u7528\u4e8e\u6240\u6709\u7c7b\u578b\u7684\u6570\u636e\u7ed3\u6784\u7684\u7c7b\u6216\u7b97\u6cd5\uff08\u51fd\u6570\uff09\uff0c\u5728\u771f\u6b63\u9700\u8981\u4f7f\u7528\u65f6\u751f\u6210\u4e00\u4e2a\u9002\u7528\u4e8e\u6240\u9700\u7c7b\u578b\u7684\u5b9e\u4f8b\u3002\u8fd9\u79cd\u7f16\u7a0b\u8303\u5f0f\u79f0\u4e3a\u8303\u578b\u7f16\u7a0b\u3002

    \u6a21\u677f\u7c7b\u7684\u5199\u6cd5 

    template<typename T>\nclass Container{\nT *data;\nunsigned size, capa;\npiblic:\nContainer(unsigned capa = 512): data(new T[capa]){}\n~Container() {delete[] data;}\nT& operator[](unsigned index) {return data[index];}\n}\n

    \u8fd9\u91cctemplate T\u8868\u660e\u5b83\u63a5\u53d7\u4e00\u4e2a\u7c7b\u578b\u4f5c\u4e3a\u53c2\u6570\uff0c\u540d\u5b57\u662fT\u3002\u5728\u6a21\u677f\u7684\u5b9a\u4e49\u5185\u90e8\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5230\u8fd9\u4e2a\u7c7b\u578b\u53d8\u91cfT\u3002

    \u7279\u5316\uff1a\u6839\u636e\u6a21\u677f\u751f\u6210\u5b9e\u9645\u7684\u7c7b\u7684\u8fc7\u7a0b 

    Container<int> ci;\nContainer<double> cd;\n

    \u6a21\u677f\u51fd\u6570\u8981\u600e\u4e48\u5199 

    template<typename T>\nT abs(T x) {return x>0?x:-x;}\n

    \u6a21\u677f\u8fd0\u7b97\u7b26\u91cd\u8f7d\u600e\u4e48\u5199 

    template<typename T>\nclass Container {\nT* data;\nunsigned size = 0, capa;\npublic: Container(unsigned capa = 512) : data(new T[capa]), capa(capa){}\n~Container(){delete[] data;}\nT& operator[](unsigned index) {return data[index];}\nconst T& operator[](unsigned idnex) const {return data[index];}\nunsigned getSize() const {return size;}\nunsigned getCapa() const {return capa;}\nContainer &add(T val){\ndata[size++] = val;\nreturn *this;\n}\n};\ntemplate<typename T>\nostream & operator<<(ostream& os, const Container<T>&c){\nfor (unsigned i = 0; i < c.getSize(); i++){\nos << c[i] << ' ';\nreturn os;\n}\n}\n

    "},{"location":"docs/1-cs/oop/templates/#reference","title":"Reference","text":"

    7 \u6a21\u677f (I) - \u57fa\u672c\u77e5\u8bc6\u4e0e STL \u4f7f\u7528 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4

    "},{"location":"docs/1-cs/oop/templates/#template","title":"\u53ef\u53d8\u53c2\u6570\u6a21\u677f template

    C++11\u7684\u65b0\u7279\u6027 \u5bf9\u53c2\u6570\u9ad8\u5ea6\u6cdb\u5316\uff0c\u53ef\u4ee5\u8868\u793a0\u5230\u4efb\u610f\u4e2a\u4efb\u610f\u7c7b\u578b\u7684\u53c2\u6570\u3002

    \u8bed\u6cd5 

    template <class ...T>  // \u58f0\u660e\u4e00\u4e2a\u53c2\u6570\u5305\uff0c\u8fd9\u4e2a\u53c2\u6570\u5305\u4e2d\u5305\u542b0\u5230\u4efb\u610f\u4e00\u4e2a\u53c2\u6570\u6a21\u677f\nvoid f(T... args);     // \u5728\u6a21\u677f\u5b9a\u4e49\u7684\u53f3\u8fb9\uff0c\u53ef\u4ee5\u5c06\u53c2\u6570\u5305\u5c55\u5f00\u6210\u4e00\u4e2a\u4e00\u4e2a\u72ec\u7acb\u53c2\u6570\n

    \u6700\u5927\u7684\u96be\u70b9\uff1a\u5982\u4f55\u5c55\u5f00\u53ef\u53d8\u6a21\u677f\u53c2\u6570

    \u6253\u5370\u53c2\u6570\u4e2a\u6570\uff1a 

    template<class ...T>\nvoid f(T... args)\n{\n        cout << sizeof...(args) << endl;\n}\n\nf();\nf(1, 2);\nf(1, 2.5, \"\");\n

    \u9012\u5f52\u65b9\u5f0f\u5c55\u5f00\u53c2\u6570\u5305 

    #include <iostream>\nusing namespace std;\n\n// \u9012\u5f52\u7ec8\u6b62\u51fd\u6570\nvoid print(){\n    cout << \"empty\" << endl;\n}\n\n// \u5c55\u5f00\u51fd\u6570\ntemplate<class T, class ...Args>\nvoid print(T head, Args... rest){\n    cout << \"parameter\" << head << endl;\n    print(rest...);\n}\n\nint main(){\n    print(1, 2, 3, 4);\n    return 0;\n}\n

    \u4e0a\u8ff0\u4f8b\u5b50\u4f1a\u8f93\u51fa\u6bcf\u4e00\u4e2a\u53c2\u6570\uff0c\u76f4\u5230\u7a7a\u65f6\u8f93\u51faempty\u3002\u5c55\u5f00\u53c2\u6570\u5305\u7684\u51fd\u6570\u6709\u4e24\u4e2a\uff0c\u4e00\u4e2a\u662f\u9012\u5f52\u51fd\u6570\uff0c\u53e6\u4e00\u4e2a\u662f\u9012\u5f52\u7ec8\u6b62\u51fd\u6570\uff0c\u53c2\u6570\u5305Args\u2026\u5728\u5c55\u5f00\u7684\u8fc7\u7a0b\u4e2d\u9012\u5f52\u8c03\u7528\u81ea\u5df1\uff0c\u6bcf\u8c03\u7528\u4e00\u6b21\uff0c\u53c2\u6570\u5305\u4e2d\u7684\u53c2\u6570\u5c31\u5c11\u4e00\u4e2a\uff0c\u76f4\u5230\u6240\u6709\u53c2\u6570\u90fd\u5c55\u5f00\u4e3a\u6b62\u3002\u5f53\u6ca1\u6709\u53c2\u6570\u65f6\uff0c\u5219\u8c03\u7528\u975e\u6a21\u677f\u51fd\u6570print()\u7ec8\u6b62\u9012\u5f52\u8fc7\u7a0b\u3002

    \u7ec8\u6b62\u51fd\u6570\u4e5f\u53ef\u4ee5\u5199\u6210 

    template<class T>\nvoid print(T t){\n    cout << t << endl;\n}\n

    \u53ef\u53d8\u6a21\u677f\u53c2\u6570\u6c42\u548c 

    template<typename T>\nT sum(T t){\n    return t;\n}\ntemplate<typename T, typename ... Types>\nT sum(T first, Types ...rest){\n    return first + sum<T> (rest...);\n}\n\nsum(1, 2, 3, 4);\n

    \u9012\u5f52\u51fd\u6570\u5c55\u5f00\u53c2\u6570\u5305\u662f\u4e00\u79cd\u6807\u51c6\u505a\u6cd5\uff0c\u4e5f\u6bd4\u8f83\u597d\u7406\u89e3\uff0c\u4f46\u662f\u7f3a\u70b9\u65f6\u5fc5\u987b\u8981\u4e00\u4e2a\u91cd\u8f7d\u7684\uff08\u540c\u540d\uff09\u9012\u5f52\u7ec8\u6b62\u51fd\u6570\u6765\u7ec8\u6b62\u9012\u5f52\u3002

    \u6216\u8005\u4e0d\u9012\u5f52\u65b9\u5f0f\uff0c\u8fd9\u79cd\u65b9\u5f0f\u9700\u8981\u501f\u52a9\u9017\u53f7\u8868\u8fbe\u5f0f\u548c\u521d\u59cb\u5316\u5217\u8868\u3002\u524d\u9762\u7684print\u53ef\u4ee5\u8fd9\u4e48\u5199 

    template<class T>\nvoid printarg(T t){\n    cout << t << endl;\n}\n\ntemplate <class ...Args>\nvoid expand(Args... args){\n    int arr[] = {(printarg(args), 0)...};\n}\n\nexpand(1, 2, 3, 4);\n

    arr\u8fd9\u4e2a\u6570\u7ec4\u7684\u76ee\u7684\u5355\u7eaf\u662f\u5c55\u5f00\u53c2\u6570\u5305

    \u5982\u679c\u5c06\u51fd\u6570\u4f5c\u4e3a\u53c2\u6570\uff0c\u5c31\u53ef\u4ee5\u652f\u6301lambda\u8868\u8fbe\u5f0f 

    template<class F, class... Args> void expand(const F& f, Args&&...args){\ninitializer_list<int>{(f(std::forward< Args>(args)), 0)};\n}\nexpand([](int i){cout << i << endl;}, 1,2,3);\n

    \u53ef\u4ee5\u5e26\u4efb\u610f\u4e2a\u6570\u4e0d\u540c\u7684\u53c2\u6570\uff0c\u6bd4\u5982std::tuple 

    template<class... Types>\nclass tuple;\n

    \u6a21\u677f\u504f\u7279\u5316\u548c\u9012\u5f52\u65b9\u5f0f\u5c55\u5f00\u53c2\u6570\u5305

    \u53ef\u53d8\u53c2\u6570\u6a21\u677f\u7c7b\u7684\u5c55\u5f00\u4e00\u822c\u9700\u8981\u5b9a\u4e49\u4e24\u5230\u4e09\u4e2a\u7c7b\uff0c\u5305\u62ec\u7c7b\u58f0\u660e\u548c\u504f\u7279\u5316\u7684\u6a21\u677f\u7c7b 

    // \u524d\u5411\u58f0\u660e\ntemplate<typename... Args>\nstruct Sum;\n\n// \u57fa\u672c\u5b9a\u4e49\ntemplate<typename First, typename... Rest>\nstruct Sum<First, Rest...>{\n    enum { value = Sum<First>::value + Sum<Rest...>::value };\n}\n\n// \u9012\u5f52\u7ec8\u6b62\ntemplate<typename Last>\nstruct Sum<Last>{\n    enum { value = sizeof(Last) };\n}\n

    ","text":""},{"location":"docs/1-cs/oop/templates/#stl","title":"\u6807\u51c6\u6a21\u677f\u5e93 STL

    STL\u516d\u5927\u90e8\u4ef6\uff1a\u5bb9\u5668\uff08containers\uff09\uff0c\u5206\u914d\u5668\uff08allocators\uff09\uff0c\u7b97\u6cd5\uff08algorithm\uff09\uff0c\u8fed\u4ee3\u5668\uff08iterator\uff09\uff0c\u9002\u914d\u5668\uff08adapters\uff09\uff0c\u4eff\u51fd\u6570\uff08functors\uff09

    ","text":""},{"location":"docs/1-cs/oop/templates/#_1","title":"\u5e38\u7528\u7684\u5bb9\u5668","text":"

    vector, deque, list, set/multiset, map/multimap \u7b49

    "},{"location":"docs/1-cs/oop/templates/#1-vector","title":"1. Vector","text":"

    Vector\u662f\u4e00\u79cd\u53d8\u957f\u6570\u7ec4\u3002 

    #include<vector>\nusing namespace std;\nvector<int> name;\nvector<double> name;\nvector<char> name;\nvector<struct node> name;\n// \u8fd9\u4e24\u4e2a\u4e3b\u8981\u6709\u901f\u5ea6\u4e0a\u7684\u533a\u522b\uff0carray\u975e\u5e38\u6162\uff0cvector\u5feb\u4e00\u4e9b\nvector< vector<int> > name; // > >\u4e4b\u95f4\u8981\u52a0\u7a7a\u683c\uff0c\u65b0\u6807\u51c6\u4e0d\u7528\u52a0\u4e86\nvector<int> array[SIZE]; // \u8fd9\u4e2a\u4e0d\u662f\u5f88\u5e38\u7528\uff0c\u56e0\u4e3a\u5bb9\u6613\u51fa\u9519\uff0c\u4e14\u6570\u7ec4\u4e0d\u77e5\u9053\u81ea\u5df1\u7684\u957f\u5ea6\uff0c\u8fd8\u6709std::array\n

    \u8bbf\u95ee\u65b9\u5f0f 

    // 1. \u901a\u8fc7\u4e0b\u6807\n#include<iostream>\n#include<vector>\nusing namespace std;\nint main()\n{\nvector<int> vi;\nvi.push_back(1);\ncout<<vi[0]<<endl;\nreturn 0;\n}\n// 2. \u901a\u8fc7\u8fed\u4ee3\u5668\nvector<int>::iterator\nvector<double>::iterator\n// \u4f8b\n#include<iostream>\n#include<vector>\nint main()\n{\nvector<int> v;\nfor(int i = 0; i < 5; i++)\n{\nv.push_back(i); }\nvector<int>::iterator it=v.begin();\nfor(int i = 0; i < v.size(); i++)\n{\ncout << it[i] << \" \";\n// \u4e5f\u53ef\u4ee5\u5199\u6210 cout << * (it + i) << \" \";\n}\nreturn 0;\n}\n// \u6216\u8005\u4f18\u96c5\u7684\u5199\u6cd5\n// \u56e0\u4e3a\u8fed\u4ee3\u5668\u4e0d\u652f\u6301 it < v.end()\u7684\u5199\u6cd5\uff0c\u53ea\u80fd\u5199!=\nfor (vector<int>::iterator it=v.begin(); it!=v.end();it++)\n{\ncout << *it << \" \";\n}\n
    \u5e38\u7528\u51fd\u6570 
    push_back(item) // \u5728vector\u540e\u9762\u6dfb\u52a0\u4e00\u4e2a\u5143\u7d20\npop_back(item) // \u5728vector\u540e\u9762\u5220\u9664\u4e00\u4e2a\u5143\u7d20\nsize(vector) // \u8fd4\u56de\u5143\u7d20\u4e2a\u6570\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(1)\nclear(vector) // \u6e05\u9664\u6240\u6709\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(N)\ninsert(position, x) // \u5728position\u7684\u5730\u65b9\u63d2\u5165\u4e00\u4e2ax\n// \u4f8b\nv.insert(v.begin()+2, -1); // \u76f8\u5f53\u4e8e\u5728v[2]\u5904\u63d2\u5165\u4e00\u4e2a-1\nerase(position);\nerase(positionBegin, positionEnd);  // \u5de6\u95ed\u53f3\u5f00\n

    "},{"location":"docs/1-cs/oop/templates/#2-set","title":"2. set","text":"

    \u96c6\u5408\u662f\u4e0d\u5141\u8bb8\u5143\u7d20\u91cd\u590d\u7684\u65e0\u5e8f\u5bb9\u5668 

    #include<set>\nusing namespace std;\nset<int> name;\nset<double> name;\nset<char> name;\nset<struct node> name;\nset<set<int> > name;\n
    \u56e0\u4e3a\u65e0\u5e8f\uff0cset\u53ea\u80fd\u901a\u8fc7iterator\u8bbf\u95ee\uff0c\u9664\u4e86vector\u548cstring\u4e4b\u5916\u7684\u5bb9\u5668\u90fd\u4e0d\u80fd\u901a\u8fc7\u4e0b\u6807\u8bbf\u95ee 
    set<int>::iterator it;\nset<char>::iterator it;\n
    \u5e38\u7528\u51fd\u6570 
    st.insert(X);\nst.find(X); // \u8fd4\u56deset\u4e2dvalue\u6240\u5bf9\u5e94\u7684\u8fed\u4ee3\u5668\uff0c\u4e5f\u5c31\u662fvalue\u7684\u6307\u9488\n// \u4f8b\nset<int>::iterator it = st.find(2);\ncout << *it << endl;\n// \u53ef\u4ee5\u76f4\u63a5\u5199\u6210\ncout << *(st.find(2)) << endl;\nst.erase(it); // \u5220\u9664\u67d0\u4e2a\u5730\u5740\u7684\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(1)\nst.erase(X); // \u5220\u9664\u67d0\u4e2a\u5143\u7d20\uff0c\u65f6\u95f4\u590d\u6742\u5ea6O(N)\nst.erase(itBegin, itEnd);\nst.size();\n

    "},{"location":"docs/1-cs/oop/templates/#3-deque","title":"3. deque","text":"

    deque\u662f\u7531\u4e00\u6bb5\u5b9a\u91cf\u8fde\u7eed\u7a7a\u95f4\u6784\u6210\uff0c\u4e00\u65e6\u8981\u5728deque\u7684\u524d\u7aef\u548c\u5c3e\u7aef\u589e\u52a0\u7a7a\u95f4\uff0c\u4fbf\u914d\u7f6e\u4e00\u6bb5\u8fde\u7eed\u7a7a\u95f4\uff0c\u4e32\u5728\u6574\u4e2adeque\u7684\u5934\u90e8\u548c\u5c3e\u90e8.

    "},{"location":"docs/1-cs/oop/templates/#4-list","title":"4. list","text":""},{"location":"docs/1-cs/oop/templates/#5-mapunordered_map","title":"5. map/unordered_map","text":""},{"location":"docs/1-cs/oop/templates/#6-string","title":"6. string","text":"
    // init\n#include<string>\nstring str;\nstring str = \"Hello\";\ncin >> str;\ncout << str;\n// assignment\nchar cstr1[20];\nchar cstr2[20] = \"jaguar\";\nstring str1;\nstring str2 = \"panther\";\ncstr1 = cstr2; // illegal\nstr1 = str2; // legal\n// concatenation\nstring str3;\nstr3 = str1 + str2;\nstr1 += str2;\nstr1 += \"a string literal\";\n// constructors (Ctors)\nstring (const char *cp, int len);\nstring (const string& s2, int pos);\nstring (const string& s2, int pos, int len);\n// sub-string\nsubstr (int pos, int len);\n// modification\nassign (...);\ninsert (...);\ninsert (int pos, const string& s);\nerase (...);\nappend (...);\nreplace (...);\nreplace (int pos, int len, const string& s);\n...\n// search\nfind (const string& s);\n// File I/O\n#include <ifstream> // read from file\n#include <ofstream>  // write to file\n// write into file\nofstream File1(\"...\");\nFile1 << \"Hello world\" << std::enl;\n// read from file\nifstream File2(\"...\");\nstd::string str;\nFile2 >> str;\n
    "},{"location":"docs/1-cs/oop/templates/#_2","title":"\u7b97\u6cd5","text":"

    \u7b97\u6cd5\u90e8\u5206\u4e3b\u8981\u7531<algorithm> <numeric> <functional>\u7ec4\u6210 <algorithm>\u662f\u6700\u5927\u7684\u4e00\u4e2a <numeric>\u4f53\u79ef\u5f88\u5c0f\uff0c\u53ea\u5305\u62ec\u51e0\u4e2a\u5728\u5e8f\u5217\u4e0a\u8fdb\u884c\u7b80\u5355\u6570\u5b66\u8fd0\u7b97\u7684\u6a21\u677f\u51fd\u6570 <functional>\u5b9a\u4e49\u4e86\u4e00\u4e9b\u6a21\u677f\u7c7b\uff0c\u7528\u4ee5\u58f0\u660e\u51fd\u6570\u5bf9\u8c61

    "},{"location":"docs/1-cs/oop/templates/#iterator","title":"\u8fed\u4ee3\u5668 Iterator","text":"

    \u7528\u8fed\u4ee3\u5668\u53ef\u4ee5\u8bfb\u53d6\u5b83\u6307\u5411\u7684\u5143\u7d20\u3002\u8fed\u4ee3\u5668\u540d\u5c31\u8868\u793a\u8fed\u4ee3\u5668\u6307\u5411\u7684\u5143\u7d20\uff0c\u901a\u8fc7\u975e\u5e38\u91cf\u8fed\u4ee3\u5668\u8fd8\u80fd\u4fee\u6539\u5176\u6307\u5411\u7684\u5143\u7d20\u3002 

    #include<iostream> #include<vector> using namespace std; int main() { vector<int> v; for (int n = 0; n < 5; ++n) v.push_back(n); vector<int>::iterator i; for (i = v.begin(); i != v.end(); i++) { cout << *i << \" \"; // *i \u662f i \u6307\u5411\u7684\u5143\u7d20 *i *= 2; \n} }\n

    "},{"location":"docs/1-cs/oop/templates/#stl_1","title":"\u7c7b\u5e93\u548cSTL

    STL\u662f\u8303\u578b\u7a0b\u5e8f\u8bbe\u8ba1\u7684\u4e00\u4e2a\u8303\u4f8b\uff0c\u542b\uff1a\u5bb9\u5668\uff08container\uff09\u3001\u8fed\u4ee3\u5668\uff08iterator\uff09\u3001\u7b97\u6cd5\uff08algorithm\uff09\u3001\u51fd\u6570\u5bf9\u8c61\uff08function object\uff09\u3002\u7c7b\u5e93\u662f\u7c7b\u7684\u96c6\u5408\uff0c\u662f\u4e00\u79cd\u9884\u5b9a\u4e49\u7684\u9762\u5411\u5bf9\u8c61\u7684\u7a0b\u5e8f\u5e93\u3002

    ","text":""},{"location":"docs/1-cs/oop/templates/#c","title":"C++\u7684\u6807\u51c6\u5e93","text":"

    using namespace std;

    "},{"location":"docs/1-cs/oop/templates/#stl_2","title":"STL\u4e2d\u7684\u5bb9\u5668\u7c7b","text":"

    \u5bb9\u5668\uff08container\uff09\u7c7b\u662f\u7528\u6765\u5bb9\u7eb3\u3001\u5305\u542b\u4e00\u7ec4\u5143\u7d20\u6216\u5143\u7d20\u96c6\u5408\u7684\u5bf9\u8c61\u7684\u3002STL\u4e2d\u5b9a\u4e49\u4e86\u591a\u79cd\u4e0d\u540c\u7c7b\u578b\u7684\u5bb9\u5668\uff0c\u4f8b\u5982

    "},{"location":"docs/1-cs/oop/templates/#vector","title":"\u5411\u91cf vector","text":"

    \u5b9a\u4e49

    vector<int> iv;\nvector<int> cv(5);\nvector<int> cv(5, 'x');\nvector<int> iv2(iv);\n

    \u4f7f\u7528

    #include<iostream>\n#include<vector>\nusing namespace std;\nint main()\n{\nvector<char> v;  // create zero-len vector\nint i;\n// put values into a vector\nfor (i = 0; i < 10; i++)\nv.push_back('A' + i);\n// can access vector contents using subsripting\nfor (i = 0; i < 10; i++)\ncout << v[i] << \" \";\ncout << endl;\n// access via iterator\nvector<char>::iterator p = v.begin();\nwhile(p != v.end())\n{\ncout << *p << \" \";\np++;\n}\nreturn 0;\n}\n
    "},{"location":"docs/1-cs/oop/templates/#list","title":"\u7ebf\u6027\u8868 list","text":"

    \u5b9a\u4e49\u4e86\u53cc\u5411\u7684\u7ebf\u6027\u8868\uff0c\u53c8\u53ef\u79f0\u4e3a\u53cc\u5411\u94fe\u8868\u3002list\u7c7b\u53ea\u652f\u6301\u987a\u5e8f\u8bbf\u95ee\u3002

    // sort a list\n#include<iostream>\n#include<list>\n#include<cstdlib>\nusing namespace std;\nint main()\n{\nint i;\nlist<char> lst;\n// create a list of random characters\nfor (i = 0; i < 10; i++)\nlist.push_back('A' + (rand()%26));\n}\n
    "},{"location":"docs/1-cs/oop/templates/#set","title":"\u96c6\u5408 set","text":"
    #include<set>\n#include<iostream>\n#include<string>\nint main()\n{\nstd::set<std::string> source;\nstd::string input;\nfor(int i=0;i<6;i++)\n{\nstd::cin>>input;\nsource.insert(input);\n}\nstd::set<std::string>::iterator at = source.begin();\nwhile(at != source.end())\nstd::cour << * at++ << std::endl;\n}\n
    "},{"location":"docs/1-cs/oop/templates/#multiset","title":"multiset","text":""},{"location":"docs/1-cs/oop/templates/#map","title":"\u6620\u5c04 map","text":""},{"location":"docs/1-cs/oop/templates/#queue","title":"\u961f\u5217 queue","text":""},{"location":"docs/1-cs/oop/templates/#stdstack","title":"std::stack","text":""},{"location":"docs/1-cs/oop/templates/#stdpair","title":"std::pair","text":""},{"location":"docs/1-cs/oop/templates/#string","title":"\u5b57\u7b26\u4e32string","text":""},{"location":"docs/1-cs/oop/templates/#_3","title":"\u7b97\u6cd5\u5e93 ` ","text":""},{"location":"docs/1-cs/oop/templates/#sort","title":"\u6392\u5e8f\u7b97\u6cd5sort","text":"
    #include<algorithm>\n#include<iostream>\n#include<string>\n#include<vector>\nusing namespace std;\nvoid load(vector<string>&);\nvoid print(vector<string>);\nconst int SIZE = 8;\nint main()\n{\nvector<string> v(SIZE);\nload(v);\nsort(v.begin(), v.end());  // \u6307\u5b9a\u6392\u5e8f\u7684\u8d77\u6b62\u4f4d\u7f6e\nprint(v);\nreturn 0;\n}\n// \u4f1a\u6309\u7167\u5b57\u6bcd\u5e8f\u6392\u5e8f\n
    "},{"location":"docs/1-cs/oop/templates/#_4","title":"\u8fed\u4ee3\u5668

    \u662f\u4e00\u79cd\u7c7b\u4f3c\u6307\u9488\u7684\u5bf9\u8c61\uff0c\u53ef\u4ee5\u4f7f\u7528\u8fed\u4ee3\u5668\u6765\u8bbf\u95ee\u5bb9\u5668\u4e2d\u7684\u5143\u7d20\u3002

    ","text":""},{"location":"docs/1-cs/oop/templates/#reverse-iterator","title":"\u53cd\u5411\u8fed\u4ee3\u5668 reverse iterator","text":"
    #include<list>\n#include<iostream>\nint main()\n{\nusing namespace std;\nlist<int> c1;\nlist<int>::iterator c1_Iter;\nlist<int>::reverse_iterator c1_rIter;\nc1_rIter = c1.rbegin(); // the last element\n}\n
    "},{"location":"docs/1-cs/oop/templates/#_5","title":"\u53c2\u8003\u8d44\u6599

    https://zhuanlan.zhihu.com/p/344558356 LJJ PPT

    ","text":""},{"location":"docs/1-cs/os/","title":"\u7d22\u5f15","text":"

    :material-circle-edit-outline: \u7ea6 384 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u6211\u89c9\u5f97 x+i for i in [x, y, g] \u4e09\u4f4d\u7684\u7b14\u8bb0\u5bf9\u4e8e\u8fd9\u95e8\u8bfe\u7406\u8bba\u90e8\u5206\u7684\u4ecb\u7ecd\u5df2\u7ecf\u975e\u5e38\u5145\u5206\u4e86\u3002\u5927\u5bb6\u53ef\u4ee5\u5728\u6211 root \u7d22\u5f15\u9875\u6307\u5411\u7684 xy \u7b14\u8bb0\u627e\u5230\u6211\u8fd9\u91cc\u63d0\u5230\u7684\u4e09\u4efd\u7b14\u8bb0\u3002

    \u6211\u4ecd\u8981\u5199\u8fd9\u95e8\u8bfe\u7684\u5b9e\u9a8c\u90e8\u5206\u7684\u539f\u56e0\u662f\uff0c\u81ea\u5df1\u89c9\u5f97\u5b9e\u9a8c\u624b\u518c\u5199\u5f97\u4ecd\u6709\u4e00\u4e9b\u5bfc\u81f4\u4e0d\u592a\u597d\u7406\u89e3\u7684\u7f3a\u9677\uff0c\u6bd4\u5982\u7406\u8bba\u548c\u64cd\u4f5c\u5206\u6210\u4e0a\u4e0b\u4e24\u5927\u5757\u6765\u5199\uff0c\u5bfc\u81f4\u67e5\u8d77\u6765\u7684\u65f6\u5019\u50cf\u5728\u5403\u4e00\u76d8\u94a2\u4e1d\u7403\u7092\u610f\u5927\u5229\u9762\uff0c\u6bd4\u5982\u6709\u65f6\u5728\u8bf4\u64cd\u4f5c\u65f6\u4e0d\u5206\u5df2\u7ecf\u5b9e\u73b0\u597d\u7684/\u6211\u8981\u505a\u7684/linux\u4f1a\u505a\u4f46\u662f\u6211\u4eec\u4e0d\u5173\u5fc3\u7684\u3002

    \u6211\u7684\u9884\u671f\u662f\u628a\u8fd9\u4efd\u7b14\u8bb0\u5199\u6210\u4e00\u5757\u4e00\u5757\u7684\u4e1c\u897f\uff0c\u6bcf\u4e00\u5757\u662f\u4e00\u4e2a\u7406\u8bba+\u64cd\u4f5c+\u4e00\u4e2a\u80fd\u8dd1\u8d77\u6765\u7684\u6700\u5c0f\u5355\u5143\u3002\u73b0\u5b9e\u662f\u6211\u7684\u65f6\u95f4\u771f\u7684\u592a\u4e0d\u8db3\u4e86\uff0c\u611f\u89c9\u53ea\u6765\u5f97\u53ca\u53bb\u8865\u5145\u4e00\u4e9b\u5b9e\u9a8c\u624b\u518c\u91cc\u6ca1\u6709\u5199\u7684\u80cc\u666f\u6216\u8005\u662f\u6211\u81ea\u5df1\u64cd\u4f5c\u65f6\u7684\u4e00\u4e9b\u5fc3\u5f97\u6216\u603b\u7ed3\uff0c\u53ea\u80fd\u5f53\u5b9e\u9a8c\u624b\u518c\u7684\u8865\u5145\u6765\u770b\u3002\u7136\u540e\u672c\u6765\u8fd9\u91cc\u5e94\u5f53\u6709\u4e00\u53e5\u5e0c\u671b\u4ee5\u540e\u6709\u65f6\u95f4\u80fd\u5199\u5b8c\uff0c\u4f46\u662f\u6211\u4e5f\u4e0d\u60f3\u8fd9\u6837\u627f\u8bfa\u4e86\uff0c\u6211\u66f4\u613f\u610f\u8bf4\u4e00\u4e9b\u73b0\u5b9e\u7684\u6bd4\u5982\u6211\u4e0d\u4f1a\u518d\u66f4\u65b0\u8fd9\u4efd\u7b14\u8bb0\u4e86\uff0c\u4f46\u662f\u5e0c\u671b\u8bfb\u8005\u505a\u5b9e\u9a8c\u7684\u65f6\u5019\u53ef\u4ee5\u5e26\u7740\u4e0a\u8ff0\u63d0\u5230\u7684\u601d\u8def\u53bb\u6574\u7406\u81ea\u5df1\u7684\u601d\u7ef4\u548c\u5b9e\u9a8c\u62a5\u544a\u3002

    \u63a5\u4e0b\u6765\u8bf7\u70b9\u8fdb\u53e6\u4e00\u4e2a lab \u9875\u9762\u7ee7\u7eed\u9605\u8bfb\u3002

    "},{"location":"docs/1-cs/os/lab/","title":"OS lab","text":"

    :material-circle-edit-outline: \u7ea6 8965 \u4e2a\u5b57 :fontawesome-solid-code: 91 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 31 \u5206\u949f

    \u76ee\u5f55\uff1a\u8fd9\u91cc\u4f1a\u5148\u8bb2\u4e00\u4e0b\u7528\u5230\u7684\u80cc\u666f\u77e5\u8bc6\u548c mac \u4e0b\u7684\u73af\u5883\u914d\u7f6e\u6280\u5de7\uff08\u56e0\u4e3a\u624b\u518c\u8bb2 mac \u4e0d\u591a\uff09\uff0c\u7136\u540e\u6328\u4e2a\u5b9e\u9a8c\u6211\u60f3\u8fdb\u884c\u4e00\u4e9b\u7efc\u8ff0\uff0c\u4e0d\u77e5\u9053\u7cbe\u529b\u80fd\u652f\u6491\u5199\u591a\u5c11\uff0c\u6700\u540e\u8865\u5145\u4e24\u4e2a\u6211\u5b9e\u9a8c\u4e2d\u603b\u9047\u5230\u7684\u4f46\u624b\u518c\u6ca1\u6d89\u53ca\u7684\u95ee\u9898\u3002\u81ea\u77e5\u5b66\u5f97\u4e0d\u597d\uff0c\u4e0d\u786e\u5b9a\u7684\u5730\u65b9\u6211\u4f1a\u6807\u51fa\u6765\u3002

    "},{"location":"docs/1-cs/os/lab/#overview","title":"overview","text":"

    Warning

    \u7ed3\u6784\u56fe TODO

    \u4e00\u4e2a\u6700\u540e\u505a\u51fa\u6765\u7684 lab \u7ed3\u6784\u56fe:

    "},{"location":"docs/1-cs/os/lab/#_1","title":"\u80cc\u666f\u77e5\u8bc6","text":"

    \u5148\u4ecb\u7ecd\u4e00\u4e0b\u6574\u4e2a\u5b9e\u9a8c\u548c\u5b9e\u9a8c\u73af\u5883\u7684\u5927\u80cc\u666f\u3002

    "},{"location":"docs/1-cs/os/lab/#os","title":"\u8ba1\u7b97\u673a\u4e0a\u7535\u5230OS\u8fd0\u884c\u7684\u8fc7\u7a0b","text":"

    \u5d4c\u5165\u5f0f\u7cfb\u7edf\uff08\u76f8\u6bd4\u8ba1\u7b97\u673a\u7cfb\u7edf\u6bd4\u8f83\u7b80\u5355\uff0c\u53ea\u80fd\u5728\u7279\u5b9a\u786c\u4ef6\u4e0a\u8fd0\u884c\uff09\u7684\u542f\u52a8\u8fc7\u7a0b\u6bd4\u8f83\u7b80\u5355\uff0c\u7528\u5b83\u6765\u505a\u4f8b\u5b50\u8bb2\u89e3\uff0c\u8fc7\u7a0b\u662f\uff1a

    Hardware             RISC-V M Mode           RISC-V S Mode \n+------------+         +--------------+         +----------+\n|  Power On  |  ---->  |  Bootloader  |  ---->  |  Kernel  |\n+------------+         +--------------+         +----------+\n
    "},{"location":"docs/1-cs/os/lab/#sbiopensbi","title":"sbi\u548copensbi","text":"

    \u4ecb\u7ecd\u5b9e\u9a8c\u73af\u5883\u7528\u7684\u7b2c\u4e00\u4e2a\u5de5\u5177\uff1asbi (supervisor binary interface)\u662f s-mode \u7684 kernel \u548c m-mode \u6267\u884c\u73af\u5883\u4e4b\u95f4\u7684\u63a5\u53e3\u89c4\u8303

    opensbi\u662f\u4e00\u4e2ariscv sbi\u89c4\u8303\u7684\u5f00\u6e90\u5b9e\u73b0\uff0c\u603b\u4e4b\u610f\u601d\u662fopensbi\u662f\u4e00\u4e9b\u5bf9m-mode\u4e0b\u786c\u4ef6\u7684\u7edf\u4e00\u5b9a\u4e49\uff0c\u5728s-mode\u4e0b\u7684\u5185\u6838\u53ef\u4ee5\u6309\u7167\u8fd9\u4e9b\u89c4\u8303\u5bf9\u4e0d\u540c\u786c\u4ef6\u64cd\u4f5c\u3002

    \u6211\u4eecopensbi\u53ef\u4ee5\u4f5c\u4e3abootloader\u5b8c\u6210\u673a\u5668\u542f\u52a8\u65f6m-mode\u4e0b\u7684\u786c\u4ef6\u521d\u59cb\u5316\u548c\u5bc4\u5b58\u5668\u8bbe\u7f6e\uff0c\u53ef\u4ee5\u5229\u7528opensbi\u5b8c\u6210\u5b57\u7b26\u6253\u5370\u4e4b\u7c7b\u7684\u64cd\u4f5c\u3002

    qemu\u4f1a\u628aopensbi\u8d77\u59cb\u5730\u5740\u52a0\u8f7d\u52300x80000000\u5904.

    opensbi\u521d\u59cb\u5316\u540e\u4f1a\u8df3\u8f6c\u52300x80200000\u5904\uff0c\u5373kernel\u7684\u8d77\u59cb\u5730\u5740\u3002\u6240\u4ee5\u8981\u7f16\u8bd1\u7684\u4ee3\u7801\u57280x80200000\u5904\u3002

    "},{"location":"docs/1-cs/os/lab/#_2","title":"\u7279\u6743\u6a21\u5f0f","text":"

    riscv\u6709\u4e09\u79cd\u7279\u6743\u6a21\u5f0f\uff1aUser, Supervisor, & Machine\u3002\u6574\u4e2a\u5b9e\u9a8c\u4e2d\u6211\u4eec\u4e00\u5f00\u59cb\u90fd\u8981\u5728 s-mode \u64cd\u4f5c\uff0c\u4e4b\u540e\u6162\u6162\u5b9e\u73b0 u-mode\u3002

    Level Encoding Name Abbreviation \u4ecb\u7ecd 0 00 User/Application U \u5bf9\u786c\u4ef6\u6a21\u5f0f\u7684\u62bd\u8c61\uff0c\u6709\u6700\u9ad8\u7ea7\u522b\u7684\u6743\u9650 1 01 Supervisor S \u5bf9\u5e94\u4e0e\u5185\u6838\u6001Kernel\u3002\u5f53\u7528\u6237\u9700\u8981\u5185\u6838\u8d44\u6e90\u65f6\uff0c\u5411\u5185\u6838\u7533\u8bf7\uff0c\u5e76\u5207\u6362\u5230\u5185\u6838\u6001\u8fdb\u884c\u5904\u7406 2 10 Reserved 3 11 Machine M \u7528\u6237\u6001\uff0c\u6700\u4f4e\u7ea7\u522b\u6743\u9650

    \u4e00\u822c\u6bcf\u79cd\u6a21\u5f0f\u53ef\u4ee5\u8fd0\u884c\u7684\u7a0b\u5e8f\u6709

    supported modes intended usage M simple embedded systems M, U secure embedded systems M, S, U systems running unix-like operating systems"},{"location":"docs/1-cs/os/lab/#_3","title":"\u73af\u5883\u914d\u7f6e","text":""},{"location":"docs/1-cs/os/lab/#docker","title":"Docker","text":"

    \u5728\u5b98\u7f51\u5b89\u88c5Docker\u3002\u4e4b\u540e\u9700\u8981\u6253\u5f00Docker app\uff0c\u767b\u9646\u540e\u624d\u80fd\u5728terminal\u4e2d\u4f7f\u7528docker\u547d\u4ee4\u3002

    $ sudo hdiutil attach Docker.dmg\n$ sudo /Volumes/Docker/Docker.app/Contents/MacOS/install\n$ sudo hdiutil detach /Volumes/Docker\n

    \u521b\u5efa\u5bb9\u5668

    docker pull ubuntu:22.04\ndocker run -it --name my_linux ubuntu:22.04 bash\n

    \u51fa\u73b0root@xxxxxxx:?# \u5373\u521b\u5efa\u6210\u529f\uff0c\u5176\u4e2dxxxxxxx\u4e00\u4e32\u662f\u5f53\u524d\u5bb9\u5668\u7684id\uff0c\u9700\u8981\u8bb0\u5f55\u4e0b\u6765\uff0c\u4e0b\u6b21\u53ef\u4ee5\u901a\u8fc7\u8be5id\u8fdb\u5165\u76f8\u540c\u5bb9\u5668\u3002

    \u5b89\u88c5\u4ea4\u53c9\u7f16\u8bd1\u5de5\u5177\u5305\uff0cqemu\uff0cgdb\uff0c\u8fd9\u51e0\u6b65\u9700\u8981\u5f00\u7740\u547d\u4ee4\u884c\u4ee3\u7406\uff0c\u622a\u56fe\u7565\u3002

    "},{"location":"docs/1-cs/os/lab/#docker_1","title":"\u806a\u660e\u5730\u4f7f\u7528docker","text":"

    \u8fd8\u662f\u6700\u597d\u914d\u7f6e\u4e00\u4e0b vscode \u91cc\u7684\u56fe\u5f62\u754c\u9762\u3002\u6b65\u9aa4\uff1a

    "},{"location":"docs/1-cs/os/lab/#_4","title":"\u65b9\u6cd5\u4ecb\u7ecd","text":"

    Warning

    TODO \u8fd9\u5757\u5e94\u8be5\u518d\u6269\u5199\u4e00\u4e0b\u7684

    "},{"location":"docs/1-cs/os/lab/#qemu-gdb","title":"qemu + gdb \u8c03\u8bd5","text":"

    \u9700\u8981\u8c03\u8bd5\u65f6\uff0c\u56e0\u4e3a\u9876\u5c42 makefile \u5e2e\u6211\u4eec\u5199\u597d\u4e86\u8c03\u8bd5\u547d\u4ee4\uff0c\u6211\u4eec\u7b2c\u4e00\u4e2a terminal \u53ea\u9700\u8981\u8f93\u5165 make debug\u3002 \u7136\u540e\u65b0\u5f00\u4e00\u4e2a terminal \u8f93\u5165 gdb-multiarch path/to/vmlinux \u5176\u4e2d vmlinux \u662f\u7f16\u8bd1\u597d\u7684\u6587\u4ef6\u3002

    gdb \u4f7f\u7528\u7684\u65b9\u6cd5/\u7a8d\u95e8

    \u663e\u793a\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u663e\u793a\u6e90\u4ee3\u7801 layout src \u663e\u793a\u6c47\u7f16\u4ee3\u7801 layout asm \u9000\u51fa\u6c47\u7f16\u663e\u793a ctrl+x, A \u9000\u51fagdb quit \u6267\u884c\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u5355\u6b65\u6267\u884c\uff0c\u8fd0\u884c\u7a0b\u5e8f\uff0c\u505c\u5728\u7b2c\u4e00\u6267\u884c\u8bed\u53e5 start \u65ad\u70b9\u540e\u7ee7\u7eed\u6267\u884c c continue \u5355\u6b65\u8c03\u8bd5\uff08\u9010c\u8bed\u8a00\u8bed\u53e5\uff0c\u51fd\u6570\u76f4\u63a5\u6267\u884c\uff09 n next \u6267\u884c\u5355\u6761\u6307\u4ee4 si step instruction \u91cd\u65b0\u5f00\u59cb\u8fd0\u884c\u6587\u4ef6\uff08run-text\uff1a\u52a0\u8f7d\u6587\u672c\u6587\u4ef6\uff0crun-bin\uff1a\u52a0\u8f7d\u4e8c\u8fdb\u5236\u6587\u4ef6\uff09 r run \u7ed3\u675f\u5f53\u524d\u51fd\u6570\uff0c\u8fd4\u56de\u5230\u51fd\u6570\u8c03\u7528\u70b9 finish \u65ad\u70b9\u6709\u5173 \u7b80\u5199 \u6307\u4ee4 \u8bbe\u7f6e\u65ad\u70b9\u5728foo\u51fd\u6570 b foo break foo \u65ad\u5728\u67d0\u5730\u5740 b * 0x80200000 break * 0x80200000 \u67e5\u770b\u7b2cm\u4e2a-\u7b2cn\u4e2a\u65ad\u70b9 info breakpoints [LIST] \u67e5\u770b\u6240\u6709\u65ad\u70b9 info breakpoints \u5220\u9664N\u53f7\u65ad\u70b9 delete [N] \u5c55\u793a\u503c\u6709\u5173\u7684 \u7b80\u5199 \u6307\u4ee4 \u67e5\u770b\u51fd\u6570\u7684\u8c03\u7528\u7684\u6808\u5e27\u548c\u5c42\u7ea7\u5173\u7cfb bt backtrace \u5207\u6362\u51fd\u6570\u7684\u6808\u5e27 f frame \u6253\u5370\u503c\u53ca\u5730\u5740 p print \u67e5\u770b\u51fd\u6570\u5185\u90e8\u5c40\u90e8\u53d8\u91cf\u7684\u6570\u503c i ifo \u67e5\u770b\u5bc4\u5b58\u5668 ra \u7684\u503c i r ra \u8ffd\u8e2a\u67e5\u770b\u5177\u4f53\u53d8\u91cf\u503c display [] \u4ee5 16 \u8fdb\u5236\u6253\u5370\u00a0\u00a0\u5904\u5f00\u59cb\u7684 16 Bytes \u5185\u5bb9 x/4x \u663e\u793a\u6570\u7ec4 p *swapper_pg_dir@100 16\u8fdb\u5236\u663e\u793a\uff08x\u500d\u6570\u53ea\u80fd\u4e3a1\uff09 p/x swapper_pg_dir [start]@1

    \u8c03\u8bd5\u7684\u65f6\u5019\u9700\u8981\u770b\u4ec0\u4e48\u5462\uff1f

    \u8fd9\u662f\u6211\u521a\u4e0a\u624b\u8c03\u8bd5\u7684\u65f6\u5019\u611f\u5230\u56f0\u6270\u7684\u4e00\u4e2a\u95ee\u9898\u3002

    \u540e\u6765\u6211\u9010\u6e10\u60f3\u6e05\u695a\u7684\u662f\uff0c\u9996\u5148\u6211\u8ba4\u4e3a\u5982\u679c\u4e0d\u77e5\u9053\u6b63\u5728\u8fd0\u884c\u7684\u7a0b\u5e8f\u8fd0\u884c\u7684\u6d41\u7a0b\uff08\u6bd4\u5982\u5148\u54ea\u4e2a\u51fd\u6570\u518d\u54ea\u4e2a\u51fd\u6570\uff09\uff0c\u662f\u4e0d\u9002\u5408\u5f00\u59cb\u8c03\u8bd5\u7684\uff0c\u5e94\u5f53\u56de\u53bb\u518d\u601d\u8003\u4e00\u904d lab \u7684\u7406\u8bba\uff0c\u8d77\u7801\u77e5\u9053\u81ea\u5df1\u7a0b\u5e8f\u7684\u5404\u79cd\u9884\u671f\u7ed3\u679c\u3002\u66b4\u8bba\u4e00\u70b9\u8bf4\u5176\u5b9e\u6211\u89c9\u5f97\u8c03\u8bd5\u65f6\u957f\u5927\u4e8e\u5f00\u53d1\u65f6\u957f\u90fd\u662f\u4e0d\u592a\u597d\u7684\uff0c\u66b4\u9732\u51fa\u80af\u5b9a\u54ea\u91cc\u7406\u8bba\u6ca1\u5543\u900f\u5c31\u5f00\u59cb\u52a8\u7b14\u4e86\u3002

    \u7136\u540e\u53ef\u4ee5\u7531\u5927\u5230\u5c0f\uff0c\u6bd4\u5982\u5148\u628a\u51e0\u4e2a\u65ad\u70b9\u6253\u5728\u731c\u6d4b\u53ef\u80fd\u51fa\u9519\u4e86\u7684\u51e0\u4e2a\u51fd\u6570\u4e0a\uff0c\u786e\u5b9a\u5177\u4f53\u5728\u54ea\u4e2a\u51fd\u6570\u51fa\u9519\u540e\u518d\u9010 c \u8bed\u8a00\u884c\u8fd0\u884c\uff0c\u786e\u5b9a\u662f\u54ea\u4e2a c \u8bed\u8a00\u884c\u51fa\u9519\u540e\u518d\u9010\u6c47\u7f16\u884c\u8fd0\u884c\uff0c\u5faa\u5e8f\u6e10\u8fdb\u627e\u5230\u5177\u4f53\u51fa\u9519\u7684\u6307\u4ee4\u3002\u5728\u9644\u8fd1\u6253\u5370\u6253\u5370\u51e0\u4e2a\u5bc4\u5b58\u5668\u7684\u503c\uff08\u53ef\u4ee5\u770b\u7684\u5bc4\u5b58\u5668\u6211\u4f1a\u5728\u4e0b\u4e00\u8282\u4ecb\u7ecd\uff09\uff0c\u7136\u540e\u5728\u6b64\u57fa\u7840\u4e0a\u601d\u8003\u9519\u8bef\u539f\u56e0\u3002

    "},{"location":"docs/1-cs/os/lab/#gdb","title":"\u806a\u660e\u5730\u4f7f\u7528 gdb","text":"

    gdb \u81ea\u5e26\u7684\u547d\u4ee4\u884c ui \u7f3a\u70b9\u4e3b\u8981\u5728\u4e8e\u4e0d\u80fd\u968f\u65f6\u663e\u793a\u5bc4\u5b58\u5668\u548c\u53d8\u91cf\u7684\u503c\uff0c\u8c03\u8bd5\u4f1a\u4e0d\u8212\u670d\u3002\u6709\u4e00\u4e9b\u66f4\u597d\u7684 ui \u5de5\u5177\u3002

    \u6211\u6ca1\u6709\u914d\u6240\u4ee5\u4e0d\u80fd\u63d0\u4f9b\u5f88\u597d\u7684\u6211\u7684\u63a8\u8350\uff0c\u8d34\u4e00\u4e9b\u522b\u4eba\u7684\u5e16\u5b50\u3002\u9664\u4e86\u4e0b\u9762\u5e16\u5b50\u91cc\u63d0\u5230\u7684\u51e0\u4e2a\uff0c\u8431\u8431\u8fd8\u63d0\u5230\u4e00\u4e2a gdbpeda\u3002

    \u63a8\u8350\u51e0\u4e2a\u597d\u7528\u7684GDB\u56fe\u5f62\u5316\u529f\u80fd\u589e\u5f3a\u63d2\u4ef6

    "},{"location":"docs/1-cs/os/lab/#lab0","title":"lab0","text":"

    \u6ca1\u96be\u5ea6\u4e0d\u7528\u8bb2

    "},{"location":"docs/1-cs/os/lab/#lab1","title":"lab1","text":""},{"location":"docs/1-cs/os/lab/#c-risc-v","title":"C & RISC-V \u5185\u8054\u6c47\u7f16","text":"

    Note

    \u8fd9\u5757\u6765\u81ea\u4e8e\u5bf9 lab1 \u6587\u6863\u7684\u6574\u7406\u3002\u5e0c\u671b\u6709\u6574\u7406\u5f97\u6bd4\u539f\u6587\u6863\u53ef\u8bfb\u4e00\u4e9b\u3002

    __asm__ volatile (\n\"instruction1\\n\"\n\"instruction2\\n\"\n......\n......\n\"instruction3\\n\"\n: [out1] \"=r\" (v1),[out2] \"=r\" (v2)\n: [in1] \"r\" (v1), [in2] \"r\" (v2)\n: \"memory\"\n);\n

    \u5176\u4e2d\uff0c\u4e09\u4e2a\u00a0:\u00a0\u5c06\u6c47\u7f16\u90e8\u5206\u5206\u6210\u4e86\u56db\u90e8\u5206\u3002\u8fd9\u56db\u90e8\u5206\u4e2d\u540e\u4e09\u90e8\u5206\u4e0d\u662f\u5fc5\u987b\u7684\uff1a

    \u8fd9\u6bb5\u6682\u65f6\u7528\u4e0d\u7740\u6211\u4e0d\u5199\u4e86\uff0c\u8d34\u4e00\u6bb5lab1\u4e2d\u7684\u539f\u6587\u7ed9\u7684\u793a\u4f8b\u3002e.g. 1

    unsigned long long s_example(unsigned long long type,unsigned long long arg0) {\nunsigned long long ret_val;\n__asm__ volatile (\n\"mv x10, %[type]\\n\"\n\"mv x11, %[arg0]\\n\"\n\"mv %[ret_val], x12\"\n: [ret_val] \"=r\" (ret_val)\n: [type] \"r\" (type), [arg0] \"r\" (arg0)\n: \"memory\"\n);\nreturn ret_val;\n}\n

    e.g. 1. \u4e2d\u6307\u4ee4\u90e8\u5206\uff0c%[type]\u3001%[arg0]\u4ee5\u53ca%[ret_val]\u4ee3\u8868\u7740\u7279\u5b9a\u7684\u5bc4\u5b58\u5668\u6216\u662f\u5185\u5b58\u3002\u8f93\u5165\u8f93\u51fa\u90e8\u5206\u4e2d\uff0c[type] \"r\" (type)\u4ee3\u8868\u7740\u5c06\u00a0()\u00a0\u4e2d\u7684\u53d8\u91cf\u00a0type\u00a0\u653e\u5165\u5bc4\u5b58\u5668\u4e2d\uff08\"r\"\u00a0\u6307\u653e\u5165\u5bc4\u5b58\u5668\uff0c\u5982\u679c\u662f\u00a0\"m\"\u00a0\u5219\u4e3a\u653e\u5165\u5185\u5b58\uff09\uff0c\u5e76\u4e14\u7ed1\u5b9a\u5230\u00a0[]\u00a0\u4e2d\u547d\u540d\u7684\u7b26\u53f7\u4e2d\u53bb\u3002[ret_val] \"=r\" (ret_val)\u00a0\u4ee3\u8868\u7740\u5c06\u6c47\u7f16\u6307\u4ee4\u4e2d\u00a0%[ret_val]\u00a0\u7684\u503c\u66f4\u65b0\u5230\u53d8\u91cf\u00a0ret_val \u4e2d\u3002

    e.g. 2

    #define write_csr(reg, val) ({\n__asm__ volatile (\"csrw \" #reg \", %0\" :: \"r\"(val)); })\n

    e.g. 2. \u5b9a\u4e49\u4e86\u4e00\u4e2a\u5b8f\uff0c\u5176\u4e2d\u00a0%0\u00a0\u4ee3\u8868\u7740\u8f93\u51fa\u8f93\u5165\u90e8\u5206\u7684\u7b2c\u4e00\u4e2a\u7b26\u53f7\uff0c\u5373\u00a0val\u3002 #reg\u00a0\u662fc\u8bed\u8a00\u7684\u4e00\u4e2a\u7279\u6b8a\u5b8f\u5b9a\u4e49\u8bed\u6cd5\uff0c\u76f8\u5f53\u4e8e\u5c06reg\u8fdb\u884c\u5b8f\u66ff\u6362\u5e76\u7528\u53cc\u5f15\u53f7\u5305\u88f9\u8d77\u6765\u3002\u4f8b\u5982\u00a0write_csr(sstatus,val)\u00a0\u7ecf\u5b8f\u5c55\u5f00\u4f1a\u5f97\u5230\uff1a

    ({\n__asm__ volatile (\"csrw \" \"sstatus\" \", %0\" :: \"r\"(val)); })\n

    \u6b64\u5916\uff0c\u8fd9\u4e2a\u793a\u4f8b\u4e2d\u7684\u00a0({...})\u00a0\u8fd8\u6d89\u53ca\u4e86\u4e00\u4e2a GNU \u5bf9 C \u7684\u6269\u5c55\uff0c\u53ef\u4ee5\u53c2\u8003\u00a0Statements and Declarations in Expressions\u3002\u590d\u5408\u8bed\u53e5\u4e2d\u7684\u6700\u540e\u4e00\u9879\u5e94\u8be5\u662f\u4e00\u4e2a\u8868\u8fbe\u5f0f\uff0c\u540e\u8ddf\u4e00\u4e2a\u5206\u53f7\u00a0;\u3002\u8be5\u5b50\u8868\u8fbe\u5f0f\u7684\u503c\u7528\u4f5c\u6574\u4e2a\u8bed\u53e5\u7684\u503c\uff0c\u53ef\u4ee5\u7528\u6765\u5b9e\u73b0\u7c7b\u4f3c\u201c\u8fd4\u56de\u503c\u201d\u7684\u6548\u679c\u3002

    "},{"location":"docs/1-cs/os/lab/#_5","title":"\u7f16\u8bd1\u7684\u77e5\u8bc6","text":"

    Note

    \u8fd9\u5757\u6765\u81ea\u4e8e\u5bf9 lab1 \u6587\u6863\u7684\u6574\u7406\u3002\u5e0c\u671b\u6709\u6574\u7406\u5f97\u6bd4\u539f\u6587\u6863\u53ef\u8bfb\u4e00\u4e9b\u3002

    `vmlinux.lds`` \u662f GNU ld\uff0c\u4e00\u79cd\u94fe\u63a5\u5668\uff0c\u5c06 .o \u6587\u4ef6\u548c\u5e93\u6587\u4ef6\u8fde\u63a5\u8d77\u6765\u6210\u53ef\u6267\u884c\u6587\u4ef6\u3002ld\u4f7f\u7528\u94fe\u63a5\u811a\u672clinker script\u63a7\u5236\u3002\u8fd9\u4e2a\u6587\u4ef6\u91cc\u6709\u5199\uff1a

    \u6211\u4eec\u9605\u8bfb\u4e00\u4e0b\u8fd9\u4e2a\u94fe\u63a5\u5668\u6587\u4ef6\uff0c\u5bf9\u4e4b\u540e\u7684\u5b9e\u9a8c\u5e2e\u52a9\u633a\u5927\u3002

    \u9996\u5148\u53ef\u4ee5\u7c97\u7565\u89c2\u5bdf\u5230\uff0ckernel \u7a7a\u95f4\u91cc\u662f\u5206\u6bb5(secition)\u7684\uff0c\u4e3b\u8981\u7684section\u6709\uff1a

    \u6bb5\u540d \u4e3b\u8981\u4f5c\u7528 .text \u901a\u5e38\u5b58\u653e\u7a0b\u5e8f\u6267\u884c\u4ee3\u7801 .rodata \u901a\u5e38\u5b58\u653e\u5e38\u91cf\u7b49\u53ea\u8bfb\u6570\u636e .data \u901a\u5e38\u5b58\u653e\u5df2\u521d\u59cb\u5316\u7684\u5168\u5c40\u53d8\u91cf \u9759\u6001\u53d8\u91cf .bss \u901a\u5e38\u5b58\u653e\u672a\u521d\u59cb\u5316\u7684\u5168\u5c40\u53d8\u91cf \u9759\u6001\u53d8\u91cf

    \u518d\u7ec6\u81f4\u4e00\u70b9\u53bb\u89c2\u5bdf\u91cc\u9762\u7684\u7b26\u53f7\u3002

    \u7f16\u8bd1\u51fa\u7684\u6587\u4ef6\u91cc\uff1a

    "},{"location":"docs/1-cs/os/lab/#risc-v","title":"RISC-V \u65f6\u949f\u4e2d\u65ad","text":"

    \u64cd\u4f5c\u7cfb\u7edf\u5728\u542f\u52a8\u540e\u7531\u4e8b\u4ef6(event)\u9a71\u52a8\uff0c\u6211\u4eec\u5c06\u5f15\u5165\u4e00\u79cd\u4e8b\u4ef6trap\uff0ctrap\u7ed9\u4e86os\u4e0e\u8f6f\u786c\u4ef6\u4ea4\u4e92\u7684\u80fd\u529b\u3002\u5728boot\u9636\u6bb5opensbi\u5b9e\u73b0\u4e86M\u6001\u7684trap\u5904\u7406\u3002\u6211\u4eec\u5b9e\u73b0\u7684\u662fs\u6001\u7684trap\u5904\u7406\u3002

    \u5e76\u4e14\u6211\u4eec\u660e\u786e\u4e00\u4e0b Interrupt, Exception \u548c Trap \u7684\u533a\u522b (from riscv unprivileged spec)\uff1a

    \u5b9e\u9a8c\u624b\u518c\u5219\u7ed9\u4e86\u4e0b\u8868\uff0c\u867d\u7136\u91cc\u9762\u6ca1\u6709\u8bb2\u5230 trap\uff0c\u4f46\u662f\u8fd9\u4e2a\u5bf9\u4e8e interrupt \u548c exception \u7684\u89e3\u91ca\u66f4\u6e05\u695a\u3002

    Interrupt Exception hardware generated software generated Asynchronous external requests (generated by e.g. keyboard or printer) synchronous internal requests for services based upon abnormal events (generated by e.g. illegal instructions, illegal address, overflow, etc.) normal events abnormal events

    \u7406\u89e3\u4e86\u4e0a\u8ff0\u4e24\u4e2a\u6982\u5ff5\u540e\u53ef\u4ee5\u628a trap \u5f53\u4f5c\u4e00\u79cd\u7edf\u79f0\uff0c\u53ef\u4ee5\u7406\u89e3\u4e3a trap = interrupt + exception\u3002\u6211\u4eec\u540e\u7eed\u5b9e\u73b0\u7684 trap_handler() \u65e2\u8981\u5904\u7406\u4e2d\u65ad\u4e5f\u8981\u5904\u7406\u5f02\u5e38\u3002

    \u8981\u5b9e\u73b0\u7684\u4e2d\u65ad\u7684\u6d41\u7a0b\u5982\u4e0b\uff0c\u53ef\u4ee5\u53c2\u7167\u8fd9\u4e2a\u5b8c\u6210 do_timer() switch_to() schedule() \u7b49\u51fd\u6570\uff1a

    "},{"location":"docs/1-cs/os/lab/#riscv","title":"RISCV \u5bc4\u5b58\u5668","text":"

    \u56de\u5fc6\u5185\u5b58\u7ed3\u6784\uff08\u5982\u679c\u4f60\u660e\u786e\u77e5\u9053\u5bc4\u5b58\u5668\u662f\u4ec0\u4e48\u5c31\u4e0d\u7528\u56de\u5fc6\u4e86\uff09\uff0c\u53ef\u89c1\u5bc4\u5b58\u5668\u5e76\u4e0d\u5728\u8fd0\u884c\u5185\u5b58\u91cc\uff1a

    \u5c0f/\u5feb <---------------> \u5927/\u6162\n[\u5bc4\u5b58\u5668] - [cache] - [\u5185\u5b58] - [\u5916\u5b58]\n

    riscv\u670932\u4e2a\u901a\u7528\u5bc4\u5b58\u5668 + \u5f88\u591a\u63a7\u5236\u72b6\u6001\u5bc4\u5b58\u5668 (control and status registers (CSRs))\u3002riscv \u7ed9\u6bcf\u4e2a\u5bc4\u5b58\u5668\u6709\u4e2a\u5143\u4fe1\u606f\uff0c\u8fd9\u4e2a\u5143\u4fe1\u606f\u5171\u7528 12-bit \u6765\u5b58\u50a8\u5373 csr[11:0]\uff0c\u6240\u4ee5\u4e00\u5171\u652f\u6301 4096 \u4e2a\u5bc4\u5b58\u5668\u3002\u5177\u4f53\u800c\u8a00\uff0ccsr[11:0] \u8fd9\u4e2a\u6570\u636e\u7ed3\u6784\u6bcf\u4e2a\u4f4d\u7684\u610f\u4e49\u5206\u914d\u5982\u4e0b\uff1a

    \u4f4d\u6570 11:10 9:8 7:4 \u957f\u5ea6 2 2 4 \u4f5c\u7528 11=read-only\uff0cother=read/write\uff1f \u80fd\u8bbf\u95ee\u8be5csr\u7684\u6700\u4f4e\u7684\u6743\u9650\u6a21\u5f0f \u6211\u731c\u662f\u4fdd\u7559\u7ed9\u6bcf\u4e2acsr\u7279\u5b9a\u7684

    \u9996\u5148\uff0c\u901a\u7528\u5bc4\u5b58\u5668\u6709\u5982\u4e0b\u8fd9\u4e9b\uff1a

    \u5728\u7f16\u5199\u6c47\u7f16\u4ee3\u7801\u7684\u65f6\u5019\u4e00\u822c\u4f7f\u7528\u5bc4\u5b58\u5668\u7684abi\u7684\u540d\u5b57\u800c\u4e0d\u662f\u5bc4\u5b58\u5668\u7684\u7f16\u53f7

    \u800c\u4e0b\u9762\u8981\u5355\u72ec\u8bb2\u4e00\u4e0b csr\u3002

    sstatus (supervisor status register)

    The sstatus register is an SXLEN(\u4ee3\u886832\u621664)-bit read/write register formatted as follows. \u6211\u4eec\u7528\u7684\u662f64\u4f4d\u3002

    \u4e5f\u5c31\u662f\u8bf4\u8fd9\u4e2a\u5bc4\u5b58\u5668\u628a\u5f88\u591a\u4e8b\u4ef6\u7684\u72b6\u6001\u90fd\u75280\u62161\u8868\u793a\uff0c\u62fc\u5230\u4e86\u540c\u4e00\u4e2a\u5bc4\u5b58\u5668\u91cc\u3002

    \u4f4d\u6570 \u540d\u79f0 \u7f6e1\u8868\u793a \u7f6e0\u8868\u793a 1 SIE \u54cd\u5e94\u6240\u6709\u7684S\u6001trap \u7981\u7528\u6240\u6709S\u6001trap 5 SPIE \u5728trap\u53d1\u751f\u524d\u7684SIE=1 \u5728trap\u53d1\u751f\u524d\u7684SIE=0 8 SPP \u5f53\u4e2d\u65ad\u53d1\u751f\u5b8c\u7684\u65f6\u5019\uff0c\u8fd4\u56de\u5230S-mode \u5f53\u4e2d\u65ad\u53d1\u751f\u5b8c\u7684\u65f6\u5019\uff0c\u8fd4\u56de\u5230U-mode

    \u624b\u518c\u91cc\u8fd8\u4ecb\u7ecd\u7684\u4f4d\u6709

    sie (supervisor interrupt enable register)

    \u5982\u679c\u5f00\u542f\u4e86sstatus[SIE]\uff0c\u5c31\u4f1a\u6839\u636esie\u4e2d\u7684\u6bd4\u7279\u4f4d\uff0c\u51b3\u5b9a\u662f\u5426\u5904\u7406interrupt

    Bits sip.SEIP and sie.SEIE are the interrupt-pending and interrupt-enable bits for supervisor- level external interrupts. If implemented, SEIP is read-only in sip, and is set and cleared by the execution environment, typically through a platform-specific interrupt controller. Bits sip.STIP and sie.STIE are the interrupt-pending and interrupt-enable bits for supervisor- level timer interrupts. If implemented, STIP is read-only in sip, and is set and cleared by the execution environment. Bits sip.SSIP and sie.SSIE are the interrupt-pending and interrupt-enable bits for supervisor- level software interrupts. If implemented, SSIP is writable in sip and may also be set to 1 by a platform-specific interrupt controller.

    stvec (supervisor trap vector base address register)

    \u4e2d\u65ad\u5411\u91cf\u8868\u57fa\u5740.

    WARL\u662f\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f\u7684\u5730\u5740

    MODE\u662f

    Value mode \u63cf\u8ff0 0 Direct \u6a21\u5f0f \u9002\u7528\u4e8e\u7cfb\u7edf\u4e2d\u53ea\u6709\u4e00\u4e2a\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f, \u5176\u6307\u5411\u4e2d\u65ad\u5904\u7406\u5165\u53e3\u51fd\u6570 \uff08 \u672c\u5b9e\u9a8c\u4e2d\u6211\u4eec\u6240\u7528\u7684\u6a21\u5f0f \uff09 1 Vectored\u6a21\u5f0f \u6307\u5411\u4e2d\u65ad\u5411\u91cf\u8868\uff0c \u9002\u7528\u4e8e\u7cfb\u7edf\u4e2d\u6709\u591a\u4e2a\u4e2d\u65ad\u5904\u7406\u7a0b\u5e8f \u22652 \u4fdd\u7559

    sscratch (supervisor scratch register)

    Typically, sscratch is used to hold a pointer to the hart-local supervisor context while the hart is executing user mode. At the beginning of a trap handler, sscratch is swapped with a user register to provide an initial working register.

    \u5728\u672c\u6b21\u5b9e\u9a8c\u4e2d\uff0c\u6211\u4eec\u62ffsscratch\u8bb0\u5f55s-mode\u7684stack pointer\uff0c\u5728trap\u53d1\u751f\u7684\u65f6\u5019\u4e0eu-mode stack pointer\u4ea4\u6362\uff08\u597d\u50cf\u662f\u6765\u7740\u5fd8\u4e86TODO\u4e00\u4f1a\u6838\u5b9e\uff09

    sepc (supervisor exception program counter)

    \u4f1a\u8bb0\u5f55 trap \u5904\u7406\u8fc7\u540e\u7684\u8fd4\u56de\u5730\u5740\u3002

    scause (supervisor cause register)

    \u4f1a\u8bb0\u5f55 trap \u53d1\u751f\u7684\u539f\u56e0\uff0c\u8fd8\u4f1a\u8bb0\u5f55\u8be5 trap \u662f\u00a0Interrupt\u00a0\u8fd8\u662f\u00a0Exception\u3002\u539f\u56e0\u6709\u4ee5\u4e0b\u51e0\u79cd\uff1a

    stval (supervisor trap value register)

    The stval register can optionally also be used to return the faulting instruction bits on an illegal instruction exception (sepc points to the faulting instruction in memory). If stval is written with a nonzero value when an illegal-instruction exception occurs, then stval will contain the shortest of:

    \u0088 the actual faulting instruction \u0088 the first ILEN bits of the faulting instruction \u0088 the first SXLEN bits of the faulting instruction

    The value loaded into stval on an illegal-instruction exception is right-justified and all unused upper bits are cleared to zero.

    satp (supervisor address translation and protection register)

    \u8bb0\u5f55\u6700\u9ad8\u7ea7\u9875\u8868\u7684\u7269\u7406\u5730\u5740\u3002MODE\u4f4d=8\u65f6\uff0c\u4f7f\u7528Sv39\u6a21\u5f0f\u865a\u62df\u5730\u5740\uff08\u672c\u5b9e\u9a8c\uff09

    \u4ee5\u4e0b\u662f\u65f6\u949f\u4e2d\u65ad\u76f8\u5173\u7684\u5bc4\u5b58\u5668\uff1a

    mtime

    \u8ba1\u65f6\u5668\uff0c\u4ee5\u6052\u5b9a\u9891\u7387\u81ea\u589e\uff08\u6211\u8bb0\u5f97\u5728\u672c\u5b9e\u9a8c\u91cc\u662f\u591a\u5c11\u5206\u4e4b\u4e00\u79d2\uff09

    mtimecmp\uff08machine timer register\uff09

    \u4e0b\u4e00\u6b21\u65f6\u949f\u4e2d\u65ad\u7684\u4e2d\u65ad\u70b9

    mcounteren\uff08counter enable register\uff09

    \uff08\u672c\u5b9e\u9a8c\u4e2d\u4e0d\u7528\u7ba1\uff0c\u4f46\u662f\u8bf4\u660e\u4e00\u4e0b\uff1a\uff09mtime\u672c\u6765\u662fm\u6001\u7684\u5bc4\u5b58\u5668\uff0c\u5728s\u6001\u4e0d\u80fd\u8bfb\u5199\uff0c\u4f46\u662fopensbi\u5df2\u7ecf\u8bbe\u7f6e\u8fc7\u53ef\u4ee5\u8bfb\u5199m\u6001

    "},{"location":"docs/1-cs/os/lab/#_6","title":"\u5bc4\u5b58\u5668\u64cd\u4f5c","text":"

    \u64cd\u4f5ccsr\u5bc4\u5b58\u5668\u7684riscv\u6307\u4ee4\u96c6 TODO\u5f85\u6574\u7406

    func scr rs1 rd

    \u5316\u7528\u4e00\u4e2a\u6682\u65f6\u4e0d\u60f3\u53bb\u627e\u6765\u6e90\u7684 CSDN \u5e16\u5b50\u7684\u603b\u7ed3\uff1a

    "},{"location":"docs/1-cs/os/lab/#lab2","title":"lab2","text":""},{"location":"docs/1-cs/os/lab/#_7","title":"\u7ebf\u7a0b","text":"

    \u672c\u5b9e\u9a8c\u5efa\u7acb\u7684\u7ebf\u7a0b\u90fd\u662f\u5185\u6838\u6001\u7ebf\u7a0b\u3002\u4e00\u4e2a\u4f9d\u636e\u5c31\u662f\u67d0\u4e2a\u7ebf\u7a0b trap \u540e\u4e0d\u4f1a\u963b\u585e\u5176\u5b83\u7ebf\u7a0b\u3002

    \u7ebf\u7a0b\u7684 task_struct \u53ef\u4ee5\u7406\u89e3\u4e3a\u7406\u8bba\u8bfe\u4e0a\u8bb2\u7684 PCB (\u662f\u4e0d\u662f\u8be5\u53eb TCB\uff1f)\u3002\u91cc\u9762\u7684\u4e1c\u897f\u4f1a\u968f\u7740\u9010\u4e2a lab \u6dfb\u52a0\u8fdb\u53bb\uff0c\u6700\u7ec8\u4f1a\u6709\u4ee5\u4e0b\u4e1c\u897f\uff1a

    Warning

    TODO \u4ee5\u4e0b\u5185\u5bb9\u9700\u8981\u518d\u68c0\u67e5\uff0c\u5ffd\u7136\u5206\u4e0d\u6e05\u6bcf\u4e2a\u7ebf\u7a0b\u603b\u5171\u662f\u5f00\u4e86\u4e00\u4e2a\u8fd8\u662f\u4e24\u4e2a\u5185\u5b58\u7a7a\u95f4

    \u7ebf\u7a0b\u5185\u5b58\u7a7a\u95f4\u7ed3\u6784\u5982\u4e0b\u3002

    \u5185\u6838\u865a\u62df\u5b58\u50a8\u5668 \u7528\u6237\u4e0d\u53ef\u89c1\u7684\u5b58\u50a8\u5668 0xc000 0000 \u7528\u6237\u6808 \u2190 sp 0x4000 0000 \u5171\u4eab\u5e93\u7684\u5b58\u50a8\u5668\u6620\u5c04\u533a\u57df \u8fd0\u884c\u65f6\u5806\uff08\u7531malloc\u521b\u5efa\uff09 \u2190 brk \u8bfb\u5199\u6bb5 .data .bss \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d \u53ea\u8bfb\u6bb5 .init .text .rodata \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d 0x0804 8000 \u672a\u7528\u7684 \u4ece\u53ef\u6267\u884c\u6587\u4ef6\u52a0\u8f7d"},{"location":"docs/1-cs/os/lab/#lab3","title":"lab3","text":"

    \u5230\u672c\u5b9e\u9a8c\u7ed3\u675f\u65f6\uff0c\u6211\u4eec\u7684\u7a0b\u5e8f\u5c06\u8981\u5b9e\u73b0\u8fd9\u6837\u4e00\u4e2a\u4ece\u542f\u52a8\u5230\u5f00\u542f\u6620\u5c04\u7684\u8fc7\u7a0b\uff08\u4e5f\u5bf9\u5e94 head.S \u5f00\u5934\u7684\u4e00\u5806\u51fd\u6570\u8c03\u7528\u6d41\u7a0b\uff09\uff1a

    "},{"location":"docs/1-cs/os/lab/#virtual-memory","title":"virtual memory","text":"

    lab2\u4e2d\u6211\u4eec\u505a\u7684\u90fd\u662f\u5185\u6838\u7ebf\u7a0b\uff0c\u53ef\u4ee5\u5171\u4eab\u8fd0\u884c\u7a7a\u95f4\uff0c\u5373\u8fd0\u884c\u4e0d\u540c\u7ebf\u7a0b\u5bf9\u5185\u8bad\u7684\u4fee\u6539\u662f\u76f8\u4e92\u53ef\u89c1\u7684\u3002\u5982\u679c\u9700\u8981\u7ebf\u7a0b\u76f8\u4e92\u9694\u79bb\u5c31\u9700\u8981\u5f15\u5165\u865a\u62df\u5185\u5b58\uff0c\u65b9\u4fbf\u591a\u7ebf\u7a0b\u9ad8\u6548\u5171\u4eab\u5185\u5b58\u3002\u5982\u679c\u5f88\u865a\u5730\u53bb\u8bb2\u865a\u62df\u5185\u5b58\u7684\u4f5c\u7528\uff1a

    \u6211\u4eec\u8981\u5b9e\u73b0\u7684\u865a\u62df\u5185\u5b58\u5e03\u5c40\uff0c\u9996\u5148\u7528\u4e00\u4e2a\u622a\u56fe\u6765\u7406\u89e3\uff1a

    \u4f4e\u5730\u5740<-                                       ->\u9ad8\u5730\u5740\n\nstart_address             end_address\n    0x0                  0x3fffffffff\n     \u2502                        \u2502\n\u250c\u2500\u2500\u2500\u2500\u2518                  \u250c\u2500\u2500\u2500\u2500\u2500\u2518\n\u2193        256G           \u2193                                \n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502      User Space       \u2502    ...   \u2502  Kernel Space  \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n                                   \u2191      256G      \u2191\n                      \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518                \u2502 \n                      \u2502                             \u2502\n              0xffffffc000000000           0xffffffffffffffff\n                start_address                  end_address\n

    \u7136\u540e\u5fc5\u987b\u8981\u641e\u660e\u767d\uff1a\u865a\u62df\u5185\u5b58\u4ece\u6765\u6ca1\u6709\u88ab\u771f\u6b63\u5f00\u8f9f\u8fc7\uff0c\u88ab\u771f\u6b63\u5f00\u8f9f\u7684\u53ea\u6709\u7269\u7406\u5185\u5b58\u3002\u6211\u4eec\u5728\u7a0b\u5e8f\u5b9e\u73b0\u8fc7\u7a0b\u4e2d\u5f00\u7684\u53d8\u91cf\u548c alloc \u7684 page\uff0c\u90fd\u662f\u5f00\u5728 kernel \u7684\u6808\u6216\u8005\u5806\u4e0a\uff08.data\u548c.bss\u6bb5\uff09\uff0c\u56e0\u4e3a\u67e5\u5730\u5740\u65f6\u53ef\u4ee5\u67e5\u5230\u5b83\u4eec\u7684\u7269\u7406\u5730\u5740\u3002\u800c\u5404\u79cd csr \u5728 cpu \u91cc\uff0c\u4e0d\u4f1a\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\u3002\u800c\u672c\u6b21\u5b9e\u9a8c\u6240\u8bb2\u7684\u201c\u5f00\u542f\u865a\u62df\u5185\u5b58\u201d\uff0c\u672c\u8d28\u4e0a\u53ea\u662f\u8bbe\u8ba1\u4e00\u4e2a\u865a\u62df\u5730\u5740\u5230\u7269\u7406\u5730\u5740\u7684\u8f6c\u6362\u51fd\u6570\uff0c\u8fd9\u4e2a\u51fd\u6570\u653e\u5728\u9875\u8868\u91cc\u3002

    "},{"location":"docs/1-cs/os/lab/#sv39","title":"Sv39 \u7684\u9875\u8868\u9879","text":"

    \u7406\u89e3\u4e00\u4e0b\u9875\u8868\u9879\uff08pte\uff09\u3002\u5b83\u7684\u4f4e\u4f4d\uff1a

    "},{"location":"docs/1-cs/os/lab/#_8","title":"\u5730\u5740\u7ffb\u8bd1\u8fc7\u7a0b","text":"

    create_mapping() \u51fd\u6570\u904d\u5386\u6574\u4e2a\u6620\u5c04\u5927\u5c0f\uff0c\u4f9d\u6b21\u6309\u4e8c\u7ea7\u9875\u8868\uff08\u5373\u6839\u9875\u8868\u7684\u4e0b\u4e00\u7ea7\uff09\u2192\u4e09\u7ea7\u9875\u8868\u2192\u7269\u7406\u9875\uff0c\u68c0\u67e5\u9875\u8868\u9879\u7684V bit\u770b\u9875\u8868\u9879\u662f\u5426\u5b58\u5728\uff0c\u4e0d\u5b58\u5728\u5219\u7528kalloc() \u5206\u914d\u4e00\u9875\u4f5c\u4e3a\u9875\u8868\u76ee\u5f55\uff1b\u5b58\u5728\u5219\u5728\u9875\u8868\u9879\u4e2d\u8bb0\u5f55\u9875\u8868\u7684\u7269\u7406\u5730\u5740\u3002

    pte : [ PPN2: 53-28 ][ PPN1: 27-19 ][ PPN0: 18-10 ][ perm: 9-0 ]

    vm_addr: [ VPN2: 38-30 ][ VPN1: 29-21 ][ VPN0:20-12 ][ offset: 11-0 ]

    \u56e0\u4e3a\u67e5\u8be2\u4e09\u7ea7\u9875\u8868\u7684\u6d41\u7a0b\u4e3a\uff1a

    \u6240\u4ee5\u53cd\u63a8\u8bbe\u7f6e\u7684\u6d41\u7a0b\u4e3a\uff1a

    "},{"location":"docs/1-cs/os/lab/#heads-todo-va2pa_offset","title":"\u4e3a\u4ec0\u4e48\u5728 head.S \u91cc\u4e00\u5f00\u59cb\u8981\u7ed9\u9875\u8868\u9879\u5730\u5740 (TODO\u574f\u4e86\u4e0d\u8bb0\u5f97\u662f\u4e0d\u662f\u5b83\u4e86) \u51cf\u53bb\u4e00\u4e2a VA2PA_offset","text":"

    \u5728 2023 \u5e74\u7248\u7684\u5b9e\u9a8c\u4e2d\uff0cvmlinux.lds \u4e2d\u8bbe\u7f6e\u4e86\u5c06\u7f16\u8bd1\u51fa\u7684\u7b26\u53f7\u8868\u90fd\u7528\u865a\u62df\u5730\u5740\u6765\u8868\u793a\uff0c\u65b9\u4fbf\u8c03\u8bd5\u3002\u4e5f\u5373\u7a0b\u5e8f\u8fd0\u884c\u5230\u6b64\u5904\u8bfb\u5230\u7684\u9875\u8868\u9879\u5730\u5740\u662f\u865a\u62df\u5730\u5740\u3002\u663e\u7136\uff0c\u5728 setup_vm() \u4e4b\u524d\uff0c\u865a\u62df\u5185\u5b58\u8fd8\u6ca1\u6709\u88ab\u5f00\u542f\uff0c\u6240\u4ee5\u8981\u51cf\u6389\u4e00\u4e2a\u504f\u79fb\u91cf\u4f7f\u5176\u80fd\u8bfb\u5230\u9875\u8868\u9879\u7684\u7269\u7406\u5730\u5740\u3002\u5728 relocate: \u5904\u7406\u504f\u79fb\u4e4b\u540e\u5c31\u4e0d\u7528\u7ba1\u4e86\u3002

    "},{"location":"docs/1-cs/os/lab/#lab4","title":"lab4","text":""},{"location":"docs/1-cs/os/lab/#_9","title":"\u66f4\u65b0\u540e\u7684\u865a\u62df\u5185\u5b58\u5e03\u5c40","text":"

    \u6211\u4eec\u56de\u5fc6 lab3 \u91cc\u865a\u62df\u5730\u5740\u53ea\u7528\u4e86\u9ad8\u4f4d\uff0c\u4f4e\u4f4d\u6ca1\u6709\u7528\uff0c\u5728\u672c\u5b9e\u9a8c\u6211\u4eec\u8981\u5c06\u4f4e\u4f4d 0x0-0x4000000 \u5206\u7ed9\u7528\u6237\u8fdb\u7a0b\u3002\u800c\u7528\u6237\u8fdb\u7a0b\u7684\u4ee3\u7801\u5b9e\u9645\u5728\u7269\u7406\u5730\u5740\u4e0a\u5206\u914d\u51fa\u6765\u7684\u67d0\u4e2a\u5730\u65b9\u3002\u603b\u4e4b\uff0c\u8981\u5b9e\u73b0\u4ee5\u4e0b\u7684\u5185\u5b58\u5e03\u5c40\uff1a

                   PHY_START   new allocated memory            allocated space end                              PHY_END\n                   \u2502         \u2502                                \u2502                                                 \u2502\n                   \u25bc         \u25bc                                \u25bc                                                 \u25bc\n       \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n PA    \u2502           \u2502         \u2502 uapp (copied from _sramdisk)   \u2502                                                 \u2502\n       \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n                             \u25b2                                \u25b2\n       \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518                                \u2502\n       \u2502            (map)                                     \u2502\n       \u2502                        \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n       \u2502                        \u2502\n       \u2502                        \u2502\n       \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n VA    \u2502           UAPP         \u2502                                                                   \u2502u mode stack\u2502\n       \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n       \u25b2                                                                                                         \u25b2\n       \u2502                                                                                                         \u2502\n\n   USER_START                                                                                                USER_END\n
    "},{"location":"docs/1-cs/os/lab/#riscv_1","title":"riscv\u5904\u7406\u5668\u652f\u6301\u7684\u6a21\u5f0f","text":"

    lab3\u521b\u5efa\u7684\u90fd\u662f\u5185\u6838\u7ebf\u7a0b \u516c\u7528\u4e86\u5730\u5740\u7a7a\u95f4\uff08\u9875\u8868swapper_pg_dir\uff09\u3002\u8981\u5f15\u5165\u7528\u6237\u6001\u8fdb\u7a0b\u9700\u8981\u505a\uff1a

    \u5177\u4f53\u5728\u6211\u4eec\u7684\u5b9e\u9a8c\u64cd\u4f5c\u4e2d\uff0c\u5b9e\u73b0\u7528\u6237\u6001\u548c\u5185\u6838\u6001\u5207\u6362\u7684\u65b9\u6cd5\u662f\uff1asstatus[SUM] \u548c PTE[U]

    Warning

    \u60f3\u5199\u4e00\u4e0b\u5728\u6c47\u7f16\u4ee3\u7801\u91cc\u7684\u64cd\u4f5c\uff0c\u5fd8\u5e72\u51c0\u4e86\uff0c\u6574\u4f53\u601d\u8def\u662f\u8fd9\u6837\u7684\uff0c\u4f46\u4e00\u4e9b\u7ec6\u8282\u5f85\u6838\u5b9e

    \u5e76\u4e14\u5728\u6c47\u7f16\u4ee3\u7801\u91cc\u9700\u8981\u5b9e\u73b0\u4e00\u7cfb\u5217 csr \u8bfb\u5199\u64cd\u4f5c\uff1a

    "},{"location":"docs/1-cs/os/lab/#buddy-system","title":"buddy system","text":"

    \u4e00\u79cd\u7269\u7406\u5185\u5b58\u7ba1\u7406\u7b97\u6cd5\uff0c\u7a7a\u95f2\u7a7a\u95f4\u9996\u5148\u88ab\u770b\u6210 2^N \u4e2a\u7269\u7406\u9875\u7684\u5927\u7a7a\u95f4\uff0c\u5f53\u4e00\u4e2a\u5927\u5c0f\u4e3a m \u7684\u9875\u8bf7\u6c42\u5185\u5b58\u5206\u914d\u65f6\uff0c\u4e0d\u505c\u628a\u7a7a\u95f4 /2 \u5212\u5206\uff0c\u6700\u540e\u627e\u5230\u6700\u63a5\u8fd1m\u76842\u7684\u6b21\u65b9\u7684\u4e00\u4e2a\u7a7a\u95f4\u5927\u5c0f\u5206\u7ed9 m\u3002\u5f53\u5757\u91ca\u653e\u65f6\uff0c\u5206\u914d\u5668\u5c31\u4f1a\u627e\u5230\u5176\u5b83\u7a7a\u95f2\u7684\u4f19\u4f34\u5757\u53bb\u5408\u5e76\u3002\u5b83\u7684\u5b9e\u73b0\u5728\u8fd9\u4e2a\u6587\u7ae0\u91cc\u8bb2\u5f97\u66f4\u597d Lab 6\uff1aRISC-V \u52a8\u6001\u5185\u5b58\u5206\u914d\u4e0e\u7f3a\u9875\u5f02\u5e38\u5904\u7406 - \u77e5\u4e4e (zhihu.com)\u3002

    "},{"location":"docs/1-cs/os/lab/#elf","title":"elf \u6587\u4ef6","text":"

    \u4e00\u4e2a elf \u6587\u4ef6\u50cf\u4e00\u4e2a\u5c01\u88c5\u590d\u6742\u7248\u7684\u4e8c\u8fdb\u5236\u7528\u6237\u7a0b\u5e8f\u3002\u7528\u62bd\u8c61\u7684\u753b\u56fe\u7ed9\u5b83\u7684\u7ed3\u6784\u505a\u4e00\u4e2a\u6bd4\u55bb\uff08\u5bf9\u4e0d\u8d77\u592a\u62bd\u8c61\u4e86\uff09\uff1a

    Elf_Ehdr     ehdr->e_phoff\n\u2b07\ufe0f            \u2b07\ufe0f\n[            [type: ???][type: LOAD][type: ???] ]\n

    \u5c31\u662f elf \u6587\u4ef6\u91cc\u6563\u843d\u7740\u51e0\u4e2a\u5c0f\u6bb5\uff0c\u5176\u4e2d\u4e00\u4e2a\u7c7b\u578b\u4e3a LOAD \u7684\u6bb5\u662f\u9700\u8981\u590d\u5236\u5230\u7ebf\u7a0b\u4ee3\u7801\u6bb5\u7684\uff0c\u4f46\u4e0d\u4e00\u5b9a\u590d\u5236\u5230\u7ebf\u7a0b\u5934\u7684\u8d77\u59cb\u5730\u5740 0x0\uff0cp_vaddr \u4f1a\u544a\u8bc9\u4f60\u8fd9\u6bb5\u4ee3\u7801\u5e0c\u671b\u88ab\u590d\u5236\u5230\u54ea\u91cc\u53bb\u3002e_entry \u4e5f\u8d34\u5fc3\u544a\u8bc9\u4f60\u7b2c\u4e00\u6761\u4ee3\u7801\u6307\u4ee4\u7684\u8d77\u59cb\u5730\u5740\u5728\u54ea\u3002\u603b\u4e4b\uff0c\u4f60\u9700\u8981\u5148\u901a\u8fc7\u4e00\u4e9b\u504f\u79fb\u91cf\u5728 Elf64_Ehdr \u8fd9\u4e2a\u6307\u9488\u91cc\u627e\u5230\u7b2c\u4e00\u4e2a segment\uff0c\u7136\u540e\u4ee5\u4e00\u4e2a Elf63_phdr \u7684\u5927\u5c0f\u4e3a\u5355\u4f4d\uff0c\u6328\u4e2a\u53bb\u5bfb\u627e\u4e00\u4e2a\u7c7b\u578b\u4e3a LOAD \u7684 segment\u3002\u7b49\u627e\u5230\u4e86\u5c31\u53ef\u4ee5\u62f7\u8d1d\u4e86\u3002

    \u5982\u679c\u4f60\u6309\u7167\u4e00\u5806\u6307\u9488\u7684\u5199\u6cd5\u88ab\u641e\u5f97\u6655\u5934\u8f6c\u5411\uff0c\u751a\u81f3\u53ea\u662f\u5148\u7528 readelf -h \u67e5\u770b\u4e00\u4e0b elf \u6587\u4ef6\u91cc\u5404\u4e2a\u4e1c\u897f\u7684\u5730\u5740\uff08\u67e5\u770b\u540e\u53ef\u4ee5\u53d1\u73b0\u4e0e\u5b9e\u9a8c\u6307\u5bfc\u4e2d\u7ed9\u7684\u4f8b\u5b50\u5c31\u662f\u540c\u4e00\u4e2a\u6587\u4ef6\uff09\uff0c\u7136\u540e\u76f4\u63a5\u628a\u6574\u4e2a uapp \u7a0b\u5e8f\u5168\u90e8\u62f7\u5230\u8fdb\u7a0b\u91cc\u6765\uff0c\u76f4\u63a5\u628a __dummy \u8fd4\u56de\u5730\u5740\u6307\u5230\u4f60\u5728\u6587\u4ef6\u91cc\u8bfb\u51fa\u6765\u7684\u90a3\u4e2a\u4ee3\u7801\u8d77\u59cb\u5730\u5740\uff0c\u751a\u81f3\u90fd\u80fd\u8dd1\u3002\u5728\u8dd1\u8d77\u6765\u4e4b\u540e\uff0c\u6839\u636e\u4f60\u7684\u7406\u89e3\u4e00\u70b9\u4e00\u70b9\u628a\u8bbe\u7f6e\u6307\u9488\u7684\u4ee3\u7801\u6309\u7167\u542b\u4e49\u66ff\u6362\u4e0a\uff0c\u6211\u611f\u89c9\u8fd9\u6837\u53cd\u7740\u505a\u4e5f\u884c\u3002

    "},{"location":"docs/1-cs/os/lab/#lab5","title":"lab5","text":"

    Warning

    \u4e0b\u9762\u51e0\u4e2a\u5b9e\u9a8c\u6211\u5199\u5f97\u6709\u70b9\u7b80\u7565\uff0c\u5c0f\u90e8\u5206\u56e0\u4e3a\u6211\u4e0d\u8bb0\u5f97\u4e86\uff0c\u5927\u90e8\u5206\u56e0\u4e3a\u6211\u81ea\u6211\u611f\u89c9\u6ca1\u6709\u5403\u900f\u8fd9\u4e2a\u5b9e\u9a8c\uff0c\u4e0d\u73ed\u95e8\u5f04\u65a7\u4e86\u3002\u4f46\u662f\u8fd9\u4e2a\u5730\u65b9\u53d1\u81ea\u5185\u5fc3\u5730\u60f3\u7559\u4e2a TODO \u5e0c\u671b\u80fd\u6709\u673a\u4f1a\u8865\u5b8c\u3002

    \u672c\u5b9e\u9a8c\u4e0e lab4 \u5185\u5b58\u5206\u914d\u7684\u533a\u522b\u662f\uff0c\u4e3a\u4e86\u9632\u6b62\u7269\u7406\u5185\u5b58\u4e0d\u8db3\uff0c\u5728 task \u521d\u59cb\u5316\u8bf7\u6c42\u7a7a\u95f4\u65f6\uff0c\u5148\u4e0d\u5206\u914d\u7269\u7406\u5185\u5b58\uff0c\u800c\u662f\u7528 do_mmap() \u5148\u628a task \u7684\u8bf7\u6c42\u7684\u6240\u6709\u53c2\u6570\u8bb0\u5f55\u4e0b\u6765\uff0c\u7b49 task \u771f\u6b63\u53bb\u8bbf\u95ee\u7684\u65f6\u5019\uff0c\u5fc5\u7136\u4f1a\u89e6\u53d1 page fault\uff0c\u7136\u540e\u5728 page fault handler \u91cc\u6839\u636e\u8bb0\u5f55\u7684\u53c2\u6570\uff0c\u518d\u5206\u914d\u7269\u7406\u5185\u5b58\u3002

    "},{"location":"docs/1-cs/os/lab/#lab6","title":"lab6","text":"

    \u5b9e\u9a8c\u4e3b\u8981\u76ee\u6807\u662f\u5b9e\u73b0\u521b\u5efa\u5b50\u8fdb\u7a0b\u7684\u903b\u8f91\uff0c\u5373\u5728\u7528\u6237\u7a0b\u5e8f\u8c03\u7528fork()\u51fd\u6570\uff0c\u4ea7\u751f220\u53f7\u7cfb\u7edf\u8c03\u7528\u7684\u65f6\u5019\uff0c\u5728sys_clone()\u8fd9\u4e2a\u51fd\u6570\u91cc\u521b\u5efa\u5b50\u8fdb\u7a0b\uff0c\u5e76\u4f7f\u5176\u52a0\u5165\u88ab\u8c03\u7528\u7684task\u961f\u5217\u3002

    "},{"location":"docs/1-cs/os/lab/#lab7","title":"lab7","text":"

    Warning

    lab7 \u6211\u53ea\u5b8c\u6210\u4e86\u5360 60% \u7684\u7b2c\u4e00\u90e8\u5206\uff0c\u4f46\u5176\u5b9e\u5de5\u4f5c\u91cf\u6bd4\u8f83\u5927\u7684\u8fd8\u5728\u7b2c\u4e8c\u90e8\u5206\u3002\u6211\u8fd9\u91cc\u53ea\u80fd\u603b\u7ed3\u7b2c\u4e00\u90e8\u5206\u4e86\u3002

    \u672c\u5b9e\u9a8c\u6bcf\u4e2atask\u90fd\u6709\u4e00\u4e2a\u7ed3\u6784\u4f53\u53bb\u7ef4\u62a4\u5df2\u7ecf\u6253\u5f00\u7684\u6587\u4ef6\u8868\u3002\u672c\u5b9e\u9a8c\u9996\u5148\u4fee\u6539task struct\uff0c\u5728\u6bcf\u4e2atask struct\u4e2d\u6dfb\u52a0\u4e86\u4e00\u4e2a\u9875(struct file* \u578b)\u53bb\u7ef4\u62a4\u8fd9\u4e2a\u6587\u4ef6\u8868\u3002

    \u6bcf\u4e2a\u6587\u4ef6\u8868\u6709\u4e00\u4e9b\u51fd\u6570\u6307\u9488\uff0c\u5206\u522b\u6307\u5411\u5bf9\u6587\u4ef6\u7684\u8bfb\u5199\u64cd\u4f5c\u51fd\u6570\u3002\u9996\u5148\u9700\u8981\u5b9e\u73b0\u8fd9\u4e9b\u51fd\u6570\uff0c\u5982 stdout_write() \u548c stdin_read() \u7b49\u3002

    \u5f53\u7528\u6237\u7a0b\u5e8f\u4ea7\u751f\u6587\u4ef6\u8bfb\u5199\u7684 system call \u65f6\uff0ctrap_handler() \u4e2d\u9700\u8981\u5b9e\u73b0\u5bf9\u8fd9\u4e9b system call \u7684\u5904\u7406\u51fd\u6570\u3002\u5177\u4f53\u64cd\u4f5c\u5c31\u662f\u6355\u83b7\uff0c\u7136\u540e\u4ec0\u4e48\u4e5f\u4e0d\u505a\uff0c\u76f4\u63a5\u628a\u53c2\u6570\u4ea4\u7ed9\u4e0a\u8ff0\u5b9e\u73b0\u7684\u6587\u4ef6\u8bfb\u5199\u51fd\u6570\u6765\u64cd\u4f5c\u3002

    "},{"location":"docs/1-cs/os/lab/#_10","title":"\u5e38\u89c1\u95ee\u9898\u4e4b\u8865\u5145\u53c8\u540d\u6211\u4e4b\u603b\u662f\u9047\u89c1\u95ee\u9898","text":"

    Q1: \u8fd0\u884c\u53d1\u73b0\u7a0b\u5e8f\u5728\u51e0\u4e2a\u521d\u59cb\u5316\u51fd\u6570\u4e4b\u95f4\u6765\u56de\u8df3\u8dc3\uff0c\u6bd4\u5982\u5df2\u7ecf\u5230\u4e86 set_up_vm_final()\uff0c\u53c8\u8df3\u56de set_up_vm()\uff0c\u518d\u5f80\u4e0b\u8fd0\u884c\u5c31\u5728\u8fd9\u51e0\u4e2a\u51fd\u6570\u4e4b\u95f4\u5faa\u73af\u3002\u8fdb\u5165 gdb \u8c03\u8bd5\uff0c\u5219\u53d1\u73b0\u53d1\u751f\u8df3\u8f6c\u7684\u5730\u65b9\u5e76\u6ca1\u6709\u4efb\u4f55 branch \u6216\u8005 call \u8bed\u53e5\u6307\u5411\u8df3\u5f80\u7684\u5730\u5740\uff0c\u4f46\u662f\u80fd\u89c2\u5bdf\u5230\u51fa\u73b0\u8df3\u8f6c\u7684\u5730\u65b9\uff0c\u5f80\u5f80\u662f\u8fdb\u4e86 memset() \u6216\u8005 memcopy() \u51fd\u6570\u3002

    A1: \u6574\u4e2a\u5b9e\u9a8c\u8fc7\u7a0b\u4e2d\u6211\u9047\u5230\u4e86\u4e09\u56db\u6b21\uff0c\u4e00\u5f00\u59cb\u89c9\u5f97\u662f\u4ee5\u5947\u602a\u7684\u65b9\u5f0f\u89e3\u51b3\u4e86\uff08\u6bd4\u5982\uff0c\u7a81\u7136\u53d1\u73b0\u81ea\u5df1\u5728\u521d\u59cb\u5316\u8fdb\u7a0b\uff0c\u5f15\u5165\u5916\u90e8\u9875\u8868\u65f6\u7528\u5230\u7684\u4ee3\u7801\u662f extern unsigned long *swapper_pg_dir;\uff0c\u800c\u4e0d\u662f extern unsigned long swapper_pg_dir[512] __attribute__((__aligned__(0x1000)));\uff0c\u5373\uff0c\u7f3a\u5c11\u4e86\u4e00\u4e2a\u5730\u5740\u5bf9\u9f50\u3002\u540c\u5b66\u6307\u51fa\u5982\u679c\u6ca1\u6709\u5bf9\u9f50\uff0c\u53ef\u80fd\u4f1a\u5bfc\u81f4\u9875\u8868\u8fb9\u7f18\u7684\u4e00\u4e9b\u6570\u636e\u7684\u4e22\u5931\u635f\u574f\u3002\uff09\uff0c\u540e\u6765\u6162\u6162\u53d1\u73b0\u89c4\u5f8b\u662f\uff1a\u53d1\u751f\u8fd9\u6837\u8df3\u8f6c\u7684\u6307\u4ee4\uff0c\u90fd\u5728\u5c1d\u8bd5\u5f80 0x80000000 \u8fd9\u4e2a\u7269\u7406\u5730\u5740\u4ee5\u4e0b\u7684\u7269\u7406\u5730\u5740\u5199\u4e1c\u897f\u3002\u6211\u4eec\u6ce8\u610f\u5230 qemu \u63d0\u4f9b\u7ed9\u6211\u4eec\u7684\u7269\u7406\u5730\u5740\u90fd\u662f 0x80000000 \u4ee5\u4e0a\u7684\u5730\u5740\uff0c\u867d\u7136\u6ca1\u6709\u8003\u8bc1\uff0c\u4f46\u662f\u5408\u7406\u731c\u6d4b\u5176\u4e0b\u7684\u5730\u5740\u662f qemu \u81ea\u5df1\u7684\u4ee3\u7801\u533a\uff0c\u652f\u6301 qemu \u81ea\u5df1\u7684\u8fd0\u884c\u903b\u8f91\u3002\u5982\u679c\u4e0d\u5c0f\u5fc3\u5199\u5230\u4e86\u8fd9\u4e2a\u5730\u65b9\uff0c\u5f53\u7136\u53ef\u80fd\u53d1\u751f\u4e0d\u80fd\u89e3\u91ca\u7684 qemu \u884c\u4e3a\u3002

    \u6240\u4ee5\u5982\u679c\u9047\u5230\u8fd9\u4e2a\u95ee\u9898\uff0c\u53ef\u884c\u7684\u4e00\u6b65\u4e00\u6b65\u68c0\u67e5\u65b9\u6cd5\u662f\uff1a

    \u603b\u4e4b\uff0c\u6839\u672c\u76ee\u6807\u662f\u53bb\u770b\u4e00\u4e0b\u6709\u6ca1\u6709\u5f80\u7269\u7406\u5730\u5740 0x80000000 \u4ee5\u4e0b\u7684\u5730\u65b9\u5199\u4e1c\u897f\u3002

    Q2: \u8fd0\u884c\u7a0b\u5e8f\u5230\u4e00\u534a\u5361\u4f4f\uff0c\u6ca1\u6709\u4efb\u4f55\u8f93\u51fa\u4e86\uff0c\u8c03\u8bd5\u53d1\u73b0\u6700\u540e\u662f\u5728 __dummy \u7684 sret \u540e\u5361\u4f4f\u4e86\u3002

    A2: \u53ef\u4ee5\u5148\u5b9e\u73b0\u4e00\u4e2a\u6f02\u4eae\u70b9\u7684 trap_handler() \u5e2e\u52a9\u8c03\u8bd5\u3002\u8fd9\u70b9\u5728 lab7 \u7684\u6307\u5bfc\u91cc\u624d\u6709\u63d0\u793a\u5230\uff0c\u4e0d\u8fc7\u6211\u89c9\u5f97\u5e94\u8be5\u65e9\u70b9\u5b9e\u73b0\u8d77\u6765\u3002\u6bd4\u5982\uff1a

    void trap_handler(uint64 scause, uint64 sepc, struct pt_regs* regs) {  // a0, a1, a2\nuint64 stval = csr_read(stval);\n// printk(\"[S] Trap @sepc = %#llx, @scause = %#llx, @stval = %#llx\\n\", sepc, scause, stval);\nint done = 0;\n/* Interrupt */\nif ((scause >> 63) && (scause & 0x7FFFFFFFFFFFFFFF) == 5) {\nclock_set_next_event();\nprintk(\"[S] Supervisor Timer Intterupt\\n\");\ndo_timer();\n} /* Exception */\nelse {\n/* instrution addr misaligned */\nif (scause == 0) {}\n/* Instruction access fault */\nelse if (scause == 1) {}\n/* Illegal instruction */\nelse if (scause == 2) {}\n/* breakpoint */\nelse if (scause == 3) {}\n/* load addr misaligned */\nelse if (scause == 4) {}\n/* load access fault */\nelse if (scause == 5) {}\n/* store/amo addr misaligned */\nelse if (scause == 6) {}\n/* store/amo access fault */\nelse if (scause == 7) {}\n/* ecall U-mode */\nelse if (scause == 8) {\nif (sys_call_num == SYS_WRITE) {\n// ...\n} else if (sys_call_num == SYS_GETPID) {\n// ...\n} else if (sys_call_num == SYS_CLONE) {\n// ...\n}\nregs->sepc += 4; // pc + 4\n} /* ecall S-mode */\nelse if (scause == 9) {}\n/* Instruction page fault */\n/* Load page fault */\n/* Store/amo page fault */\nelse if (scause == 12 || scause == 13 || scause == 15) {\ndone = do_page_fault(scause, regs);\n} else {\nprintk(\"[S] Unhandled exception with scause = %d, sepc = %lx\\n\", scause, sepc);\nwhile (1);\n}\n}\n// if (!done) while(1);\n}\n
    \u603b\u4e4b\uff0c\u5efa\u8bae\u5bf9 trap_handler() \u505a\u7684\u6539\u8fdb\u6709\u4e24\u4ef6

    \u5982\u679c\u786e\u5b9e\u662f\u5faa\u73af trap \u5bfc\u81f4\u7684\u7a0b\u5e8f\u5361\u4f4f\uff0c\u90a3\u4e48\u6309\u6253\u5370\u7684\u4fe1\u606f\u53bb\u601d\u8003\u5c31\u53ef\u4ee5\u4e86\u3002\u5982\u679c\u8fd8\u662f\u4ec0\u4e48\u8f93\u51fa\u90fd\u6ca1\u6709\uff08\u6211\u8bb0\u5f97\u4e5f\u6709\u8fd9\u79cd\u60c5\u51b5\uff09\uff0c\u6211\u4e0d\u8bb0\u5f97\u662f\u4ec0\u4e48\u539f\u56e0\u4e86\uff0c\u4f46\u662f\u8d77\u7801\u5e2e\u4f60\u6392\u9664\u4e86\u53d1\u751f\u4e86 trap \u7684\u53ef\u80fd\u6027\uff0c\u4f60\u53ef\u4ee5\u5728\u6b64\u57fa\u7840\u4e0a\u7ee7\u7eed\u601d\u8003\u662f\u4e3a\u4ec0\u4e48\u3002

    "},{"location":"docs/2-ling/","title":"Linguistic Notes","text":"

    :material-circle-edit-outline: \u7ea6 62 \u4e2a\u5b57

    This section mainly consists of the notes of the linguistics courses from Zhejiang University.

    "},{"location":"docs/2-ling/#contents","title":"Contents","text":"

    It is commonly considered that the subject linguistics consists of 6 main branches.

    Besides, we also talk about other topics,

    "},{"location":"docs/2-ling/acqusition/","title":"Language Acqusition","text":"

    :material-circle-edit-outline: \u7ea6 40 \u4e2a\u5b57

    \u4e3b\u8981\u53ef\u80fd\u5199\u4e00\u4e9b\u8bed\u6cd5\uff0c\u8bcd\u6cd5\u548c\u53e5\u6cd5\u7b49\u3002

    \u5355\u8bcd\u8bb0\u5fc6\u548c\u4e60\u60ef\u7528\u8bed\u4e0d\u5728\u672c\u5e16\u7684\u8bb0\u5f55\u8303\u56f4\u4e4b\u5185\u3002

    "},{"location":"docs/2-ling/acqusition/#contents","title":"Contents","text":""},{"location":"docs/2-ling/acqusition/french-tense/","title":"French Tense summarization","text":"

    :material-circle-edit-outline: \u7ea6 1161 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/2-ling/acqusition/french-tense/#overview","title":"Overview\uff1a\u8bed\u6001\u548c\u65f6\u6001","text":"

    \u52a8\u8bcd\u7684\u53d8\u4f4d\u6709\u4e24\u79cd\u5c5e\u6027\uff1a\u8bed\u6001\u548c\u65f6\u6001\u3002\u8bed\u6001\u5bf9\u5e94\u4e00\u4e2a\u52a8\u4f5c\u7684\u7edd\u5bf9\u8fdb\u884c\u7a0b\u5ea6\u5c5e\u6027\uff0c\u800c\u65f6\u6001\u5bf9\u5e94\u52a8\u4f5c\u7684\u76f8\u5bf9\u53d1\u751f\u65f6\u95f4\u3002

    \u6211\u627e\u5230\u4e86\u4e00\u4e2a\u5173\u4e8e\u8bed\u6001\u6bd4\u8f83\u597d\u7684\u793a\u610f\u56fe\uff0c\u6a2a\u5411\u8868\u793a\u52a8\u8bcd\u7684\u5b8c\u6210\u7a0b\u5ea6\uff0c\u7eb5\u5411\u8868\u793a\u52a8\u8bcd\u672c\u8eab\u7684\u6301\u7eed\u65f6\u957f\uff0c\u4e8e\u662f\u4e0a\u3001\u4e0b\u3001\u5de6\u3001\u53f3\u53ef\u4ee5\u5927\u81f4\u5bf9\u5e94\u77ac\u6001\u52a8\u8bcd\u3001\u6301\u7eed\u52a8\u8bcd\u3001\u5c06\u8981\u53bb\u505a\u3001\u5df2\u7ecf\u5b8c\u6210\u3002 

              \u77ac\u6001\n           /\\\n          /  \\\n         /\u975e\u5e38\u6001\\\n         -------\n\u4e0d\u5b9a\u6001  /         \\  \u5b8c\u6210\u6001\n       ------------\n           \u5e38\u6001\n
    \u800c\u65f6\u6001\u8868\u793a\u52a8\u4f5c\u53d1\u751f\u7684\u65f6\u95f4\u987a\u5e8f\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u4e0a\u8ff0\u4e09\u89d2\u5957\u5165\u8fc7\u53bb\u3001\u73b0\u5728\u3001\u5c06\u6765\u8fd9\u4e09\u4e2a\u76f8\u5bf9\u65f6\u95f4\uff0c\u7ec4\u5408\u5f97\u5230\u5bf9\u5e94\u65f6\u6001\u4e0b\u7684\u591a\u4e2a\u8bed\u6001\u3002

    \u6cd5\u8bed\u7684 3 \u79cd\u65f6\u6001\u6709\uff1a

    \u540c\u65f6\u8fd8\u6709 6 \u79cd\u8bed\u6001\uff1a

    \u4e8e\u662f\u53ef\u4ee5\u7ec4\u5408\u4ea7\u751f\u591a\u4e2a\u65f6\u6001\u4e0b\u7684\u591a\u4e2a\u8bed\u6001\uff0c\u5b83\u4eec\u4e00\u822c\u5408\u79f0\u53eb\u65f6\u6001\uff0c\u6709\u70b9\u6b67\u4e49\uff0c\u4e0d\u8fc7\u5c31\u8fd9\u6837\u53eb\u597d\u4e86\u3002\u4e0b\u9762\u4e00\u4e00\u4ecb\u7ecd\u3002

    "},{"location":"docs/2-ling/acqusition/french-tense/#_1","title":"\u5177\u4f53\u65f6\u6001\u4ecb\u7ecd","text":"

    \u9996\u5148\u63d0\u4f9b\u4e00\u4e2a overview\u3002

    Fig 1. \u4ec5\u4e0e\u5ba2\u89c2\u73b0\u5b9e\u6709\u5173\u7684\u51e0\u4e2a\u65f6\u6001\u7684\u65f6\u95f4\u8f74

    \u76f4\u9648\u5f0f (l'indicatif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u76f4\u9648\u5f0f\u73b0\u5728\u65f6l'indicatif pr\u00e9sent \u53d1\u751f\u5728\u73b0\u5728\u7684\u52a8\u4f5c\u6216\u5b58\u5728\u7684\u72b6\u6001\u3002 \u52a8\u8bcd\u8bcd\u6839 - \u8bcd\u5c3e + \u4e0d\u540c\u4eba\u79f0\u4e3b\u8bed\u5bf9\u5e94\u7684\u8bcd\u5c3e j'aime,tu aimes,il/elle/on aime,nous aimons,vous aimez,ils/elle aiment je choisis,tu choisis,il/elle/on choisit,nous choisissons,vous choisissez,ils/elles choisissent je dors,tu dors,il/elle/on dort,nous dormons,vous dormez,ils/elles dorment \u76f4\u9648\u5f0f\u590d\u5408\u8fc7\u53bb\u65f6le pass\u00e9 compos\u00e9 \u8868\u793a\u4ece\u73b0\u5728\u89d2\u5ea6\u770b\u5df2\u7ecf\u53d1\u751f\u7684\u52a8\u4f5c\u3002\u8868\u8fbe\u7684\u662f\u201c\u67d0\u4e8b\u5df2\u7ecf\u5b8c\u6210\u201d\u7684\u6982\u5ff5\u3002 \u00eatre \u7684\u76f4\u9648\u5f0f\u73b0\u5728\u65f6 + \u52a8\u8bcd\u8fc7\u53bb\u5206\u8bcd\uff08\u5c11\u90e8\u5206\u8868\u793a\u8d8b\u5411\u6027\u3001\u4f4d\u7f6e\u6216\u72b6\u6001\u53d8\u5316\u7684\u4e0d\u53ca\u7269\u52a8\u8bcd\u3001\u6240\u6709\u4ee3\u8bcd\u5f0f\u52a8\u8bcd\uff0csee Fig 2\uff09 \u6216avoir \u7684\u76f4\u9648\u5f0f\u73b0\u5728\u65f6 + \u52a8\u8bcd\u8fc7\u53bb\u5206\u8bcd\uff08\u5176\u5b83\uff09 .. .. .. \u76f4\u9648\u5f0f\u672a\u5b8c\u6210\u8fc7\u53bb\u65f6l'imparfait \u8868\u793a\u8fc7\u53bb\u53d1\u751f\u7684\u52a8\u4f5c\uff0c\u53ea\u662f\u4e8b\u60c5\u7684\u5b8c\u6210\u72b6\u6001\u662f\u4e0d\u660e\u786e\u7684\uff0c \u76f4\u9648\u5f0f\u6108\u8fc7\u53bb\u65f6le plus-que parfait \u76f4\u9648\u5f0f\u7b80\u5355\u8fc7\u53bb\u65f6le pass\u00e9 simple \u76f4\u9648\u5f0f\u5148\u8fc7\u53bb\u65f6le pass\u00e9 ant\u00e9rieur \u76f4\u9648\u5f0f\u6700\u8fd1\u8fc7\u53bb\u65f6le pass\u00e9 proche \u76f4\u9648\u5f0f\u7b80\u5355\u5c06\u6765\u65f6le furture simple \u76f4\u9648\u5f0f\u5148\u5c06\u6765\u65f6le future ant\u00e9rieur \u76f4\u9648\u5f0f\u6700\u8fd1\u5c06\u6765\u65f6le future proche \u76f4\u9648\u5f0f\u8fc7\u53bb\u5c06\u6765\u65f6le futur dans le pass\u00e9

    Fig 2. le pass\u00e9 compos\u00e9 \u4e2d\u4f7f\u7528 \u00eatre \u52a9\u52a8\u8bcd\u7684\u52a8\u8bcd

    \u547d\u4ee4\u5f0f (l'imp\u00e9ratif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u6761\u4ef6\u5f0f (le conditionnel)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u865a\u62df\u5f0f (le subjonctif)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent

    \u5206\u8bcd\u5f0f (le participe)\u4e0b\u7684\u65f6\u6001

    \u65f6\u6001 \u5b9a\u4e49 \u5927\u81f4\u6784\u6210\u89c4\u5219 \u4e00\u7c7b\u52a8\u8bcd\u6784\u6210 \u6784\u6210 \u7b2c\u4e09\u7ec4\u6784\u6210 \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent \u547d\u4ee4\u5f0f\u73b0\u5728\u65f6l'imp\u00e9ratif pr\u00e9sent"},{"location":"docs/2-ling/acqusition/french-tense/#references","title":"References","text":""},{"location":"docs/2-ling/morphology/","title":"Morphology","text":"

    :material-circle-edit-outline: \u7ea6 2 \u4e2a\u5b57

    "},{"location":"docs/2-ling/morphology/#outline","title":"outline","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/","title":"TODO","text":"

    :material-circle-edit-outline: \u7ea6 327 \u4e2a\u5b57 :fontawesome-solid-code: 2 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    Aug. 25th. 2023

    This talk aims both to provide an introduction to the subject Philosophy of Language (a similar subject with semantics and pragmatics, according to its definition; PoL hereafter), and give a summary on the recent ongoing discussion on the linguistics concepts in NLP (e.g. \"meaning\", \"understanding\", \"reasoning\", \"grounding\").

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#a-preview-of-this-talk","title":"A Preview of This Talk","text":"

    1st 40min: History of philosophy of language 2nd 40min: Recent papers and discussions on PoL topics in NLP 3rd 10min: Discussion on take-away

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#the-location-of-pol-on-the-academic-coordinate","title":"The Location of PoL on the Academic Coordinate","text":"

    Before we start this talk, we will first provide a brief definition of the term Philosophy of Language in our talk here. The PoL concerns mainly the two following questions, (i) The relationship between the natural language and the world, (ii) The relationship between the human languages and their meaning. Chen (2003) believes that the PoL and the linguistics are two different subjects. He suggests that the linguistics is the study of language rules and patterns and the application of them, while the PoL pays more attention on the more abstract and essential features of the human language (e.g. its relation to the cognition). The author of this talk believes, according to the definition of PoL, it is a subject that closely involves the semantics and pragmatics branches in linguistics. However the PoL and linguistics overlap or not, it is commonly believed that the subject PoL was born in the 1920s, when the linguistic turn was put on stage in the European philosophy.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#history-of-pol","title":"History of PoL","text":"

    Now we will dive into the history of PoL. This section is parted \"person by person\". It is noticed that \"person-by-person\" is a common structure of most of the philosophy history, as most of the philosophy progresses are propelled by giants instead of the common people.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#gottfried-wilhelm-leibniz","title":"Gottfried Wilhelm Leibniz","text":"

    The main contribution of Leibniz is

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#ferdinand-de-saussure","title":"Ferdinand de Saussure","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#friedrich-ludwig-gottlob-frege","title":"Friedrich Ludwig Gottlob Frege","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#bertrand-russell","title":"Bertrand Russell","text":"

    Bertrand Russell is a pure logician.

    "},{"location":"docs/2-ling/philosophy/pol_en_todo/#ludwig-wittgenstein","title":"Ludwig Wittgenstein","text":""},{"location":"docs/2-ling/philosophy/pol_en_todo/#noam-chomsky","title":"Noam Chomsky","text":""},{"location":"docs/2-ling/philosophy/pol_zh/","title":"Philosophy of Language \u8bed\u8a00\u54f2\u5b66","text":"

    :material-circle-edit-outline: \u7ea6 3102 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    Nov. 9th. 2022

    "},{"location":"docs/2-ling/philosophy/pol_zh/#talk","title":"\u8fd9\u6b21talk\u4f1a\u8bb2\u4ec0\u4e48","text":"

    \u2705\u00a0\u4ecb\u7ecd\u8bed\u8a00\u54f2\u5b66\u7684\u601d\u6f6e\u6d41\u53d8\u5386\u7a0b\uff0c\u4ecb\u7ecd\u8bed\u8a00\u4e0a\u7684\u5b9e\u9a8c\u601d\u60f3\u5b9e\u9a8c\uff0c\u8ba8\u8bba\u4e00\u4e9b\u8bed\u8a00\u5b66\u3001\u8ba4\u77e5\u3001\u903b\u8f91\u548c\u54f2\u5b66\u7684\u5173\u8054

    "},{"location":"docs/2-ling/philosophy/pol_zh/#pol","title":"PoL","text":"

    \u8bed\u8a00\u54f2\u5b66\u7684\u57fa\u672c\u95ee\u9898\uff1a 1. \u8bed\u8a00\u548c\u4e16\u754c\u7684\u5173\u7cfb 2. \u8bed\u8a00\u6216\u8bed\u8bcd\u7684\u610f\u4e49\u95ee\u9898

    \u8bed\u8a00\u54f2\u5b66\u548c\u8bed\u8a00\u5b66 \u8bed\u8a00\u5b66\u548c\u8bed\u8a00\u54f2\u5b66\u7684\u8054\u7cfb\u7d27\u5bc6\uff0c\u4f46\u662f\u662f\u4e24\u95e8\u5b66\u79d1\u3002

    20\u4e16\u7eaa\u54f2\u5b66\u4e0a\u53d1\u751f\u4e86\u8bed\u8a00\u8f6c\u5411\uff0c\u8fd9\u4e5f\u662f\u73b0\u4ee3\u8bed\u8a00\u5b66\u5f62\u6210\u7684\u65f6\u5019\u3002

    \u8bed\u8a00\u5b66\u662f\u5bf9\u8bed\u8a00\u89c4\u5f8b\u548c\u8fd9\u4e9b\u89c4\u5f8b\u7684\u5e94\u7528\u7684\u7814\u7a76\uff0c\u8bed\u8a00\u54f2\u5b66\u66f4\u5173\u5fc3\u8bed\u8a00\u66f4\u672c\u8d28\u66f4\u62bd\u8c61\u7684\u610f\u4e49\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#history-of-pol","title":"History of PoL","text":"

    \u83b1\u5e03\u5c3c\u8328\uff1a\u63d0\u51fa\u903b\u8f91\u8bed\u8a00\uff0c\u7b80\u5386\u4eba\u5de5\u8bed\u8a00\u7684\u52aa\u529b

    \u5f3a\u8c03\u81ea\u7136\u8bed\u8a00\u4f9d\u8d56\u4e8e\u77e5\u8bc6\uff0c\u56e0\u6b64\u5206\u6709\u77e5\u89c9\u7684\u6a21\u7cca\u3001\u6b67\u4e49\u7b49\u79cd\u79cd\u7f3a\u9677\u3002\u81ea\u7136\u8bed\u8a00\u4e0d\u662f\u63cf\u8ff0\u5ba2\u89c2\u4e8b\u7269\u7684\u6700\u4f73\u5de5\u5177\uff0c\u4e3a\u4e86\u63a2\u7a76\u771f\u7406\uff0c\u5fc5\u987b\u5efa\u7acb\u4e00\u4e2a\u7531\u666e\u904d\u7b26\u53f7\u7ec4\u6210\u7684\u66f4\u4e3a\u6e05\u695a\u7684\u7b26\u53f7\u4f53\u7cfb\u3002\u8fd9\u79cd\u52aa\u529b\u5728\u6570\u5b66\u65b9\u9762\u662f\u5353\u6709\u6210\u6548\u7684\uff0c\u6bd4\u5982\u5fae\u79ef\u5206\u7b26\u53f7\u3002

    \u7d22\u7eea\u5c14\uff1a \u7d22\u7eea\u5c14\u6700\u5927\u7684\u5f71\u54cd\u662f\u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u3002\u6211\u4eec\u4e00\u822c\u8ba4\u4e3a\u7d22\u7eea\u5c14\u662f\u4e00\u4f4d\u8bed\u8a00\u5b66\u5bb6\uff0c\u4f46\u662f\u4ed6\u5728\u8fd9\u672c\u4e66\u4e2d\u63d0\u51fa\u7684\u201c\u80fd\u6307\u201d\u4e0e\u201c\u6240\u6307\u201d\u7406\u8bba\uff0c\u662f\u54f2\u5b66\u91cc\u7684\u7b26\u53f7\u5b66\u7684\u5f00\u7aef\u3002

    \u8bed\u8a00\u662f\u7528\u58f0\u97f3\u8868\u8fbe\u601d\u60f3\u7684\u7b26\u53f7\u7cfb\u7edf\uff0c\u7b26\u53f7\u662f\u7528\u4ee5\u8868\u793a\u8005\u548c\u88ab\u8868\u793a\u8005\u7684\u7ed3\u5408\u3002

    \u6211\u4eec\u4f1a\u8bf4\uff0c\u58f0\u97f3\u672c\u8eab\u4e0d\u80fd\u65bd\u6307\uff0c\u53ea\u6709\u5904\u5728\u67d0\u79cd\u7279\u5b9a\u5173\u7cfb\u4e2d\uff08\u8bed\u8a00\u5b9a\u4e49\u4e86\u58f0\u97f3\u548c\u5b9e\u4f53\u4e4b\u95f4\u7684\u5173\u7cfb\uff09\uff0c\u58f0\u97f3\u624d\u6709\u4e86\u610f\u4e49\u3002

    \u4efb\u610f\u6027\u539f\u5219\u662f\uff0c\u5982\u6b64\u8fd9\u822c\u7684\u65bd\u6307\u548c\u5982\u6b64\u8fd9\u822c\u7684\u6240\u6307\u7ed3\u5408\u800c\u6210\u7684\u4e00\u4e2a\u7b26\u53f7\uff0c\u662f\u4efb\u610f\u7684\u3002eg. \u989c\u8272\u4e0e\u989c\u8272\u8bcd\u7684\u8054\u7ed3\u662f\u4efb\u610f\u7684\uff0c\u989c\u8272\u7684\u754c\u9650\u4e0e\u989c\u8272\u8bcd\u7684\u8054\u7ed3\u4e5f\u662f\u4efb\u610f\u7684\u3002

    \"\u7eff\"\u4e0d\u4ec5\u548c\u7eff\u989c\u8272\u76f8\u8fde\uff0c\u800c\u4e14\u548c\u201c\u84dd\u201d\u201c\u9752\u201d\u7b49\u8bed\u8bcd\u76f8\u8fde\u3002\n\u5982\u679c\u6ca1\u6709\u201c\u84dd\u201d\u201c\u9752\u201d\uff0c\u6211\u4eec\u5c31\u4e0d\u80fd\u77e5\u9053\u201c\u7eff\u201d\u6240\u754c\u5b9a\u7684\u989c\u8272\u8303\u56f4\u3002\n\n\u201c\u4e03\u8272\u5f69\u8679\u201d\n\u65e5\u8bed\u4e0d\u533a\u5206\u201c\u84dd\u201d\u548c\u201c\u7eff\u201d\uff0c\u53ea\u6709\u4e00\u4e2a\u5355\u8bcd\u201c\u9752\u201d\uff08aoi\uff09\uff0c\u65e5\u8bed\u6bcd\u8bed\u8005\u5728\u9274\u522b\u84dd\u8272\u548c\u7eff\u8272\u65f6\u53cd\u5e94\u65f6\u9ad8\u4e8e\u82f1\u8bed\u6bcd\u8bed\u8005\u3002\n\u4e00\u79cd\u5317\u6b27\u8bed\u8a00\u6709\u4e03\u79cd\u84dd\u8272\u7684\u540d\u79f0\u3002\n

    \u6211\u4eec\u4e60\u60ef\u628a\u8bed\u8bcd\u548c\u60c5\u5883\u7684\u8054\u7cfb\u79f0\u4f5c\u7eb5\u5750\u6807\u6216\u8bed\u5883\u5750\u6807\uff0c\u628a\u8bed\u8bcd\u4e4b\u95f4\u7684\u8054\u7cfb\u79f0\u4f5c\u6a2a\u5750\u6807\u548c\u903b\u8f91\u5750\u6807\u3002

    eg. \u5b8c\u5f62\u586b\u7a7a\u9898

    eg. \u6570\u636e\u5e93\u5173\u7cfb\u6a21\u578b\u7684\u5c5e\u6027\u3001\u5143\u7ec4

    \u975e\u5e38\u6709\u8da3\uff0c\u7d22\u7eea\u5c14\u5199\u8fd9\u672c\u8bed\u8a00\u5b66\u6559\u6750\u65f6\uff0c\u4e16\u754c\u4e0a\u5e76\u6ca1\u6709\u7b26\u53f7\u5b66\u8fd9\u4e2a\u5b66\u79d1\u3002\u5728\u4ed6\u63d0\u51fa\u201c\u80fd\u6307\u201d\u201d\u6240\u6307\u201c\u8fd9\u4e2a\u6982\u5ff5\u540e\uff0c\u7b26\u53f7\u5b66\u5728\u4ed6\u201d\u80fd\u6307\u201c\u5728\u201d\u6240\u6307\u201c\u7684\u94fe\u6761\u4e0a\u6ed1\u52a8\u8fd9\u4e00\u8bba\u65ad\u7684\u57fa\u7840\u4e0a\u8bde\u751f\uff0c\u5e76\u81f3\u4eca\u6210\u4e3a\u6cd5\u56fd\u54f2\u5b66\u7684\u4e00\u4e2a\u91cd\u8981\u95ee\u9898\u3002

    \u5f17\u96f7\u683c\uff1a

    \u5f17\u96f7\u683c\u662f\u516c\u8ba4\u7684\u5206\u6790\u54f2\u5b66\u3001\u8bed\u8a00\u54f2\u5b66\u548c\u73b0\u4ee3\u6570\u7406\u903b\u8f91\u7684\u5f00\u521b\u8005\u3002

    \u300a\u6982\u5ff5\u6587\u5b57\uff1a\u4e00\u79cd\u6a21\u4eff\u7b97\u672f\u8bed\u8a00\u6784\u9020\u7684\u7eaf\u601d\u7ef4\u7684\u5f62\u5f0f\u8bed\u8a00\u300b\u4e3b\u8981\u5de5\u4f5c\u662f\uff0c\u8bbe\u8ba1\u4e86\u4e00\u5957\u4eba\u5de5\u7b26\u53f7\u7cfb\u7edf\uff0c\u6392\u9664\u4e86\u81ea\u7136\u8bed\u8a00\u4e2d\u4fee\u8f9e\u4e4b\u7c7b\u7684\u4e1c\u897f\uff0c\u4e13\u6ce8\u4e8e\u6982\u5ff5\u672c\u8eab\u548c\u6982\u5ff5\u4e4b\u95f4\u7684\u8054\u7cfb\uff0c\u56e0\u6b64\uff0c\u5b83\u5c06\u6392\u9664\u81ea\u7136\u8bed\u8a00\u7684\u6a21\u7cca\u6027\u548c\u4e0d\u786e\u5b9a\u6027\u3002\u7528\u8fd9\u5957\u7b26\u53f7\u7cfb\u7edf\u6765\u91cd\u65b0\u8868\u8ff0\u7b97\u672f\u7684\u57fa\u672c\u6982\u5ff5\u548c\u63a8\u7406\u89c4\u5219\uff0c\u660e\u786e\u6240\u6709\u63a8\u7406\u7684\u524d\u63d0\uff0c\u4fdd\u8bc1\u4e00\u4e2a\u8bc1\u660e\u4e2d\u5404\u4e2a\u547d\u9898\u95f4\u7684\u6240\u6709\u63a8\u7406\u89c4\u5219\uff0c\u4f7f\u63a8\u7406\u4e0d\u518d\u57fa\u4e8e\u76f4\u89c9\uff0c\u4e5f\u6ca1\u6709\u8df3\u8dc3\u548c\u8131\u8282\u3002

    \u5bf9\u8bed\u8a00\u54f2\u5b66\u5f71\u54cd\u6700\u6df1\u7684\u662f\u4ed6\u5728\u300a\u7b97\u672f\u57fa\u7840\u300b\u4e2d\u63d0\u51fa\u7684\u4e09\u6761\u8457\u540d\u539f\u5219\uff1a

    1. \u59cb\u7ec8\u628a\u5fc3\u7406\u7684\u4e1c\u897f\u548c\u903b\u8f91\u7684\u4e1c\u897f\u3001\u4e3b\u89c2\u7684\u4e1c\u897f\u548c\u5ba2\u89c2\u7684\u4e1c\u897f\u4e25\u683c\u533a\u5206\u5f00\u3002\u8fd9\u4e00\u6761\u53cd\u5bf9\u5f53\u65f6\u751a\u4e3a\u6d41\u884c\u7684\u5fc3\u7406\u4e3b\u4e49\u3002\u5f17\u96f7\u683c\u4e3b\u5f20\u903b\u8f91\u5b66\u5bb6\u7814\u7a76\u7684\u662f\u8bed\u8a00\u8868\u8fbe\u5f0f\u3002\u8bed\u8a00\u8868\u8fbe\u5f0f\u662f\u53ef\u4ee5\u516c\u5f00\u8003\u5bdf\u7684\uff0c\u610f\u4e49\u7814\u7a76\u5e94\u5f53\u57fa\u4e8e\u8fd9\u4e9b\u8868\u8fbe\u5f0f\uff0c\u800c\u4e0d\u662f\u4f9d\u8d56\u4e8e\u5bf9\u5fc3\u7406\u8fc7\u7a0b\u7684\u81c6\u6d4b\u3002
    2. \u7edd\u4e0d\u5b64\u7acb\u5730\u5bfb\u95ee\u4e00\u4e2a\u8bcd\u7684\u610f\u4e49\uff0c\u800c\u53ea\u5728\u4e00\u4e2a\u547d\u9898\u7684\u4e0a\u4e0b\u6587\u4e2d\u5bfb\u95ee\u8bcd\u7684\u610f\u601d\u3002\u88ab\u79f0\u4e3a\u8bed\u5883\u539f\u5219\u548c\u4e0a\u4e0b\u6587\u539f\u5219\uff0c\u6307\u51fa\u8bed\u4e49\u7814\u7a76\u7684\u6700\u5c0f\u5355\u4f4d\u8d77\u7801\u662f\u53e5\u5b50\uff0c\u4e0d\u662f\u8bcd\uff0c\u4e0d\u662f\u8868\u5c42\u8bed\u6cd5\u3002\u6211\u4eec\u6ce8\u610f\u5230\u8fd9\u4e00\u6761\u4e0e\u7b2c\u4e00\u6761\u76f8\u5173\uff0c\u56e0\u4e3a\u5982\u679c\u7814\u7a76\u8bcd\uff0c\u8bcd\u4f9d\u8d56\u7684\u5fc5\u7136\u662f\u610f\u4e49\u5728\u5fc3\u7406\u8fc7\u7a0b\u4e2d\u7684\u6620\u5c04\uff0c\u800c\u7814\u7a76\u53e5\u5b50\uff0c\u6211\u4eec\u4f1a\u628a\u8bed\u8bcd\u5728\u53e5\u5b50\u4e2d\u7684\u8054\u7cfb\u5f53\u4f5c\u610f\u4e49\u3002
    3. \u7edd\u4e0d\u5fd8\u8bb0\u6982\u5ff5\u548c\u5bf9\u8c61\u7684\u533a\u522b\u3002

    \u4e24\u4e2a\u601d\u7ef4\u5b9e\u9a8c\uff1a

    1. \u6307\u79f0\u76f8\u540c\u800c\u610f\u4e49\u4e0d\u540c\u7684\u8bcd 

      \u201c\u542f\u660e\u661f\u201d\u548c\u201c\u957f\u5e9a\u661f\u201d\u662f\u540c\u4e00\u9897\u884c\u661f\u2014\u2014\u2014\u2014\u91d1\u661f\u3002\n\u4f46\u662f\u4e24\u4e2a\u540d\u8bcd\u7684\u610f\u4e49\u4e0d\u540c\uff0c\u5927\u591a\u6570\u65f6\u5019\u4e0d\u80fd\u66ff\u6362\u3002\n\u201c\u4ed6\u5929\u8fd8\u6ca1\u4eae\u5c31\u8d77\u8eab\uff0c\u8fce\u7740\u542f\u660e\u661f\u5411\u4e1c\u8d70\u53bb\u3002\u201d\n

    2. \u51fd\u5f0f\u7406\u8bba 

      \uff08 \uff09\u662f\u4e2d\u56fd\u7684\u9996\u90fd\n\uff08 \uff09= \"\u4f26\u6566\"\u3001\"\u5317\u4eac\"\n\u53ea\u6709\u586b\u5165\u5317\u4eac\u7684\u65f6\u5019\u624d\u662f\u771f\u547d\u9898\n

    \u7f57\u7d20\uff1a\u903b\u8f91

    \u6df1\u5165\u4e13\u540d\u548c\u901a\u540d\u3001\u6096\u8bba\u3001\u6392\u4e2d\u5f8b\u3002

    \u7ef4\u7279\u6839\u65af\u5766\uff1a

    \u524d\u671f\u601d\u60f3\u300a\u903b\u8f91\u54f2\u5b66\u8bba\u300b

    \u201c\u4e16\u754c\u662f\u4e8b\u5b9e\u7684\u7efc\u5408\u201d\uff1a\u201c\u53f8\u9a6c\u5149\u662f\u5510\u671d\u4eba\u201d\u7b26\u5408\u903b\u8f91\uff0c\u4f46\u4e0d\u7b26\u5408\u4e8b\u5b9e\u3002

    \u56fe\u50cf\u8bba

    \u8bed\u8a00\u662f\u547d\u9898\u7684\u603b\u548c\u800c\u4e0d\u662f\u540d\u79f0\u7684\u603b\u548c\u3002

    \u4eba\u5728\u4ea4\u6d41\u601d\u60f3/\u547d\u9898\u65f6\uff0c\u4ea4\u6d41\u7684\u662f\u8111\u4e2d\u7684\u56fe\u50cf\u3002

    \u4ed6\u7684\u524d\u671f\u601d\u60f3\u542f\u53d1\u4e86\u7ef4\u4e5f\u7eb3\u5b66\u6d3e\uff1a\u4eba\u5de5\u8bed\u8a00\uff0c\u903b\u8f91\u8bed\u8a00

    \u5341\u4e5d\u4e16\u7eaa\u672b\u4ee5\u6765\u4eba\u5de5\u8bed\u8a00\u7684\u5c1d\u8bd5\uff1a\u201c\u4e16\u754c\u8bed\uff08Esperanto\uff09\u201d\uff0c\u4e18\u5409\u5c14\u63a8\u5d07\u7684\u57fa\u672c\u82f1\u8bed\uff0c\u81ea\u7136\u8bed\u8a00\u4e2d\u5bf9\u201c\u5973\u4eba\u201d\u201c\u5973\u6027\u201d\u201c\u5973\u58eb\u201d\u201c\u5987\u5973\u201d\u8fd9\u6837\u7684\u6307\u79f0\u7684\u89c4\u8303\u5c1d\u8bd5\u3002

    \u540e\u671f\u601d\u60f3\u300a\u54f2\u5b66\u7814\u7a76\u300b

    \u8bed\u8a00\u6e38\u620f\uff08Sprachspiel\uff09

    \u8bed\u8a00\u7684\u529f\u80fd\u7684\u672c\u8d28\uff1a\u4e00\u65b9\u558a\u51fa\u8bed\u8bcd\uff0c\u53e6\u4e00\u65b9\u4f9d\u7167\u8fd9\u4e9b\u8bed\u8bcd\u6765\u884c\u52a8\u3002

    \u8001\u5e08\u6307\u7740\u77f3\u5934\u8bf4\u201c\u77f3\u5934\u201d\uff0c\u5b66\u751f\u8ddf\u7740\u8bf4\u201c\u77f3\u5934\u201d\u3002\n
    \u4e22\u624b\u7ee2\u65f6\u5531\u7740\u201c\u8f7b\u8f7b\u5730\u653e\u5728\u5c0f\u670b\u53cb\u7684\u8eab\u540e\u201d\uff0c\u628a\u624b\u7ee2\u653e\u5728\u5c0f\u670b\u53cb\u7684\u8eab\u540e\n

    \u4e0e\u524d\u671f\u56fe\u50cf\u7406\u8bba\u7684\u5bf9\u6bd4\uff1a\u5728\u56fe\u50cf\u7406\u8bba\u4e2d\uff0c\u8bed\u8a00\u4ece\u6839\u672c\u4e0a\u662f\u4e00\u79cd\u53cd\u6620\uff1b\u5728\u8bed\u8a00\u6e38\u620f\u8bf4\u4e2d\uff0c\u8bed\u8a00\u9996\u5148\u662f\u4e00\u79cd\u6d3b\u52a8\u3002

    \u610f\u4e49\u6765\u6e90\u4e8e\u4f7f\u7528\u3002

    \u6211\u4eec\u5173\u5fc3\u201c\u9524\u5b50\u201d\u662f\u4ec0\u4e48\u65f6\uff0c\n\u5173\u5fc3\u7684\u662f\u201c\u4f7f\u7528\u4e00\u628a\u9524\u5b50\u201d\uff0c\n\u800c\u4e0d\u662f\u201c\u9524\u5b50\u610f\u5473\u7740\u2026\u2026\u201d\n\u4e8b\u5b9e\u4e0a\uff0c\u6211\u4eec\u4e5f\u6b63\u662f\u4ece\u201c\u4f7f\u7528\u4e00\u628a\u9524\u5b50\u201d\u6765\u5b9a\u4e49\u9524\u5b50\n
    \u5982\u4f55\u533a\u5206\u201c\u4f7f\u7528\u201d\u201c\u6709\u7528\u201d\u201c\u5229\u7528\u201d\uff1f\n\u5728\u4e00\u4e9b\u60c5\u5883\u4e2d\u80fd\u7528\uff0c\u5728\u4e00\u4e9b\u60c5\u5883\u4e2d\u4e0d\u80fd\u7528\u3002\n

    \u8bed\u8a00\u6e38\u620f\u7684\u7c7b\u522b

    \u5bb6\u65cf\u76f8\u4f3c\u7406\u8bba\uff08Familien\u00e4hnlichkeiten\uff09

    \u201c\u4e00\u4e2a\u5bb6\u65cf\u7684\u6709\u4e9b\u6210\u5458\u6709\u4e00\u6837\u7684\u9f3b\u5b50\uff0c\u53e6\u4e00\u4e9b\u6709\u4e00\u6837\u7684\u7709\u6bdb\uff0c\u8fd8\u6709\u4e00\u4e9b\u6709\u4e00\u6837\u7684\u6b65\u6001\uff1b\u8fd9\u4e9b\u76f8\u4f3c\u4e4b\u5904\u4ea4\u53c9\u91cd\u53e0\u3002\u201c

    \u5185\u6db5\uff1a\u4e00\u4e2a\u6982\u5ff5\u7684\u5b9a\u4e49

    \u5916\u5ef6\uff1a\u4e00\u4e2a\u6982\u5ff5\u5305\u542b\u7684\u4e0b\u5c5e\u6982\u5ff5\u7684\u8303\u56f4

    \u901a\u540d\u7684\u4e0b\u5c5e\u8bcd\uff0c\u5404\u79cd\u4e13\u540d\u4e4b\u95f4\u5e76\u6ca1\u6709\u4e25\u683c\u7684\u754c\u9650\uff0c\u4e00\u4e2a\u76f8\u4f3c\u53e6\u4e00\u4e2a\uff0c\u5206\u4eab\u4e0d\u540c\u7684\u5171\u540c\u7279\u5f81\u3002

    \u751f\u6d3b\u5f62\u5f0f\uff08Lebens Form\uff09\uff1a\u5e38\u8bc6\u7684\u91cd\u8981\u6027

    \u201c\u626b\u5e1a\u5728\u90a3\u91cc\u201d\u5df2\u7ecf\u8db3\u591f\u6e05\u6670\u3002\n\u201c\u626b\u5e1a\u628a\u548c\u626b\u5e1a\u5934\u5728\u90a3\u91cc\u201d\uff0c\u867d\u7136\u5206\u6790\u5f97\u66f4\u6e05\u695a\uff0c\u4f46\u5728\u4ea4\u9645\u4e2d\u8ba9\u4eba\u8d39\u89e3\u3002\n

    \u4eff\u4f5b\u6211\u4eec\u53ea\u8981\u66f4\u591a\u8bf4\u4e00\u70b9\uff0c\u591a\u5206\u6790\u4e00\u70b9\uff0c\u4e8b\u60c5\u5c31\u4f1a\u66f4\u6e05\u695a\uff0c\u4eff\u4f5b\u6ca1\u6709\u4e00\u53e5\u8bdd\u672c\u8eab\u5c31\u662f\u8db3\u591f\u6e05\u695a\u7684\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#conclusion-of-agreements","title":"Conclusion of Agreements","text":"
    1. \u8bed\u8a00\u7684\u610f\u4e49\u4f9d\u8d56\u4e8e\u7b26\u53f7\u4e0e\u7b26\u53f7\u4e4b\u95f4\u76f8\u4e92\u5b9a\u4e49\uff0c\u4e0e\u771f\u5b9e\u4e16\u754c\u7684\u5bf9\u8c61\u6ca1\u6709\u7edd\u5bf9\u7684\u4e00\u4e00\u5bf9\u5e94\u5173\u7cfb\u3002
    2. \u8bed\u8a00\u7684\u529f\u80fd\u5728\u4e8e\u53d1\u51fa\u548c\u5b8c\u6210\u547d\u4ee4\u3002
    3. \u81ea\u7136\u8bed\u8a00\u771f\u5b9e\u73b0\u8c61\u6bd4\u4eba\u9020\u8bed\u8a00\u89c4\u5219/\u903b\u8f91\u8868\u8fbe\u5f0f\u66f4\u80fd\u53cd\u5e94\u4eba\u8111\u7684\u8ba4\u77e5\u3001\u66f4\u503c\u5f97\u7814\u7a76\u3002
    "},{"location":"docs/2-ling/philosophy/pol_zh/#history-of-nlp","title":"History of NLP","text":"
    1. \u57fa\u4e8e\u89c4\u5219\u7684 \u2192 \u7ef4\u7279\u6839\u65af\u5766\u524d\u671f\u53ca\u4ee5\u524d\u7684\u7eaf\u903b\u8f91\u8bed\u8a00\uff0c\u4eba\u9020\u8bed\u8a00\u3002
    2. \u57fa\u4e8e\u7edf\u8ba1\u7684\u548c\u6df1\u5ea6\u5b66\u4e60 \u2192 \u7ef4\u7279\u6839\u65af\u5766\u540e\u671f\u7684\u8bed\u8a00\u610f\u4e49\u5728\u4f7f\u7528\u4e2d\u3002
    3. \u548c\u7ed3\u5408\u8bed\u8a00\u5b66\u3001\u8ba4\u77e5\u77e5\u8bc6 \u2192 \u4e54\u59c6\u65af\u57fa\u7684\u8bed\u8a00\u7684\u610f\u4e49\u5728\u521b\u9020\u4e2d\u3002
    "},{"location":"docs/2-ling/philosophy/pol_zh/#pol_1","title":"PoL\u7684\u5176\u5b83\u95ee\u9898","text":"

    \u963f\u4f69\u5c14\u603b\u7ed3\u897f\u65b9\u54f2\u5b66\u7684\u53d1\u5c55\uff1a

    \u53e4\u4ee3\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u672c\u4f53\u8bba\uff0c\u4ece\u8fd1\u4ee3\u5f00\u59cb\uff0c\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u8ba4\u8bc6\u8bba\uff0c\u523020\u4e16\u7eaa\uff0c\u54f2\u5b66\u6ce8\u91cd\u7684\u662f\u8bed\u8a00\u3002

    \u672c\u4f53\u8bba\u7684\u95ee\u9898\uff1a\u4ec0\u4e48\u4e1c\u897f\u5b58\u5728\uff0c\u4ec0\u4e48\u662f\u5b9e\u5728\u7684\u57fa\u672c\u5b58\u5728\u5f62\u5f0f\u3002

    \u8ba4\u8bc6\u8bba\u7684\u95ee\u9898\uff1a\u54ea\u4e9b\u4e1c\u897f\u662f\u6211\u4eec\u80fd\u8ba4\u8bc6\u7684\uff0c\u6211\u4eec\u662f\u600e\u6837\u8ba4\u8bc6\u8fd9\u4e9b\u4e1c\u897f\u7684\u3002

    \u8bed\u8a00\u7684\u95ee\u9898\uff1a\u6211\u4eec\u5728\u4f55\u79cd\u610f\u4e49\u4e0a\u80fd\u591f\u8ba4\u8bc6\u5b58\u5728\u2014\u2014\u800c\u610f\u4e49\u7684\u9996\u8981\u8f7d\u4f53\u662f\u8bed\u8a00\u3002\u2192 Linguistic Turn

    PoL\u7684\u5176\u5b83topic\uff1a 1. \u6307\u79f0\u4e0e\u5b9e\u4f53\uff0c\u8bed\u8a00\u4e0e\u610f\u4e49\u7684\u5173\u7cfb 2. \u901a\u540d\u4e0e\u4e13\u540d\uff0c\u8bcd\u4e49\u7684\u8303\u56f4 3. \u771f\u7406\u7406\u8bba 4. \u300a\u6211\u4eec\u8d56\u4ee5\u751f\u5b58\u7684\u9690\u55bb\u300b\uff1a\u9690\u55bb\u65e0\u5904\u4e0d\u5728\uff0c\u4e0d\u4ec5\u5b9a\u4e49\u4e2d\u7684\u201cxx\u662fxx\u201d\u662f\u9690\u55bb\uff0c\u6709\u65f6\u5355\u4e2a\u8bcd\u5c31\u662f\u4e00\u4e2a\u9690\u55bb\u3002

    \u52a8\u8bcd\u662f\u9690\u55bb 

    \u65f6\u95f4\u5728\u6d41\u901d\u3002\n

    \u4ecb\u8bcd\u662f\u9690\u55bb 

    I\u2019m feeling up today.\nHe is down.\n\u9ad8\u5174\u4e3a\u4e0a\uff0c\u60b2\u4f24\u4e3a\u4e0b\u3002\nWake up.\nHe fell asleep.\n\u6709\u610f\u8bc6\u4e3a\u4e0a\uff0c\u65e0\u610f\u8bc6\u4e3a\u4e0b\u3002\nHe fell ill.\nShe dropped dead.\n\u5065\u5eb7\u548c\u751f\u547d\u4e3a\u4e0a\uff0c\u75be\u75c5\u548c\u6b7b\u4ea1\u4e3a\u4e0b\u3002\nI have controlled over her.\nHe fell from power.\n\u63a7\u5236\u6216\u5f3a\u8feb\u4e3a\u4e0a\uff0c\u88ab\u63a7\u5236\u6216\u88ab\u5f3a\u8feb\u4e3a\u4e0b\u3002\nMy income rose last year.\nThe number of errors is low.\n\u66f4\u591a\u4e3a\u4e0a\uff0c\u66f4\u5c11\u4e3a\u4e0b\u3002\n

    \u4e54\u59c6\u65af\u57fa\uff1a

    \u7ed3\u6784\u4e3b\u4e49\u8bed\u8a00\u5b66\u5230\u8f6c\u6362\u751f\u6210\u8bed\u6cd5\u3002

    1. \u8bed\u8a00\u80fd\u529b/\u8bed\u8a00\u8868\u73b0\uff1a\u8bed\u8a00\u80fd\u529b\u662f\u4eba\u5148\u5929\u5177\u6709\u7684\u72ec\u7acb\u80fd\u529b\uff0c\u5b83\u901a\u8fc7\u5b66\u4e60\u67d0\u79cd\u6216\u67d0\u4e9b\u7279\u5b9a\u8bed\u8a00\u5c55\u73b0\u51fa\u6765\u3002
    2. \u6df1\u5c42\u7ed3\u6784/\u8868\u5c42\u7ed3\u6784\uff1a\u6df1\u5c42\u7ed3\u6784\u901a\u8fc7\u8f6c\u6362\u89c4\u5219\u751f\u6210\u8868\u5c42\u7ed3\u6784\u3002

    \u8bed\u8a00\u5b66\u7684\u5de5\u4f5c\u4e0d\u5e94\u5f53\u662f\u641c\u96c6\u8bed\u8a00\u7d20\u6750\u52a0\u4ee5\u5f52\u7eb3\uff0c\u800c\u662f\u8981\u89e3\u91ca\u8bed\u8a00\u7684\u521b\u9020\u6027\u3002

    CNF 

    S -> AB\nA -> AA | a\nB -> b | e\n

    \u8f6c\u6362\u751f\u6210\u8bed\u6cd5\u89c4\u5219 \\(\\Sigma = \\{NP, Vp, T, N, Npsing, NPpl, Aux, V, C, M, En, S, Past, Af\\}\\) 

    S -> NP + VP\nVP -> Verb + NP\nNP -> Det + N\nVerb -> Aux + V\nDet -> the, a...\nN -> man, ball...\nAux -> will, can...\nV -> hit, see...\n

    \u4f20\u7edf\uff08\u6210\u5206\uff09\u8bed\u6cd5\u89c4\u5219 

    1. \u4e3b + \u8c13\n2. \u4e3b + \u8c13 + \u5bbe\n3. \u4e3b + \u7cfb + \u8868\n4. \u4e3b + \u8c13 + \u5bbe + \u53cc\u5bbe\n5. \u4e3b + \u8c13 + \u5bbe + \u5bbe\u8865\n6. \u4e3b + \u8c13 + \u5e76\u5217\u5bbe\n\n...\n

    \u300a\u53e5\u6cd5\u7ed3\u6784\u300b\uff081957\uff09\u6838\u5fc3\u53e5\u548c\u8f6c\u6362\u6982\u5ff5\u3002

    \u751f\u6210\u6b65\u9aa4 1. \u751f\u6210\u6838\u5fc3\u53e5\u3002 

    S -> X1 | X2 | ... Xn\n

    1. \u8f6c\u6362\u7ed3\u6784\uff08\u66ff\u6362\u3001\u7701\u7565\u3001\u6dfb\u52a0\u3001\u6362\u4f4d\uff09\u3002 

      X1 -> Y1Z1 | ...\n...\n

    2. \u6dfb\u52a0\u5f62\u6001\u97f3\u4f4d\u89c4\u5219\u3002 

      Z1 -> W1\n...\nZn -> Wn\n

    \u8f6c\u6362\uff1a\u6574\u4e2a\u8f6c\u6362\u751f\u6210\u8fc7\u7a0b\u53ef\u4ee5\u5206\u4e3a\u4e09\u4e2a\u6b65\u9aa4

    1. \u901a\u8fc7\u77ed\u8bed\u7ed3\u6784\u6539\u5199\u89c4\u5219\uff0c\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_c\\)\uff0c\\(R_c\\)\u7531\u975e\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u662f\u6df1\u5c42\u7ed3\u6784\u3002
    2. \u901a\u8fc7\u8bcd\u6c47\u63d2\u5165\u89c4\u5219\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_1\\)\uff0c\\(R_1\\)\u7531\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u4f46\u4ecd\u662f\u6df1\u5c42\u7ed3\u6784\u3002
    3. \u901a\u8fc7\u8f6c\u6362\u89c4\u5219\u5f97\u5230\u8868\u8fbe\u5f0f\\(R_1\\)\uff0c\\(R_1\\)\u5f53\u7136\u8fd8\u662f\u7531\u975e\u7ec8\u7aef\u8bed\u7c7b\u7b26\u53f7\u7ec4\u6210\uff0c\u4f46\u5b83\u662f\u8868\u5c42\u7ed3\u6784\u3002

    \u6df1\u5c42\u7ed3\u6784\u548c\u8868\u5c42\u7ed3\u6784

    \u4e54\u59c6\u65af\u57fa\u8bed\u6cd5\u4f53\u7cfb\u4e2d\uff0c\u6307\u53e5\u5b50\u751f\u6210\u8fc7\u7a0b\u4e2d\u7279\u5b9a\u9636\u6bb5\u6240\u91c7\u7528\u7684\u4e00\u79cd\u7279\u6b8a\u64cd\u4f5c\u624b\u6bb5\u6216\u89c4\u5219\u3002\u6df1\u5c42\u7ed3\u6784\u662f\u5b83\u7684\u8f93\u5165\uff0c\u8868\u5c42\u7ed3\u6784\u662f\u5b83\u7684\u8f93\u51fa\u3002

    \u6709\u7684\u53e5\u5b50\u8868\u5c42\u7ed3\u6784\u4e0d\u540c\uff0c\u6df1\u5c42\u7ed3\u6784\u76f8\u4f3c\u3002\u901a\u8fc7\u8f6c\u6362\u64cd\u4f5c\u53ef\u4ee5\u76f8\u4e92\u8f6c\u5316\u3002

    \u6709\u7684\u53e5\u5b50\u6df1\u5c42\u7ed3\u6784\u4e0d\u540c\uff0c\u8868\u5c42\u7ed3\u6784\u76f8\u4f3c\u3002\u901a\u8fc7\u8f6c\u6362\u64cd\u4f5c\u4e0d\u80fd\u76f8\u4e92\u8f6c\u5316\u3002

    \u4e3a\u4ec0\u4e48\u4eca\u5929\u6211\u4eec\u8981\u8c08\u8bed\u8a00\u54f2\u5b66\uff1f

    \u9648\u5609\u6620\u8001\u5e08\uff1a\u79d1\u5b66\u662f\u4e00\u4e2a\u4e25\u5bc6\u7684\u6574\u6d01\u7684\u4f53\u7cfb\uff0c\u539f\u56e0\u662f\u5b83\u628a\u6240\u6709\u6df7\u6c8c\u7684\u65e0\u6cd5\u89e3\u51b3\u7684\u95ee\u9898\u629b\u5728\u4e86\u8fd9\u4e2a\u4f53\u7cfb\u4e4b\u5916\u3002[\u300a\u8d70\u51fa\u552f\u4e00\u771f\u7406\u89c2\u300b\uff0c2020]

    \u6240\u4ee5\u54f2\u5b66\u7684\u95ee\u9898\u662f\u7814\u7a76\u88ab\u79d1\u5b66\u6254\u51fa\u53bb\u7684\u6df7\u6c8c\u3002

    \u8bed\u8a00\u54f2\u5b66\u5c31\u50cf\u201c\u5165\u4fb5\u7684\u5b9e\u5728\u754c\u201d\uff0c\u201c\u8fb9\u754c\u7684\u6d4b\u8bd5\u70b9\u201d\u3002

    "},{"location":"docs/2-ling/philosophy/pol_zh/#recommended-reading","title":"Recommended Reading","text":"

    \u300a\u8bed\u8a00\u54f2\u5b66\u300b\u9648\u5609\u6620

    \u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u7d22\u7eea\u5c14

    \u300a\u903b\u8f91\u54f2\u5b66\u8bba\u300b\u7ef4\u7279\u6839\u65af\u5766

    \u300a\u54f2\u5b66\u7814\u7a76\u300b\u7ef4\u7279\u6839\u65af\u5766

    \u300a\u6211\u4eec\u8d56\u4ee5\u751f\u5b58\u7684\u9690\u55bb\u300b\u4e54\u6cbb\u00b7\u83b1\u8003\u592b

    \u300a\u5fc3\u667a\u3001\u8bed\u8a00\u548c\u673a\u5668\u300b\u5f90\u82f1\u747e

    "},{"location":"docs/2-ling/philosophy/pol_zh/#_1","title":"\u8ba8\u8bba","text":"

    \u662f\u5426\u6240\u6709\u6ca1\u6709\u7528\u8bed\u8a00\u8868\u8fbe\u7684\u77e5\u8bc6\uff0c\u90fd\u53ef\u4ee5\u88ab\u7528\u8bed\u8a00\u8868\u8fbe\uff1f\uff08not NP or NP-hard\uff09

    \u53ea\u5b66\u4e60\u8bed\u8a00\u662f\u5426\u80fd\u6a21\u62df\u4eba\u7684\u667a\u80fd\u6c34\u5e73\uff1f

    \u6a21\u578b\u662f\u5426\u9700\u8981\u5e94\u5bf9\u6240\u6709\u7684\u5f02\u5e38\u60c5\u51b5/\u673a\u5668\u8bed\u8a00\u7684\u76ee\u6807\u672c\u8eab\u8981\u4e0e\u4eba\u7c7b\u8bed\u8a00\u6709\u6240\u533a\u522b

    "},{"location":"docs/2-ling/philosophy/saussure/","title":"Reading Notes of Cours de linguistique g\u00e9n\u00e9rale, Ferdinand de Saussure","text":"

    :material-circle-edit-outline: \u7ea6 685 \u4e2a\u5b57 :fontawesome-solid-code: 5 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    \u300a\u666e\u901a\u8bed\u8a00\u5b66\u300b\u7d22\u7eea\u5c14 \u8bfb\u4e66\u7b14\u8bb0

    \u7b2c\u96f6\u7f16\uff1a\u7eea\u8bba

    \u7b2c\u4e09\u7ae0\uff1a\u8bed\u8a00\u5b66\u7684\u5bf9\u8c61

    \u8bed\u97f3\u4e0e\u8bed\u4e49\u7684\u8054\u7cfb 

        _______________________\n   |                       |\n   |                       \u2228\nc <-> i                 i <-> i \n  \u542c\u97f3                    \u53d1\u97f3\n   \u2227                       |\n   |_______________________|\n
    c\uff1a\u6982\u5ff5

    i\uff1a\u97f3\u54cd\u5f62\u8c61

    \u8bed\u8a00\u7814\u7a76\u7684\u5bf9\u8c61

    \u7b2c\u516d\u7ae0\uff1a\u6587\u5b57\u8868\u73b0\u8bed\u8a00

    \u8bed\u97f3\u7684\u53d1\u5c55\u662f\u5386\u53f2\u6027\u7684\u3002

    \u7b2c\u4e03\u7ae0\uff1a\u97f3\u4f4d\u5b66 phonetics

    \u7b2c\u4e00\u7f16\uff1a\u4e00\u822c\u539f\u5219

    \u7b2c\u4e00\u7ae0\uff1a\u8bed\u8a00\u7b26\u53f7\u7684\u6027\u8d28

    \u7b26\u53f7\u7684\u7ed3\u6784\uff1a\n     ________________   \u4e0a\n    |   \u6982\u5ff5 -> \u6240\u6307  |\n    -----------------\n    | \u97f3\u54cd\u5f62\u8c61 -> \u80fd\u6307 |   \n    |________________|  \u4e0b\n

    \u80fd\u6307\u7684\u5c5e\u6027

    \u7b26\u53f7\u5728\u65f6\u95f4\u4e0a\u7684\u8fde\u7eed\u6027\u548c\u65f6\u95f4\u4e0a\u7684\u53d8\u5316\u76f8\u8fde\uff0c\u7b26\u53f7\u7684\u4efb\u610f\u6027\u4f7f\u5176\u65e0\u6cd5\u62b5\u5fa1\u4f7f\u80fd\u6307\u5728\u6240\u6307\u4e0a\u6ed1\u52a8\u7684\u56e0\u7d20\u3002

    \u4e00\u5207\u79d1\u5b66 

            C\n        |\n        |\nA ------------- B  \u540c\u65f6\u8f74\u7ebf\n        |\n        |\n        D\n      \u8fde\u7eed\u8f74\u7ebf\n

    \u8bed\u8a00\u5b66 

            C\n        |\n        |\nA ------------- B  \u9759\u6001\u8bed\u8a00\u5b66\uff08\u5171\u65f6\uff09\n        |\n        |\n        D\n    \u6f14\u5316\u8bed\u8a00\u5b66\uff08\u5386\u65f6\uff09\n

    \u5185\u5728\u4e8c\u91cd\u6027\u4f8b\u8bc1

            -> \u5171\u65f6\n       \u00b7<--------->\u00b7  \u7532\u65f6\u671f\n  |    |           |\n  \u2228    \u2228           \u2228\n \u5386\u65f6   \u00b7<--------->\u00b7  \u4e59\u65f6\u671f\n

    \u53ef\u4ee5\u6bd4\u4f5c\u4e0b\u68cb\uff1a\u8861\u5b9a\u7684\u89c4\u5219\u548c\u53d8\u52a8\u7684\u5c40\u52bf

    \u7b2c\u4e8c\u7f16\uff1a\u5171\u65f6\u8bed\u8a00\u5b66

    \u540c\u4e00\u6027\uff1a\u5171\u65f6 - \u97f3\u6bb5 -> \u610f\u4e49

    \u666e\u904d\u4ef7\u503c\uff1a

    \u8bed\u8a00\u4e4b\u4e2d\u53ea\u6709\u5dee\u522b -\u2014\u2014 \u6ca1\u6709\u79ef\u6781\u8981\u7d20\u7684\u5dee\u522b\u3002\u8bed\u8a00\u662f\u5f62\u5f0f\u800c\u4e0d\u662f\u5b9e\u8d28\u3002

    \u7b2c\u4e94\u7ae0

    \u7b2c\u516d\u7ae0\uff1a\u8bed\u8a00\u7684\u673a\u6784

    \u53e5\u6bb5\u7684\u8fde\u5e26\u5173\u7cfb\uff1a\u6574\u4f53\u7684\u4ef7\u503c\u53d6\u51b3\u4e8e\u5b83\u7684\u90e8\u5206\uff0c\u90e8\u5206\u7684\u4ef7\u503c\u51b3\u5b9a\u4e86\u5b83\u4eec\u5728\u6574\u4f53\u4e2d\u7684\u5730\u4f4d\u3002

           ----------\n        d\u00e9-faire\n       ----------\n         /    \\\n    d\u00e9coller  faire\n       /         \\\n    d\u00e9lancer    refaire\n     /             \\\n d\u00e9cendre        contrefaire\n

    \u6b63\u662f\u8fd9\u4e9b\u4e0d\u540c\u7684\u5f62\u5f0f\u6f02\u6d6e\u5728\u5468\u56f4\uff0c\u8fd9\u4e24\u4e2a\u8bcd\u624d\u80fd\u5206\u89e3\u6210\u5355\u4f4d\uff0c\u6216\u6210\u4e3a\u53e5\u6bb5\u3002

    \u53ea\u6709\u4e00\u90e8\u5206\u7b26\u53f7\u662f\u7edd\u5bf9\u4efb\u610f\u7684\uff0c\u4efb\u610f\u6027\u4e0d\u80fd\u53d6\u6d88\uff0c\u90fd\u6709\u7a0b\u5ea6\u5dee\u522b\uff0c\u7b26\u53f7\u53ef\u80fd\u662f\u76f8\u5bf9\u5730\u53ef\u4ee5\u8bba\u8bc1\u7684\u3002

    \u6574\u4f53 > \u90e8\u5206\u4e4b\u548c\u3002poirexier > poiretier

                     ------\n               /        \\\n    \u8bcd\u6c47     -             -   \u8bed\u6cd5\n\u4e0d\u80fd\u8bba\u8bc1\u7684\u6781\u7aef   \\        /    \u53ef\u4ee5\u8bba\u8bc1\u7684\u6781\u7aef\n    \u7b26\u53f7         -------       \u7ed3\u6784\n

    \u7b2c\u4e03\u7ae0\uff1a\u8bed\u6cd5\u548c\u533a\u5206

    \u62bd\u8c61\u5b9e\u4f53\uff0c\u6700\u540e\u5206\u6790\u8d77\u6765\uff0c\u603b\u662f\u4ee5\u5177\u4f53\u5b9e\u73b0\u4e3a\u57fa\u7840\u7684\u3002

    \u7b2c\u4e09\u7f16\uff1a\u5386\u65f6\u8bed\u8a00\u5b66

    \u7b2c\u4e09\u7ae0\uff1a\u8bed\u97f3\u6f14\u5316\u5728\u8bed\u6cd5\u4e0a\u7684\u540e\u679c

    \u7b2c\u56db\u7ae0\uff1a\u7c7b\u6bd4

    \u7b2c\u4e94\u7ae0\uff1a\u7c7b\u6bd4 -> \u6f14\u5316

    viendre, monru, traisait

    \u7b2c\u516d\u7ae0\uff1a\u6d41\u4fd7\u8bcd\u6e90

    "},{"location":"docs/2-ling/pragmatics/ca_da/","title":"Research Methods: Conversation Analysis and Discourse Analysis","text":"

    :material-circle-edit-outline: \u7ea6 275 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/ca_da/#discourse-analysis","title":"Discourse Analysis","text":"

    Some discourse analysis are taught in linguistic departments (Johnstone, 2018)

    Foucault (1972, 1980) use 'discourse' to refer to the ways of talking and thinking constitute ideologies (set of interrelated ideas) and serve to circulate power in society, and in the sense involved patterns of belief and habitual actions as well as patterns of language.

    Johnstone, Barbara. 2018. Discourse Analysis (3rd ed.). UK: Wiley-Blackwell.

    "},{"location":"docs/2-ling/pragmatics/ca_da/#conversational-analysis","title":"Conversational Analysis","text":"

    Definition

    Conversation analysis is the study of interactional activities. The object being studied involves at least two persons.

    Unit

    conversation > sequence > adjacency pair > turn

    types of adjacency pairs

    turn-taking feature

    One involved in a conversation is supposed to give floor to the other party (parties) at a proper point of time. to keep the balance between the time one spends talking and the time the others spend talking.

    pre-sequence

    insertion sequence

    A: Are you coming tonight?\nB: Can I bring a guest?\nA: Male or female?\nB: What difference does that make?\nA: An issue of balance.\nB: Female.\nA: Sure.\nB: Yeah, I\u2019ll be there.\n

    preference organization

    first part second part preferred dispreferred assessment agree disagree invitation accept refuse offer accept decline proposal agree disagree request acccept refuse"},{"location":"docs/2-ling/pragmatics/intro/","title":"Introduction and Concepts","text":"

    :material-circle-edit-outline: \u7ea6 1923 \u4e2a\u5b57 :fontawesome-solid-code: 11 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/intro/#what-is-pragmatics","title":"What is Pragmatics","text":""},{"location":"docs/2-ling/pragmatics/intro/#how-pragmatics-differ-from-other-linguistics-branches","title":"How pragmatics differ from other linguistics branches?","text":"

    Charles W. Morris (1901-1979) American semiotician and philosopher. supervised by Charles S. Pierce. In his Foundations of the Theory of Signs (1938), Morris proposed that semiotics should have three divisions:

    syntax  -------------> semantics -------------> pragmatics\n              \u2b06\ufe0f\u00a0                        \u2b06\ufe0f\u00a0           \n                        decoding              use in context\n

    During the course of everyday communication, human beings as social animals convey more than the literal, propositional meaning (i.e. we don\u2019t always mean what we say literally).

    There is more to the literal meaning of a sentence when we consider the sentence in relation to the context, i.e., the situation of uttering the sentence.

    Sentence that cannot be considered in isolation \u2192 utterance

    Pragmatics looks beyond truth-conditional meanings, and explores non-literal, implicit, context-related meanings.

    Thus both semantics and pragmatics deal with meaning, yet there is a division of labour: semantics deals with meaning in context.

    "},{"location":"docs/2-ling/pragmatics/intro/#levels","title":"Levels","text":""},{"location":"docs/2-ling/pragmatics/intro/#context-deixis-and-reference","title":"Context, Deixis and Reference \u8bed\u5883\uff0c\u6307\u793a\u4e0e\u6307\u79f0","text":""},{"location":"docs/2-ling/pragmatics/intro/#deixis","title":"Deixis","text":"

    Definition

    Deixis and context: Deictic does not have concrete meanings. Deictic words depend on context for meaning.

    Types of deixis

    defined in relation to the deictic center (person, time, place, discourse, social)

    The deictic cycle. Harman, 1990.

    "},{"location":"docs/2-ling/pragmatics/intro/#reference","title":"Reference","text":"

    Definition: The act of using a word/phrase to pick out something in the world.

    Types of referring expressions (\u6307\u793a\u8bed)

    Choice of referring expressions: based on the speaker\u2019s assumption about what the listener knows.

    Conditions for successful reference: must be collaborative

    "},{"location":"docs/2-ling/pragmatics/intro/#presupposition","title":"Presupposition","text":"

    Differences between semantic and pragmatic presuppositions

    for pragmatic presupposition

    cancellation of presuppositions

    Presuppositions are cancellable or defeasible by changing the words to alter the previous proposition.

    F: \u6709\u4e9b\u4eba\u517b\u732b\u4e86\n~F: \u6709\u4e9b\u4eba\u6ca1\u517b\u732b\n

    projection problem

    presupposition may not survive when simple sentences are projected into complex ones.

    Mary didnt manage to find a job.\nMary didnt manage to find a job. In fact, she didnt even try.\n
    Mike didnt date Mary again.\nMike didnt date Mary gain, if indeed he ever did.\n

    presupposition triggers (\u89e6\u53d1\u8bed): how to determine speakers\u2019 presupposition in the course of verbal communication?

    "},{"location":"docs/2-ling/pragmatics/intro/#conversational-implicature","title":"Conversational Implicature","text":"

    Implicature

    Grice\u2019s theory of conversational implicature, Logic and Conversation.

    An outline of a systematic theory of language use, which can account for the way people read between the lines when understanding everyday language.

    meaning of a sentence

    Grice\u2019s new terms

    Grice draws a distinction

    - Smith doesn't seem to have a girlfriend these days.\n\n- He has been paying a lot of visits to New York lately.\n\n=> entailment: he visits New York recently\n=> implicature: Smith may be having a girlfriend in New York.\n

    features

    Grice\u2019s cooperative principle

    common purpose/common direction: Conversational partners normally recognize a common purpose or a common direction in their conversation.

    common objectives (~= joint project): At any point of a conversation, certain \u201cconversational moves\u201d are judged suitable or unsuitable for accomplishing their common objectives.

    How the cooperative principle is applied:

    How to follow the maxims:

    How to break the maxims:

    The cooperative maxims are guidelines instead of rules. They can be creatively infringed/violated.

    The Horn scales & scalar implicature

    When any form on a scale (most, some, always, often, must, may\u2026) is used or asserted, the negative of all forms higher on the scale is implicated.

    types of implicature

    graph TD\nimplicatures --> conventional/lexical\nimplicatures --> conversational\nconversational --> generalized\nconversational --> particularized\n
    "},{"location":"docs/2-ling/pragmatics/intro/#lexical-pragmatics","title":"Lexical Pragmatics","text":"

    Criticism of relevance theory

    To calculate the processing cost,

    Lexical pragmatics

    pragmatic enrichment

    graph TD\n\npragmatic_enrichment --> pragmatic_narrowing\npragmatic_enrichment --> pragmatic_broadening\npragmatic_broadening --> approximation\npragmatic_broadening --> metaphorical_extension\n
    "},{"location":"docs/2-ling/pragmatics/socio/","title":"Sociopragmatics","text":"

    :material-circle-edit-outline: \u7ea6 129 \u4e2a\u5b57

    \u8fd9\u5757\u5185\u5bb9\u4f3c\u4e4e\u6ca1\u6709\u8bb2\u5f88\u591a\u4e1c\u897f. \u7c98\u4e00\u70b9ppt\u539f\u8bdd

    Intercultural Pragmatics

    Intercultural Pragmatics has the potential to help establish a \u201charmonious\u201d interaction and relationship between people from different cultures.

    IP aims to study how to deal with the differences arising from cross-cultural communication and how they may affect the universality of pragmatic principles (theory of speech acts, co-

    operative principle, politeness principle, etc.)

    intercultural pragmatics\u2019 two way perspective

    sociopragmatics

    "},{"location":"docs/2-ling/pragmatics/theories/","title":"Theories and Hypothesis","text":"

    :material-circle-edit-outline: \u7ea6 810 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/2-ling/pragmatics/theories/#speech-act-theory","title":"Speech Act Theory \u8a00\u8bed\u884c\u4e3a\u7406\u8bba","text":"

    Speech action definition:

    Speech act theory:

    A speech act = locutionary act + illocutionary act + perlocutionary act

    Illocutionary force \u8bed\u529b: communicative purposes or social functions

    Classification of speech act

    Funtion-based classification system:

    by John Searle, UCB philosopher

    Structure-based classification system:

    "},{"location":"docs/2-ling/pragmatics/theories/#politeness-theory","title":"Politeness Theory","text":"

    Development of Gricean theory

    Definition of politeness theory

    Conversationalists work together, each trying to maintain his/her own face and the face of his/her counterpart.

    type of face

    Acts involved

    Leech\u2019s six Politeness Principle: extension of Gricean theory

    (Note that the term \u2018neo-Gricean\u2019 is most often used to describe the works of Laurence Horn, Stephen Levinson, etc. not other theories e.g. relevance theory)

    "},{"location":"docs/2-ling/pragmatics/theories/#relevance-theory","title":"Relevance Theory","text":"

    Only preserving the maxim of relation in Gricean theory

    Definition of relevance theory

    its investigates how aspects of meaning are generated in context and in relation to the speakers intentions.

    R(relevance) = E(#contextual effects)/C(cost of efforts in obtaining E)

    Relevance is higher when cognitive effects are higher, but it is lower when more processing efforts is required.

    Two aspects of relevance principle

    Application of RT

    "},{"location":"docs/2-ling/semantics/","title":"Index","text":""},{"location":"docs/2-ling/semantics/#contents","title":"Contents","text":"

    1 - Definition Clearification

    This chapter provides a brief introduction to the terminologies involved in semantics.\n

    2 - Logics & Formal Semantics

    This chapter first introduces the semiotics in formal semantics (which adopts a similar system with that in the logics). It then discusses about the semantics in two perspectives: the propositional logic and the predicate logic. It also introduces several basic rules in logic inference.\n

    3 - Scope Ambiguity

    This chapter discusses on the unsolved questions in scope ambiguity.\n
    "},{"location":"docs/2-ling/semantics/#grading","title":"Grading","text":"

    mid-term: 35%

    final: 50%

    participation: 15%

    "},{"location":"docs/2-ling/semantics/#two-tests","title":"Two tests","text":"

    Two tests will be given during the term, one in the middle and one at the end of the term, covering all the material covered up to that point in the course. The tests will be a combination of various types of questions, including true/false and short essay.

    "},{"location":"docs/2-ling/semantics/#final-review-for-fun","title":"Final Review & For Fun","text":"

    :material-circle-edit-outline: \u7ea6 629 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    The following parts are written in preparation for the final review but I upload it as well for you to read for fun.

    "},{"location":"docs/2-ling/semantics/#noble-semanticians","title":"Noble Semanticians","text":"Name Field Contribution Live Nation Institution Fun facts Noam Chomsky mainly in syntax generative grammar, transformational grammar, government and binding theory, minimalist program, productivity of language, recursivity of language 1928- USA MIT Most prominent linguist alive Ferdinand de Saussure linguist and semiotician founder of semiotics. concepts: sign, signifier vs. signified, diachronic vs. synchronic, language vs. parole, paradigmatic vs. syntagmatic 1857-1913 Switzerland University of Geneva, Switzerland Charles Sanders Peirce philosopher, mathematician, logician founder of semiotics. concepts: index, icon, symbol. 1839-1914 Milford Pennsylvania JHU Michel Br\u00e9al comparative grammar coined the term \u201csemantics\u201d, diachronic focus 1832-1915 born in Rheinlan (Germany), studied in Paris and Berlin in Paris Leonard Bloomfield structural linguistics structural linguistics, language as a self-regulating system, behaviorism(stimulus-response testing) 1887-1949 Yale University reject introspection Aristotle polymath term logic, initiator of western scientific tradition 384-322 BC Stagira, Greece tutor of Alexander the Great Gottlob Freg philosopher, logician, mathematician predicate logic, sense(sentence\u2019s proposition) vs. reference (its truth value) 1848-1925 German University of Jena extreme right-wing views Peter Geach philosopher, professor of logic donkey sentence (1962) 1916-2013 England Oxford Richard Montegue semanticist Montegue grammar: syntax and semantics go together 1930-1971 student of Alfred Tarski, gay man, killed in his apartment, four influential papers Gareth Evans philosopher philosophy of mind, work on reference, e-type anaphora 1946-1980 England Oxford Irene Heim semanticist definite and indefinite pronouns 1954- German, Munich MIT, phd 1982 advisor: Barbara Partee Hans Kamp philosopher and linguist discourse representation theory (DRT) 1954- Dutch Bertrand Russell philosopher, logician logic, philosophy of mathematician 1872-1970 Wales, Britain Cambridge Henri\u00ebtte de Swart linguist tense and aspect, negation, bare nominals and indefinite noun phrases. She has also investigated the role of semantics in language evolution, and was involved in the development of bidirectional optimality theory. 1961- Dutch director of Netherlands Graduate School of Linguistics and Utrecht Institute of Linguistics"},{"location":"docs/2-ling/semantics/#example-questions","title":"Example questions","text":"

    What is a donkey pronoun?

    A donkey sentence is such that an expected existential is interpreted as universal taking wide scope.\n

    What is a discourse pronoun:

    outside the scope of existing quantifier\ne.g. No student studies semantics. He is outside.\n

    The scope of a quantifier is always bound in the clause it appears.

     True\n

    What is quantifier raising?

    Chmosky and May.\nLF, \n

    What are De Morgan\u2019s laws?

    ~(p or q) <=> (~p) and (~q)\n~(p and q) <=> (~p) or (~q)\n

    What are conditional laws

    p -> q <=> ~p or q\n

    When is the indefinite \u201ca\u201d not an existential quantifier?

    1. donkey sentence\n2. generic noun phrase. A woman is difficult to please. \\forall x(Wx -> Dx)\n3. John is a plumber.pj\n

    2 readings: Some boy smiled at Jane and some boy kissed Molly.

    \\exist x(Bx and Sx,j and Kx,m)\n\\exist x(Bx and Sx,j) and \\forall y(By and Ky,m)\n

    2 Types of Recursion

    embedding and coordination\n
    "},{"location":"docs/2-ling/semantics/ambiguity/","title":"Ambiguity","text":""},{"location":"docs/2-ling/semantics/ambiguity/#scope-ambiguity","title":"Scope Ambiguity","text":""},{"location":"docs/2-ling/semantics/ambiguity/#scope-and-anaphora","title":"Scope and Anaphora","text":"

    antecedent vs. postcedent

    anaphor vs. cataphor

    Predicate logic is suited to capture natural language meaning

    allow recursion = recursivity

    two sources of recursion

    some boy kissed every girl.\n\nEvery girl was kissed by some boy.\n
    Someone mentioned tehy called everyone.\n\n\\forall x: Px\\forall y(M(x, Cxy))\n

    linear order: negative polarity item

    graph TD\n  DS -.Transformation.-> SS\n    SS -.send off.-> PF\n    SS -.send off.-> LF\n    PF -.acoustic representation.-> SS\n    LF -.semantic interpretation.-> SS\n

    Transformation:

    CALLOUT: annotation, connotation and denotation

    "},{"location":"docs/2-ling/semantics/ambiguity/#solution-for-scope-ambiguity","title":"Solution for scope ambiguity","text":"

    Quantifier-raising - NC RM - syntactic structure comes before the semantic structure - The movement we make in SS to remove ambiguity in DS is called quantifier-raising. - take the quantifier to the higher position to show the scope

    Quantifier-in - Montague grammar - The derivational illustration is called quantifier-in. - each predicate take an argument once a time

    Quantifier storage - Cooper storage - semantic ambiguity not represented in syntactic structure - semantic representation in which scope ambiguities are obtained without special syntactic rules

    "},{"location":"docs/2-ling/semantics/ambiguity/#quantifier-in","title":"Quantifier-in","text":"

    interrogative: asking a question 

    which woman does every man love?\n

    which scopes over every.

    "},{"location":"docs/2-ling/semantics/ambiguity/#scope-ambiguity_1","title":"Scope ambiguity","text":"

    e.g. some boy did not laugh. 

    \\exist x (Boy(x) and ~Laugh(x))\n~\\exist x (Boy(x) and Laugh(x))\n

    some boy kissed no girl. 

    \\exist x (Boy(x) and ~\\exist y (Girl(y) and Kiss(x, y)))\n~\\exist y (Girl(y) and \\exist x (Boy(x) and Kiss(x, y))): there was no girl kissed by a boy\n

    every boy kissed no girl. 

    \\forall x (Boy(x) and ~\\forall y(Girl(y) and Kiss(x, y)))\n

    "},{"location":"docs/2-ling/semantics/ambiguity/#deictic","title":"Deictic","text":"

    No boy said he was hungry.

    No boy was present. He was outside instead.: \u201che\u201d is trying to refer to \u201dno boy\u201d but outside the scope.

    pronoun \\(\\sub\\) anaphora

    "},{"location":"docs/2-ling/semantics/ambiguity/#discourse-anaphora","title":"Discourse Anaphora","text":"

    e.g. 

    Every student was present and she was interested.\n

    every: scopes over \u201cEvery student was present\u201d

    every: an indefinite quantifier. \u201cshe\u201d\u2019s antecedent is not clear

    \u201cshe\u201d is hardly bound by the antecedent. \u201cshe\u201d is free * ungrammatical: \u4e0d\u5408\u8bed\u6cd5\u7684, syntactic

    "},{"location":"docs/2-ling/semantics/ambiguity/#infelicitous-semantic-fit-the-context","title":"infelicitous: \u4e0d\u5408\u9002\u7684, semantic, fit the context","text":"

    :material-circle-edit-outline: \u7ea6 1349 \u4e2a\u5b57 :fontawesome-solid-code: 15 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 5 \u5206\u949f

    So we may conclude the following rules for e-type anaphora. BUT this part has NOT been verified with any authority. Do NOT take them as given truths during exams.

    e.g. No boy thinks that he has a chance. 

    ~\\exist x(Boy(x) and Think(x, Has-a-chance(x)))\n

    A particular boy said he wanted to kiss every girl. He then did it. 

    \\exist !x(Bx and  W(x, K(x, \\forall y(Gy -> K(x, y))))) and K(x, y)\n

    "},{"location":"docs/2-ling/semantics/ambiguity/#donkey-anaphora","title":"Donkey anaphora","text":"

    if a farmer owns a donkey, he beats it. 

    * \\exist x (Fx and \\exist y (Dy and O(x, y))) -> B(x, y)\n\\forall x \\forall y (Fx and Dy and O(x, y) -> B(x, y))\n

    = every farmer who owns a donkey beats it. 

    \\exist x(Fx and \\exist y (Dy and O(x, y)) -> B(x, y))  // y is free\n

    \u2757\u2757\u2757

    A donkey sentence is such that an expected existential is interpreted as universal taking wide scope.

    donkey pronoun can be: it, him, they (can also be plural forms)

    \u201ca\u201d: generic indefinite 

    A woman is a difficult thing to please.\n

    [Every farmer [who owns a donkey] beats it.]

    universal wide scope: it scopes more over the relative clause

    The problem - Existential with narrow scope - interpreted as universal with wide scope - in conditional clauses - in restriction of every

    Conclusion - the machinery of predicate logic is broken - cannot capture meaning of natural language

    If a student tries, she passes the exam. 

    (\\exist x(Sx and Tx)) -> Py   ; y is free\n\\exist x((Sx and Tx)) -> Py)\n

    interpretation 

    \\forall x((Sx and Tx) -> px)\n

    Solutions for donkey anaphora:

    Reference: Unselective Binding

    "},{"location":"docs/2-ling/semantics/ambiguity/#chapter-6-in-short-discoursedonkey-anaphora","title":"Chapter 6 in short: Discourse/Donkey Anaphora","text":"

    (\u52a0\u7c97\u7684\u662fDonkey anaphora\u548cE-type anaphora\u7684\u533a\u522b)

    Discourse: basic unit of interpretation

    Anaphoric relations in sentence and discourse - E-type anaphora: pronoun outside the scope of binder, not bound, content of pronoun reconstructed, reconstruction based on context - in separate sentences

        ```\n    A student came in. *She*(the student came in) had a question about the exam.\n    ```\n\n- in the same sentence but outside the scope\n    ```\n    If a student likes Copenhagen, *she*(for every case we examine, the student in question who likes Copenhagen) is happy.\n    ```\n\n- problem of compound: antecedent must appear as a noun?\n    ```\n    Bill owns a cat. Max takes care of it.\n    Bill is a cat-owner. # Max takes care of it.\n    ```\n

    Anaphora resolution - TODO

    "},{"location":"docs/2-ling/semantics/definitions/","title":"Definition Clarification","text":"

    :material-circle-edit-outline: \u7ea6 1068 \u4e2a\u5b57 :fontawesome-solid-code: 53 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/2-ling/semantics/definitions/#what-is-semantics","title":"What is semantics?","text":""},{"location":"docs/2-ling/semantics/definitions/#the-topics-involving","title":"The topics involving:","text":""},{"location":"docs/2-ling/semantics/definitions/#meaning-capturing-metalanguage-tools","title":"Meaning capturing: metalanguage tools","text":""},{"location":"docs/2-ling/semantics/definitions/#ways-to-capture-meaning-henriette-de-swart","title":"Ways to capture meaning: (Henri\u00ebtte de Swart)","text":""},{"location":"docs/2-ling/semantics/definitions/#predicatepredicate-calculusfirst-order-predicate-logic","title":"Predicate/Predicate Calculus/First-order Predicate Logic","text":""},{"location":"docs/2-ling/semantics/definitions/#map-of-linguistics-theory","title":"Map of Linguistics Theory","text":"
    graph TD\n  Language_Ability --> Competence\n  Language_Ability --> Performance\n  Competence --> Grammar\n  Competence --> Lexicon\n  Grammar --> Semantics\n  Grammar --> Phonology\n  Grammar --> Syntax\n  Grammar --> Pragmantics\n
    "},{"location":"docs/2-ling/semantics/definitions/#semantics-syntax","title":"Semantics & Syntax","text":""},{"location":"docs/2-ling/semantics/definitions/#syntax-needs-semantics","title":"Syntax needs semantics","text":""},{"location":"docs/2-ling/semantics/definitions/#semantics-needs-syntax","title":"Semantics needs Syntax","text":""},{"location":"docs/2-ling/semantics/definitions/#semantics-pragmatics","title":"Semantics & Pragmatics","text":""},{"location":"docs/2-ling/semantics/definitions/#context-and-deixis","title":"Context and Deixis","text":""},{"location":"docs/2-ling/semantics/definitions/#deixis-needs-context","title":"Deixis needs context","text":"

    Deixis is how objects, events and situations relate to the here and now of the speakers. It shows that utterance meaning cannot be fully determined by sentence meaning.

    (Last week) (I) play(ed) tennis with Chris.\n
    "},{"location":"docs/2-ling/semantics/definitions/#deictic-vs-anaphoric-use-of-pronouns","title":"Deictic vs. Anaphoric use of pronouns","text":"

    Deictic: pointing context Anaphoric: linguistic expression context. pronoun resolution: antecedent - pronoun

    \ud83d\udcad index - indices (higher register) / indexes \ud83d\udcad Desiderata (high-register way to say Goal, desideratum. sl.)"},{"location":"docs/2-ling/semantics/definitions/#map-of-semantics-taxomony","title":"Map of Semantics / Taxomony","text":"

    Semantics - lexical semantics - meaning of lexical items - smaller unites - mainly words - morphemes - compositional semantics - meaning of larger units - phrases and sentences - word combination

    "},{"location":"docs/2-ling/semantics/definitions/#utterance-sentence-proposition","title":"Utterance / Sentence / Proposition","text":""},{"location":"docs/2-ling/semantics/definitions/#lexical-semantics","title":"lexical semantics","text":" 
    abiguity: bank, punch, pitcher\nsynonymy: beautiful-lovely, antonymy: male-female\nhyponymy: set -> superset\ntaxonomy: set -> subset\nsymmetric relation: marry. mutually entail each other\nconverse relation: send, sell\nmeronomy:
    "},{"location":"docs/2-ling/semantics/definitions/#1-homonymy","title":"1) homonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#2-polysemy","title":"2) polysemy","text":""},{"location":"docs/2-ling/semantics/definitions/#3-synonymy","title":"3) synonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#4-antonymy","title":"4) antonymy","text":""},{"location":"docs/2-ling/semantics/definitions/#5-hyponymy","title":"5) hyponymy","text":""},{"location":"docs/2-ling/semantics/definitions/#6-meronymy","title":"6) meronymy","text":"

    part-whole relationship

    subtypes of meronymy

    pistachio - almond taxonymy\nlaugh - cry move in - move out\ncry - weep\nRMB - monetary unit\ngrilfriend - wife\nsit - stand\njump - hop\ngood - bad\nbeat - beet\nrise - fall reverse\ncigarette - cigar taxonymy\nkid - goat dragon - monster\n
    "},{"location":"docs/2-ling/semantics/definitions/#compositional-semantics","title":"Compositional semantics","text":""},{"location":"docs/2-ling/semantics/definitions/#inventory-of-components","title":"Inventory of components","text":""},{"location":"docs/2-ling/semantics/definitions/#important-linguistics","title":"Important linguistics","text":"

    Michel Br\u00e9al: coined semantics

    Ferdinand de Saussure: semiotician, diachronic vs. synchronic.

    Leonard Bloomfield: structural linguistics, Language, behaviorism(stimulus-response testing). reject introspection(theorize about language learning by thinking about on ones own experience)

    "},{"location":"docs/2-ling/semantics/definitions/#diachronic-synchronic","title":"Diachronic & Synchronic","text":""},{"location":"docs/2-ling/semantics/definitions/#signifier-signified-referent","title":"Signifier & Signified & Referent","text":""},{"location":"docs/2-ling/semantics/definitions/#langue-parole","title":"Langue & Parole","text":""},{"location":"docs/2-ling/semantics/definitions/#paradigmatic-syntagmatic","title":"Paradigmatic & Syntagmatic","text":"

    Noam Chomsky Syntax

    "},{"location":"docs/2-ling/semantics/definitions/#generative-grammar","title":"Generative Grammar","text":""},{"location":"docs/2-ling/semantics/definitions/#ambiguity","title":"Ambiguity","text":"

    e.g. Flying planes can be dangerous.

    graph TD\n  are --> planes\n    planes --> flying\n    are --> dangerous\n
    graph TD\n    is --> flying\n    flying --> planes\n    is --> dangerous\n
    "},{"location":"docs/2-ling/semantics/definitions/#pronoun-resolution","title":"pronoun resolution","text":""},{"location":"docs/2-ling/semantics/definitions/#inference","title":"Inference","text":"

    notes: cf. compare, e.g. for example

    graph TD\n  Inference --> Entailment\n  Inference --> Presuppositions\n  Inference --> Implicature\n

    any conclusion drawn from a set of propositions, from something someone has said and so on.

    "},{"location":"docs/2-ling/semantics/definitions/#entailment","title":"Entailment","text":" 
    Three girls were present. -> More than two girls were present.\nThree girls were not present. kills More than two girls were present.\n

    Cannot be cancelled

    # Three girls were present, but actually two girls come.\n#: semantically wrong\n
    "},{"location":"docs/2-ling/semantics/definitions/#presupposition","title":"Presupposition","text":" 
    Jim regrets ignoring the first problem. -> Jim has the first problem.\nJim does not regret ignoring the first problem. -> Jim has the first problem.\n

    cannot be cancelled

    # Jim regrets ignoring the first problem, but he does not have the first problem.\n
    "},{"location":"docs/2-ling/semantics/definitions/#implicature","title":"Implicature","text":" 
    Susan blushes when Jim looks at her, but she does not have a crush on him.\n
    "},{"location":"docs/2-ling/semantics/definitions/#compositionality","title":"Compositionality","text":"

    Proposed by Noam Chomsky, the term compositionality entails three dimension.

    "},{"location":"docs/2-ling/semantics/definitions/#principle-of-compositionally-of-meaning","title":"Principle of compositionally of meaning","text":"

    The meaning of the whole is a function of the meaning of its parts and the way they are put together.: \u2026 is determined by\u2026

    "},{"location":"docs/2-ling/semantics/formal_semantics/","title":"Logics & Formal Semantics","text":"

    :material-circle-edit-outline: \u7ea6 2560 \u4e2a\u5b57 :fontawesome-solid-code: 24 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 9 \u5206\u949f

    "},{"location":"docs/2-ling/semantics/formal_semantics/#metalanguage","title":"Metalanguage","text":" 
    a. January has 31 days.\nb. *******January******* has 7 letters.\nb*. 'January' has 7 letters.\n

    Liar sentence

    (31) Sentence (31) is false.\n

    solutions: (\u4e0d\u8003)

    "},{"location":"docs/2-ling/semantics/formal_semantics/#connectives-truth-and-truth-conditions","title":"Connectives, truth, and truth conditions","text":"

    logic overview

    graph TD\n  Logic --> Logic_from_antiquity\n    Logic --> Predicate_Logic\n    Logic_from_antiquity --> Term_Logic\n    Logic_from_antiquity --> Propositional_Logic\n

    logic from antiquity: older

    predicate logic: newer

    Aristotle: term logic

    Gottlob Frege: predicate logic

    "},{"location":"docs/2-ling/semantics/formal_semantics/#history-of-logics","title":"History of Logics","text":"

    Not applied for - question (?) - exclamation - modal: modal logic

    \ud83d\udcad ergo: therefore"},{"location":"docs/2-ling/semantics/formal_semantics/#term-logic","title":"Term logic","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#modus-ponens","title":"Modus Ponens","text":"

    Means of putting, MP syllogism, affirming the antecedent

    P(conditional statement): If it rain, I do not go to school.\nH: It rains.\nC: I do not go to class.\n

    Formal fallacy: affirming the consequent. Abductive reasoning. 

    P: If it rains, I will not go to class.\nH: I do not go to class.\nC: * It rains.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#modus-tollens","title":"Modus Tollens","text":"

    Means of carrying, MT syllogism, denying the consequent. 

    P: If it has not been cloudy, it does not rain.\nH: It rains.\nC: It has been cloudy.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#hypothetical-syllogism","title":"Hypothetical syllogism","text":"

    principle of transitivity 

    P: If it rains, the soils goes wet. If the soil goes wet, the plants grow.\nH: It rains.\nC: The plants grow.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#disjunctive-syllogism","title":"Disjunctive syllogism","text":"

    two premises and a conclusion 

    P: It either rains or its sunny.\nH: It rains.\nC: It is not sunny.\n

    "},{"location":"docs/2-ling/semantics/formal_semantics/#three-types-of-reasoning","title":"Three types of reasoning","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#propositional-logic","title":"Propositional logic","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#conditional-material-implication","title":"conditional, material implication","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#biconditional","title":"biconditional","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#de-swarts-formalizations","title":"De Swarts formalizations","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#well-formed-formula","title":"Well-formed formula","text":""},{"location":"docs/2-ling/semantics/formal_semantics/#propositional-practice","title":"Propositional practice","text":"John is happy. p John is not happy. ~p John is happy or sad. p or q exlusive John is happy, not sad. p and ~q If John has eaten, John is happy. p -> q If John has not eaten, John is not happy. ~p -> ~q John is hungry or thirsty. p or q inclusive. John left before you did. p John is not hungry or thirsty. ~(p or q inclusive) <-> ~p and ~q John is not hungry and thirsty. ~(p and q) <-> ~p or ~q inclusive If John did not laugh, then John cried. ~p \u2192 q \u2194 p or q If John laughed, then John also cried. p \u2192 q \u2194 ~p or q inclusive John did not laugh, or John cried. ~p or q \u2194 p \u2192 q John laughed, or John cried and beat on the table. p and (q or r) \u2194 (p and q) or (p and r) John is not happy, but rather sad. (scope of \u201cnot\u201d) ~p and q. * ~(p and q) John is not happy, or sad. ~(p and q) John is not happy, or John is sad. ~p or q John did not help us or hinder us. ~(p or q) \u2194 ~p and ~q John did not help us or John hinders us. ~p or q 
    John is friendly or John is not friendly.\n
    p V_e ~p T T F F T T 
    John is friendly and John is not friendly.\n
    p and ~p T F F F F T 
    It is not the case that John is not friendly.\n
    ~ ~ p T F T F T F

    contingent.

    It is not the case that John is hungry or John is not grumpy.\n
    ~( p or ~q F T T T F T T F F F T T T F F F"},{"location":"docs/2-ling/semantics/formal_semantics/#material-implication","title":"Material implication \u2192","text":"

    converse: q\u2192p. affirming the consequent

    inverse: ~p\u2192~q. denying the antecedent

    contrapositive: ~q\u2192~p. modus tollens

    given p\u2192q.

    Although it was extremely cold, Sally did not stay indoors.

    ~q->p\np and ~q\n

    We get a holiday, or we protest.

    ~p->q\np or q\n

    Jone said that Jane helped him.

    p\np and q\n

    John\u2019s sister burped

    p: John has a sister. presupposition, assume it true\nq: This sister burped.\np\np and q\n

    John arrives before Jane left

    p before q\n

    John did not arrive before Jane left.

    ~p before q\np ~before q\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#predication-and-quantification","title":"Predication and Quantification","text":"

    universal quantifier: every, each, all, any, only

    existential quantifier: a, some, there is \\(\\exist\\), for all \\(\\forall\\)

    predicate, argument

    John may like Sally.

    predicate: may like\n

    John has a crush on Sally.

    predicate: has a crush on\n

    Frank is the father of Susan.

    predicate: is the father of\n

    Frank is Susan\u2019s father.

    predicate: is...'s father\n

    Adjunct: if, probably, means, of course, early

    Valent, empty place holder: formal subject

    "},{"location":"docs/2-ling/semantics/formal_semantics/#collective-and-distributive-readings","title":"Collective and distributive readings","text":"
    Jogn and Molly ate a pizza.\np: one pizza, ate one together.   distributive\np and q: two pizzas, each ate a pizza.  collective\n
    Cinthia and Sam have saved 100 dollars.\np: together 100 dollars\np and q: 200 dollars\n

    Content verb is a predicate, but functional verbs are not

    John obviously spoke with Jane because he had to.

    predicate: spoke with\nargument: John, Jane\nadjuncts: obviously, because he had to.\n

    If I get a chance, I will probably try to avoid the mistake.

    predicate: will try to \nargument: I, avoid the mistake\nadjuncts: If I get a chance, probably\n

    John performed Jill\u2019s operation first.

    \n

    The person who talk loudly is Jim\u2019s father.

    predicate: is someone's father\nargument: the person who talk loudly, Jim\nadjunct: \n

    the talking loudly person

    predicate: talking\nargument: person\nadjunct: loudly\n

    predicate: the nodes that are connected in SUD parsing tree

    universal dependency (UD)

    syntactic-universal dependency (SUD)

    graph TD\n  Primitive_units_within_propositions --> Predicates\n  Primitive_units_within_propositions --> Arguments\n    Arguments --> individuals_Terms\n    individuals_Terms --> constants\n    individuals_Terms --> variables\n

    lexical predicates vs. syntactic predicates

    individual constants vs. individual variables

    e.g. We think John likes Susan.

    T(w, Lj,s)\n

    Types of predicates:

    e.g. Monica hid her bicycle.

    x hide y: Hx,y\nMonica: m\nher bicycle: b\nHm,b\n

    e.g. Monica did not hide her bicycle.

    x hide y: Hx,y\nMonica: m\nher bicycle: b\n~Hm,b\n

    e.g. Monica laughed and cried.

    Monica: m\nlaugh: L()\ncry: C()\nLm and Cm\n

    e.g. Jim sent Monica his dog.

    Sj,m,d\n

    e.g. William did not help or hinder Mike.

    ~ (H1w,m or H2w,m) \n

    e.g. Jennifer promise to help.

    P(j, Hj)\n

    e.g. Jennifer did not promise to help.

    ~P(j,Hj)\n

    e.g. Jennifer promise to not laugh.

    P(j,~Lj)\n

    e.g. Mike claimed he wanted to help.

    C(m, W(m/x, Hm/x))\n\nm: Mike\nx: maybe some other\n

    e.g. John asked Mandy to stop laughing.

    A(j, m, S(m, Lm))\n

    e.g. John and Larry called Molly.

    Cj,m and Cl,m\nC(j and l, m)\n

    e.g. Molly did not call John and Larry.

    ~C(m, j) and ~C(m, l)\n~C(m, j and l)\n~C(m, j) or ~C(m, l)\n

    entailment: (universal instantiation)

    every dog barks \u2192 if something is a dog, then it is a dog.

    Universal quantification

    \\(\\forall\\)x (Dx \u2192 Bx)

    D = (d1, d2, d3,\u2026)

    \\(\\forall\\)x (Dx \u2192 Bx)= (Bd1 and Bd2 and Bd3, \u2026.)

    Existential quantification

    \\(\\exist\\)x (Dx and Bx)

    D = (d1, d2, d3,\u2026)

    \\(\\exist\\)x (Dx and Bx) = (Bd1 or Bd2 or Bd3, \u2026.)

    e.g. Every cat barfed.

    \\forall x (Cx -> Bx)\n

    e.g. The cat barfed.

    Bc\n

    e.g. Bill fed cat.

    \\forall x (Cx -> Fb,x)\n

    e.g. Some dog barked at Fred.

    \\exist x (Dx and Bx,f)\n

    e.g. Fred scolded some dog.

    \\exist x (Dx and Sf,x)\n

    e.g. Fred and Susan avoid some dog.

    \\exist x (Dx and Af,x and As,x)\n\\exits x (Dx and Af,x) and \\exist y (Dy and Af,s)\n

    e.g. No dog barks.

    \\forall x (Dx -> ~Bx)\n~\\exist x (Dx and Bx)\n

    e.g. Bill fed no dog.

    ~\\exist x (Dx and Fb,x)\n\\forall x (Dx -> ~Fb,x)\n

    e.g. No dog barked at Susan or chased Fred.

    ~\\exist x ((Dx and (Bx,s or Cx,f))\n\\forall x ((Dx -> (~Bx,s and ~Cx,f))\n\\forall x ((Dx -> ~(Bx,s or Cx,f))\n

    Scope ambiguity

    e.g. Some boy kissed every girl.

    \\exist x \\forall y (Bx and (Gy -> Kx,y)) = \\exist x(Bx and \\forall y (Gy -> Kx,y))\n\\forall y \\exist x (Gy -> (Bx and Kx,y)) = \\forall y (Gy -> \\exist x (Bx and Kx,y))\n

    Every boy kissed some girl.

    \\forall x (Bx -> \\exist (Gy and Kxy)) <=> \\forall x \\exist y (Gy and Kxy)\n

    Every students did not laugh.

    \\forall x (Sx -> ~Lx) <=> ! \\exist x (Sx and Lx)\n~\\forall x (Sx -> Lx) <=> \\exist (Sx and ~Lx)\n

    Not every student laughs.

    ~\\forall x (Sx -> Lx) <=> \\exist (Sx and ~Lx)\n
    graph TD\n  laughed --> student\n    student --> /every\n    /every --> not\n

    each studnet did not laugh.

    \\forall x (Sx -> ~Lx) \n~\\forall x (Sx -> Lx)\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#polarity-item","title":"Polarity item","text":"

    any: negative polarity item

    John did not pass every exam.

    ~\\forall x (Ex -> Pj,x) <=> \\exist x (Ex and Pj,x)\n\\forall x (Ex -> ~Pj,x)\n

    John did not pass any exam.

    \\forall x (Ex -> ~Pj,x)\n

    e.g.

    Jack saw a rat.

    \\exist x (Rx and Sj,x) \n

    Jack is a rat.

    the quantifier is in the predicate but not the argument. here rat is a constant.

    Rj\n

    Jack knows no genius.

    use not exist to render \u201cno\u201d

    ~\\exist x (Gx and Kj,x)  <=> \\forall x (Gx -> ~Kj,x)\n

    Jack is no genius. <=> Jack is not a genius.

    ~Gj\n

    These problems are difficult.

    Dp\n

    These problems are difficult ones.

    Dp\n

    All the problems are difficult.

    \\forall x (Px -> Dx)\n

    These problems are all the problems.

    Ap\n

    These problems are not all the problems.

    ~Ap\n

    Jack is our plumber.

    Pj\n

    Our plumer is Jack. (has presupposition)

    Pj\n

    Everything counts.

    whether thing includes animate and inanimate.

    \\forall x (Cx)\n\\forall x (Tx -> Cx)\n

    Everybody counts.

    *\\forall x (Cx)\n\\forall x (Px -> Cx)\n

    predicates

    common nouns

    content verbs are the core of syntactic predicates

    adjectives are most always the core of syntactic predicates.

    e.g. Mike\u2019s wife thinks Mikes if lazy.

    predicates inside individual constants are presuppositional

    A thin man was present.

    predicates inside \u2026 .are propositional

    e.g. Every barking is harmless

    has true or false impact on the truth

    \\forall x ((Dx and Bx) -> Hx)\n

    this proposition has to show up in the predicate

    The barking dog is harmless.

    Hd\n

    the presupposition does not show in the predicate

    John avoids every dog he sees.

    \\forall x ((Dx and Sj,x) -> Aj,x)\n

    John said every dog barks.

    intensional

    Sj\nS(j,\\forall x (Dx -> Bx)) \nSj,I  ; I for intensional argument predicate\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#adjunct-predicates","title":"Adjunct predicates","text":"

    Jane probably teased Sam last night

    John arrived drunk.

    Jim burped twice.

    twice: propositional or presuppositional

    Susan did not cheat yesterday.

    Mary stayed because John stayed.

    Mary did not stay because John stayed

    "},{"location":"docs/2-ling/semantics/formal_semantics/#restricted-quantification","title":"restricted quantification","text":"

    Every boy was hungry

    \\forall x: Bx(Hx)\n

    Some boy was hungry.

    \\exist x: Bx(Hx)\n

    Every cat barfed.

    \\forall x: Cx(Bx)\n

    Bill fed every cat.

    \\forall x (Cx, Fb,x)\n\\forall x: Cx(Fb,x)\n

    Some dog barked at Fred.

    \\exist x (Dx, Bx,f)\n\\exist x: Dx(Bx,f)\n

    Fred and Susan avoid some dog.

    \\exist x(Dx and (Af,x and As,x))\n\\exist x: Dx (Af,x and Af,x)\n

    No dog barks.

    ~\\exist x (Dx and Bx) <=> ~\\exist x: Dx (Bx)\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#formal-predicate-semantics","title":"Formal Predicate Semantics","text":"
    graph TD\n  Semantic_Rules --> Model\n  Semantic_Rules --> Valuation_Function\n    Model --> Universe_of_Discourse\n    Model --> Interpretation_Function\n    Universe_of_Discourse --> entities\n
    "},{"location":"docs/2-ling/semantics/formal_semantics/#relation","title":"Relation","text":""},{"location":"docs/2-ling/syntax/","title":"Syntax","text":"

    :material-circle-edit-outline: \u7ea6 23 \u4e2a\u5b57

    \u4e0d\u597d\u8bf4 \u65bd\u5de5\u4e2d

    \u76ee\u5f55

    "},{"location":"docs/2-ling/syntax/conv_gen/","title":"\u8f6c\u6362\u751f\u6210\u53e5\u6cd5","text":"

    :material-circle-edit-outline: \u7ea6 599 \u4e2a\u5b57 :fontawesome-solid-code: 30 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    "},{"location":"docs/2-ling/syntax/conv_gen/#x-bar-theory","title":"X-bar theory","text":"

    \u751f\u6210\u53e5\u6cd5\u548c\u6210\u5206\u53e5\u6cd5\u4e4b\u95f4\u7684\u533a\u522b

    [The big book of poems with the blue cover] is on the table.\n

    \u6210\u5206\u53e5\u6cd5\u505a\u51fa\u6765\uff0csubject\u662f\u4e00\u4e2a\u9ad8\u5ea6\u4e3a1\u7684\u6811

    \u53e5\u5b50\u4e4b\u95f4\u7684\u6210\u5206\u901a\u8fc7\u4e24\u4e24\u7ec4\u5408\u8fd8\u80fd\u505a\u51fa\u65b0\u7684\u9ad8\u5ea6

    one-replacement

    \u7528one-replacement\u63a2\u6d4b\u9650\u5b9a\u8bcd\u4e4b\u95f4\u7684\u8ddd\u79bb\u5173\u7cfb\uff08\u52a8\u8bcd\u7528did so/did too\uff09

    Mika loved the policeman intensively.\nSusan did so half-heartedly.\n*Susan did so the baker.\n
    graph TD\n  NP --> D\n    D --> the\n    NP --> N1\n    N1 --> AdjP\n    AdjP --> big\n    N1 --> N2\n    N2 --> N3\n    N2 --> PP1\n    N3 --> N\n    N --> book\n    N3 --> PP2\n    PP2 --> of_poems\n    PP1 --> with_the_blue_cover\n

    \u52a0\u5165\u4e86bar level\uff0cbook\u4e0eof poems\u6784\u6210\u4e00\u4e2a\u4e2d\u95f4\u6295\u5c04X-bar\uff0c\u6784\u6210\u4e00\u4e2aconstituent\u3002\u4f7f\u5f97\u6bcf\u4e2a\u53e5\u5b50\u90fd\u80fd\u88ab\u753b\u6210\u4e00\u4e2a\u4e8c\u53c9\u6811\u5f62\u5f0f

    \u751f\u6210\u53e5\u6cd5\u5b66\u6d3e\uff1a\u4e0a\u4e16\u7eaa\u4e94\u5341\u5e74\u4ee3\u3002classical theory and standard theory\u30021988\u5e74\u63d0\u51fa\u4e86government and binding theory\u3002lexicon, D-S, S-S, PF, LF

    "},{"location":"docs/2-ling/syntax/conv_gen/#n-bar","title":"N-bar","text":"

    \u539f\u672cNP\u6839\u636e\u4e00\u7cfb\u5217\u89c4\u5219\u4e0d\u662f\u4e8c\u53c9\u6811\uff0c\u6bd4\u5982N\u2192

    N-bar theory\u8ba4\u4e3a\u53ef\u4ee5\u90fd\u53d8\u6210\u4e8c\u53c9\u6811

    \u89c4\u5219\u6bd4\u5982

    NP -> Det N'\nN' -> AP N'\nN' -> N PP\n

    \u7b2c\u4e00\u6761\u79f0\u4e3a\u4e00\u4e2a\u6700\u5927\u6295\u5c04

    "},{"location":"docs/2-ling/syntax/conv_gen/#v-bar","title":"V-bar","text":"
    VP -> V'   // \u9884\u7559\u4e00\u4e2a\u4f4d\u7f6e\u7ed9\u6f5c\u5728\u7684specifier\uff0c\u5373\u4f7f\u6ca1\u6709\nV' -> AdvP V' | V' PP | V' AdvP\nV' -> V(NP)\n
    "},{"location":"docs/2-ling/syntax/conv_gen/#abj-bar","title":"Abj-bar","text":"
    AdjP -> Adj'\nAdj' -> (AdvP) Adj' | Adj' (AdvP)\nAdj' -> Adj(PP)\n
    "},{"location":"docs/2-ling/syntax/conv_gen/#p-bar","title":"P-bar","text":"
    PP -> P'\nP' -> P'(PP) | (AdvP)P'\nP' -> P(NP)\n

    \u4e2d\u5fc3\u8bcdX \u2192 \u4e2d\u95f4\u6295\u5c04X\u2019 \u2192 \u6700\u5927\u6295\u5c04XP\u3002\u4e0d\u80fd\u76f4\u63a5\u5230XP\uff0c\u4e00\u5b9a\u8981\u6709\u4e2d\u95f4\u6295\u5c04

    "},{"location":"docs/2-ling/syntax/conv_gen/#parameter-of-word-orders","title":"Parameter of Word Orders \u7ba1\u7ea6\u8bba\uff0c \u539f\u5219\u4e0e\u53c2\u6570\u7406\u8bba","text":"

    \u6839\u636eX-bar\u7406\u8bba\uff0c\u53ef\u4ee5\u5bf9\u4e00\u4e9b\u8bed\u8a00\u7684\u4e0d\u540c\u8bed\u5e8f\uff08\u5982SVO\uff0cSOV\u7b49\uff09\u7ed9\u51fa\u8bed\u6cd5\u53c2\u6570\u5316\u89e3\u91ca

    specifier\u548ccomplement\u53ef\u4ee5\u51fa\u73b0\u5728\u5176sister\u7684\u4e24\u4fa7\uff0c\u8fd9\u79cd\u6295\u5c04\u7684\u5de6\u53f3\u533a\u522b\u88ab\u79f0\u4e3aparameter setting

    "},{"location":"docs/2-ling/syntax/conv_gen/#_2","title":"\u753b\u6811\u7684","text":""},{"location":"docs/2-ling/syntax/conv_gen/#head-movement","title":"Head Movement \u4e2d\u5fc3\u8bed\u79fb\u4f4d","text":"

    head movement: movement from a head to another head position

    \u53e5\u5b50\u53ef\u4ee5\u53d1\u751fmovement\u7684\u6807\u5fd7

    "},{"location":"docs/2-ling/syntax/conv_gen/#-reading","title":"- \u4e00\u4e2a\u53e5\u6cd5\u7ed3\u6784\u5177\u6709\u4e24\u79cdreading","text":"

    shortest movement

    shortest: let the path of a movement be the set of nodes that dominate the original position of the moved item, and do not dominate the leading site.

    "},{"location":"docs/2-ling/syntax/ud_sud/","title":"\u4f9d\u5b58\u53e5\u6cd5 UD & SUD","text":"

    :material-circle-edit-outline: \u7ea6 381 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    In full spelling, Universal Dependency gammar and Surface Syntax Universal Dependency grammar.

    "},{"location":"docs/2-ling/syntax/ud_sud/#tools","title":"Tools","text":"

    AllenNLP Demo CoreNLP Tool

    "},{"location":"docs/2-ling/syntax/ud_sud/#concepts","title":"Concepts","text":""},{"location":"docs/2-ling/syntax/ud_sud/#ud","title":"UD","text":"

    Dependency grammar\u00a0(DG) is an approach to the study of the syntax and grammar of natural languages that is quite distinct from\u00a0phrase structure grammar\u00a0(PSG), which is also known as\u00a0constituency grammar. The modern history of DG begins with\u00a0Lucien Tesni\u00e8re's major oeuvre (1959), whereas the modern history of PSG begins arguably with\u00a0Noam Chomsky's first prominent work (1957).

    DG views linguistic structures in terms of a\u00a0one-to-one mapping\u00a0of atomic linguistic units to the nodes in structure, whereas PSG assumes a\u00a0one-to-one-or-more mapping. The distinction is clearly visible when one compares the tree structures. The next trees are taken from the\u00a0Wikipedia article on DG:

    "},{"location":"docs/2-ling/syntax/ud_sud/#sud","title":"SUD","text":"

    [Surface Syntactic Universal Dependencies (SUD) | SUD](https://surfacesyntacticud.github.io/ SUD is an annotation scheme for syntactic dependency treebanks, and has a nearly perfect degree of two-way convertibility with the Universal Dependencies scheme (UD). Contrary to UD, it is based on syntactic criteria (favoring functional heads) and the relations are defined on distributional and functional bases.

    "},{"location":"docs/2-ling/syntax/ud_sud/#general-principles-of-sud","title":"General principles of SUD","text":""},{"location":"docs/2-ling/syntax/ud_sud/#specific-sud-relations","title":"Specific SUD relations","text":"

    SUD has 4 specific syntactic relations and a few extended relations: - subj - udep - comp - comp:aux - comp:cleft - comp:obj - comp:obl - comp:pred - mod

    "},{"location":"docs/2-ling/syntax/uni_gram/","title":"\u666e\u904d\u8bed\u6cd5 Universal Grammar","text":"

    :material-circle-edit-outline: \u7ea6 260 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/2-ling/syntax/uni_gram/#introduction","title":"Introduction","text":"

    Syntax\u7684\u610f\u4e49\u5728\u4e8e\u627e\u5230\u4e00\u79cdgrammar\uff0c\u80fd\u591f\u751f\u6210\u67d0\u79cd\u8bed\u8a00\u4e2d\u7684\u6240\u6709\u53e5\u5b50\u3002

    Grammar\u662f\u57fa\u4e8e\u89c4\u5219\u7684\uff0c\u4e0d\u80fd\u7528high order of statistical approximation to English\u6765\u66ff\u4ee3\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#basic-linguistics","title":"Basic Linguistics","text":"

    DFA & Regular language

    \u8c13\u8bcd\u903b\u8f91\u3002\u4f46\u6211\u4eec\u4e0d\u5173\u5fc3\u5176\u4e2d\u7684\u8bed\u4e49\uff0c\u53ea\u9700\u5173\u5fc3CFG\u7684\u5f62\u5f0f\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#phrase-structure-limitation","title":"Phrase Structure & Limitation","text":"

    \u81ea\u7136\u8bed\u8a00\u7684CFG\uff08\u4ee5\u82f1\u8bed\u4e3a\u4f8b\uff09\u6784\u6210\u8bed\u6cd5\u7684\u57fa\u7840\u90e8\u5206\u3002

    \u4f46\u8fd9\u6837\u63cf\u8ff0\u81ea\u7136\u8bed\u8a00\u7684\u5de5\u5177\u8fd8\u662f\u4e0d\u80fd\u751f\u6210\u6240\u6709\u5408\u7406\u7684\u53e5\u5b50\uff0c\u6545\u5f15\u5165a more powerful model combining phrase structure and grammatical transformation\uff0c\u5f97\u5230\u8f6c\u6362-\u751f\u6210\u6587\u6cd5\u3002

    "},{"location":"docs/2-ling/syntax/uni_gram/#on-the-goals-of-linguistic-theory","title":"On the Goals of Linguistic Theory","text":"

    \u4ece\u4e00\u822c\u8bed\u6cd5\u4e2d\u5f52\u7eb3\u51faUG\u7406\u8bba\uff0c\u5bf9UG\u7684\u671f\u671b\u7531\u5f3a\u81f3\u5f31\u4e3a\uff1a

    "},{"location":"docs/2-ling/syntax/uni_gram/#the-explanatory-power-of-linguistic-theory","title":"The Explanatory Power of Linguistic Theory","text":"

    \u5e94\u8be5\u7814\u7a76competence\uff0c\u800c\u975eperformance

    "},{"location":"docs/3-dl/","title":"Deep Learning","text":"

    :material-circle-edit-outline: \u7ea6 26 \u4e2a\u5b57

    "},{"location":"docs/3-dl/#contents","title":"Contents","text":""},{"location":"docs/3-dl/#todo","title":"TODO","text":""},{"location":"docs/3-dl/#references","title":"References","text":"

    AI\u5185\u5bb9\u751f\u6210\uff08ai-gc\uff09

    "},{"location":"docs/3-dl/basics/","title":"Index","text":"

    :material-circle-edit-outline: \u7ea6 0 \u4e2a\u5b57

    "},{"location":"docs/3-dl/basics/bpe/","title":"Byte pair encoding (BPE)","text":"

    :material-circle-edit-outline: \u7ea6 144 \u4e2a\u5b57

    The original version of this algorithem focuses on compression. It replaces the highest-frequency pair of bytes with a new byte that was not contained in the initial dataset. A lookup table of the replacement is required to rebuild the initial dataset. The modified version builds tokens that match varying amount of source text from single characters to whole words.

    Example

    Suppose the sentence to be 

    aaabbaaabac\n

    Since the byte pair (each alphabet as a byte) 'aa' occurs the most often, it is replaced by a byte 'Z' (first match).

    ZabbZabac\n

    Then 'ab' with 'Y'

    ZYbZYac\n

    Then 'ZY' with X

    XbXac\n

    Then this sequence can not be further compressed since there are no byte pair appearing more than once.

    This algorithm is effective for tokenization because it has low computational overhead and remains consistent and reliable.

    References

    Wikipedia - Byte Pair Encoding

    "},{"location":"docs/3-dl/basics/elmo/","title":"ELMo","text":"

    :material-circle-edit-outline: \u7ea6 207 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    ELMo (embeddings from language model) is a word embedding method for representing a sequence of words as a corresponding sequence of vectors. Its essence is a bidirectional LSTM which takes character-level as inputs and produces word-level embeddings.

    According to its original paper (?), it requires training on a corpus of about 30 million sentences and a billion words.

    Contributions:

    e.g., for sentence 

    She went to the bank to withdraw money.\n

    References

    Wikipedia ELMo

    "},{"location":"docs/3-dl/efficient-train/","title":"Efficient Training","text":"

    :material-circle-edit-outline: \u7ea6 7 \u4e2a\u5b57

    "},{"location":"docs/3-dl/efficient-train/#intro","title":"Intro","text":""},{"location":"docs/3-dl/efficient-train/#contents","title":"Contents","text":""},{"location":"docs/3-dl/efficient-train/hardware/","title":"Hardware","text":"

    :material-circle-edit-outline: \u7ea6 1101 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/3-dl/efficient-train/hardware/#gpu","title":"GPU","text":"

    A graphic processing unit (GPU) is an electronic circuit designed for accelerating computer graphics. It is now widely adopted for non-graphic calculations such as the training of neural networks.

    GPU Parameters that are most cared about

    In a table:

    GPU GPU Memory Memory Bandwidth NVLINK CUDA Cores Turning Tensor cores RT cores T4 16GB 320GB/s No 2,560 320 40 A40 48GB 696GB/s Yes 10,752 336 84 RTX 6000 48GB 960GB/s No 18,176 568 142"},{"location":"docs/3-dl/efficient-train/hardware/#a-taxonomy-of-parallelism","title":"A Taxonomy of Parallelism","text":""},{"location":"docs/3-dl/efficient-train/hardware/#data-parallelism","title":"Data Parallelism","text":"

    Data Parallelism replicates the model across multiple GPUs, usually with two specific techniques: (1) fully shared data parallelism (FSDP), and (2) distributed data parallelism (DDP).

    We denote the training dataset as \\(D\\), the shared model parameters as \\(W\\), the model's operation on the dataset as \\(f(D_i, W)\\), the \\(i\\)th processor as \\(p_i\\), the number of processors as \\(P\\), the \\(i\\)th machine which may be mapped to multiple processors as \\(m_i\\), and the number of machines as \\(M\\). In FSDP, the dataset \\(D\\), ignoring its original division of batches, is further divided into \\(P\\) smaller batches \\(D = {D_1, D_2, ..., D_P}\\). Each processor \\(p_i\\) performs a \\(f(D_i, W)\\) on its small batch. Meanwhile, DDP extends the data parallelism technique across multiple machines. The dataset \\(D\\) is first divided into \\(M\\) subsets \\(D = {D_1, D_2, ..., D_M}\\) for each machine, and each subset on \\(m_i\\) is further divided into \\(P_i\\) subsets according to the number of processors on each machine. After each processor performs the processing \\(f(D_{i,j}, W_k)\\), synchronization will be taken across all machines to aggregate and update the model weights \\(W_k \\leftarrow Aggregate(W_1, W_2, ..., W_M)\\).

    While the computation workload is efficiently distributed across GPUs, inter-GPU communication is required to keep the model replicas consistent between training steps.

    "},{"location":"docs/3-dl/efficient-train/hardware/#model-parallelism","title":"Model Parallelism","text":"

    Model parallelism is a distributed model deployment method that partitions the model parameters across GPUs to reduce the need for per-GPU memory. Common techniques of model parallelism include (1) tensor parallelism, (2) pipeline parallelism, and (3) expert parallelism.

    We denote the input data tensor as \\(W\\), the model parameters as \\(W\\), the function representing the model's operations as \\(f(X, W)\\), and the \\(i\\)th processor as \\(p_i\\), the number of processors as \\(P\\).

    Tensor Parallelism distributes the parameter tensor of an individual layer across GPUs. The model weights are divided along specific dimensions into \\(W = {W_1, W_2, ..., W_P}\\), and thus each processor \\(p_i\\) processes part of the model weights \\(f(X, W_i)\\).

    Pipeline Parallelism involves partitioning the computation graph of a model into several stages and assigning each stage to a different processor or machine, making it an analogy to the CPU's pipelining technique. The input tensor \\(X\\) sequentially passes through each processor in each time step until the processing steps finish. This allows for overlapping execution of different stages, increasing the throughput.

    Expert Parallelism, also known as Mixture of Experts (MoE), involves dynamically selecting a subset of model parameters, to reach the original performance using the entire model. Additionally, MoE models require a gating network \\(g(X)\\) to select the expert to output, which selects a subset of networks from the total \\(E\\) sub-networks, as $ \\epsilon =g(X), \\epsilon \\subseteq E $. Only the selected networks will be involved in the generation of the output \\(\\sum_{k \\in \\epsilon} f(X, W_k)\\).

    "},{"location":"docs/3-dl/efficient-train/hardware/#activition-partitioning","title":"Activition Partitioning","text":"

    In large language model training, a large memory space is needed to store the input activation of the network layers. The activation partitioning techniques, which involves efficiently distributing the activations to ensure GPU usage, is another crucial technique for efficient training. Commonly used activation partitioning techniques involve (1) sequence parallelism and (2) context parallelism. We denote the input sequence as \\(X\\), the context of this training, including the batches and environments, as \\(C\\), the processing function as \\(f(X, C, W)\\), and \\(P\\) the number of processors.

    Sequence Parallelism suggests that partitions are made by distributing computing load and activation memory across multiple GPUs along the sequence dimension of transformer layers. The input sequence \\(X\\) is divided into sub-sequences \\(X = [X_1, X_2, ..., X_P]\\). Each sub-sequence is sent into a processor with inner tensor forwarding techniques from the previous sub-sequence, denoted as \\(f(X_i, C, W_{i-1})\\).

    Context Parallelism distributes different contexts, usually including batches and environments, across multiple processors. It is useful in multi-task learning and reinforcement learning scenarios. The context \\(C\\) is divided among processors \\(C = [C_1, C_2, ..., C_P]\\), and each processor processes the context with the entire input sequence, denoted as \\(f(X, C_i, W_i)\\).

    "},{"location":"docs/3-dl/efficient-train/hardware/#multi-gpu-training","title":"Multi-GPU Training","text":"

    TODO

    Reference: \ud83e\udd17 Efficient Training on Multiple GPUs

    "},{"location":"docs/3-dl/efficient-train/parameter/","title":"Parameter","text":"

    :material-circle-edit-outline: \u7ea6 664 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f

    "},{"location":"docs/3-dl/efficient-train/parameter/#parameter-level","title":"Parameter-level","text":"

    Huggingface's efficient training guide discusses a number of parameters and their effect on training efficiency.

    Relevant table:

    Method/tool Improves training speed? Optimizes memory utilization? Batch size choice True True Gradient accumulation False True Gradient checkpointing False True Mixed precision training True Maybe Torch empty cache steps False True Optimizer choice True True Data preloading True False DeepSpeed Zero False True torch.compile True False Parameter-efficient Tuning (PEFT) False True"},{"location":"docs/3-dl/formal-language/","title":"Introduction to Formal Languages","text":"

    :material-circle-edit-outline: \u7ea6 4 \u4e2a\u5b57

    "},{"location":"docs/3-dl/formal-language/lecture/","title":"Lectures","text":"

    :material-circle-edit-outline: \u7ea6 411 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/3-dl/formal-language/lecture/#language-model-and-formal-language","title":"Language Model and Formal Language","text":"

    ACL tutorial 4

    big promises

    neural language models - expressiblity - formal language

    useful tools - RNN: sequntial automata - Transformer: circuits

    Definition

    a language model p is a distribution on *\\Sigma.

    Two language models are equal if p(y) = q(y) for all y on *\\Sigma.

    Any language model can be written as an autogressive one.

    tightness: for arbituary language model, the sum of all p(y) < 1 can happen. If the sum of all p(y) = 1, it is tight.

    A minimum non-tight example: To set the probablity of EOS as 0, thus the generation might never stop.

    special features of automaton: parity, hierachy detection

    simplist RNN: Elman RNN

    RNNs can be both as language models / recognizors (to classify grammatical or not)

    RNNs work like language model (TODO: photo)

    infinite state automata - with unbounded precision and computation time

    a turing machine is equivalent to a two-stack pushdown automaton. (tape = two-stacks)

    Theorem: an infinite-precision RNNs with unbounded computation time are Turing complete.

    implies: - TODO: photo - we need the hidden states to encode the stacks

    stack = neuron

    drawbacks: - numbers are in finite precision - RNNs stop within finite time

    "},{"location":"docs/3-dl/formal-language/lecture/#improvement-theoretical-model-rnns-with-bounded-computation-time-and-finite-precision","title":"improvement theoretical model: RNNS with bounded computation time and finite precision","text":"

    Theorem: Finite-precision real-time RNNs are equivalent to FSAs (without stacks, taking the training and inference procedure apart. )

    clear: - any finite-precision RNN will define a finite number of states - it can thus be represented by a FSA - an upper bound RNNs can do at most what finite-state automata can

    => Elman RNNs can simulate deterministic FSAs (any non-deterministic FSA can be => deterministic ones)

    main differences: - automaton: tabular rules - RNNs: matrix multiplications

    Any simple family of automata can efficient simulation of RNNs?

    TODO: photo

    Some FSA with |Q| states can be compressed into an RNN with O(log|Q|) hidden states.

    Takeaways:

    an RNN can end up in any rung of the NC hierarchy depending on - whether allowing unbounded processing time - whether allowing unbounded precision

    QAs:

    "},{"location":"docs/3-dl/formal-language/lecture/#how-to-turn-an-rnn-into-a-classifier","title":"How to turn an RNN into a classifier","text":"

    the missing bit:

    probablistic finite-state automata also compute probalisties

    Beyond Binary States: LSTMs and counting

    Counter machine:

    TODO: photo, position on NC hierarchy

    no model currently reach the computation ability of Turing machine. Some advanced models (e.g. ChatGPT) happen to recognize some programs.

    LSTM as a counter machine, the memory cell works as the counter. set (TODO: some parameters) as 1 and the updating function of mem cells are as the counter.

    "},{"location":"docs/3-dl/formal-language/lecture/#transformers-and-formal-language-theory-part-on-encoder","title":"Transformers and formal language theory, part on encoder","text":"

    bolean circuits, definition:

    runtime without parallelism

    definition (depth): longest path from input to output runtime with parallelism (?)

    need sth dependent on input time

    formal models: Boolean circuits

    (what is ACC here)

    formal models: first order logic (how did this appear)

    TODO: photo, NC hierarchy interact with language classes

    does circuits recognize parity?

    decisions to make: attention, softmax

    uniformity:

    dependence on - number of parameters

    unique hard attention:

    linear temporal logic

    TODO: photo on example of L=\\Sigma*ab\\Sigma*

    "},{"location":"docs/3-dl/formal-language/lecture/#adding-sequentiality-to-transformers-chain-of-thought-part-of-decoder","title":"adding sequentiality to Transformers, chain-of-thought, part of decoder","text":"

    so far, only deterministic automata

    non-deterministic

    "},{"location":"docs/3-dl/formal-language/lecture/#takeaways","title":"takeaways","text":"

    QAs - the Turing machines can move head left-to-right and right-to-left. if taking that into account, we might

    Reference

    "},{"location":"docs/3-dl/survey/","title":"Misc Survey","text":"

    :material-circle-edit-outline: \u7ea6 32 \u4e2a\u5b57

    If I have written about some topics that I don't read anymore, they will be thrown into this section.

    "},{"location":"docs/3-dl/survey/#contents","title":"Contents","text":""},{"location":"docs/3-dl/survey/explainable-nlp/","title":"Explainable NLP Survey","text":"

    :material-circle-edit-outline: \u7ea6 1084 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    TODO

    "},{"location":"docs/3-dl/survey/explainable-nlp/#survey","title":"Survey","text":""},{"location":"docs/3-dl/survey/explainable-nlp/#a-survey-of-the-state-of-explainable-ai-for-natural-language-processing","title":"A Survey of the State of Explainable AI for Natural Language Processing","text":"

    This survey thoroughly explains the state of explainable NLP. The Introduction discusses two distinguishing criteria for explanability models (1) whether the explanation is for each prediction individually or the model\u2019s prediction process as a whole, and (2) determining whether generating the explanation requires post-processing or not. In Categorization of Explanations, this paper categorizes the explanation models into local (provides information or justification for the model's prediction on a specific input) vs. global (provides similar justification by revealing how the model's predictive process works, independently of any particular input), and self-explaining (also directly interpretable, generates the explanation at the same time as the prediction, e.g. decision trees, rule-based models, and feature saliency models like attention models) vs. post-hoc (an additional operation is performed after the predictions are made). This section also states that the different categories of models can overlap. In section Aspects of Explanations, this paper introduces three types of explanation techniques: (1) explainability techniques (feature importance, surrogate model, example-driven, provenance-based, declarative induction), (2) operations to enable explainability (first-derivation saliency, layer-wise relevance propagation, and input perturbations, attention, LSTM gating signals, explainability-aware architecture design) and (3) visualization techniques (saliency, raw declarative representations, natural language explanation). The section Evaluation introduces several evaluating metrices.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#opinion-papers","title":"Opinion Papers","text":""},{"location":"docs/3-dl/survey/explainable-nlp/#climbing-towards-nlu-on-meaning-form-and-understanding-in-the-age-of-data-2020","title":"Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (2020)","text":"

    This paper argues that the modern NLP models trained on form has no abilities in understanding natural languages based on both the science and philosophy theories. It is structured as follows. In section Large LMs: Hype and analysis, this paper samples example pieces from news and academic literature that exaggerate the understanding abilities in using words including \"understand\"\"comprehension\"\"recall factual knowledge\", and argues that the current LMs have the ability no other than learning the surface linguistic forms of language rather than understanding them. In section What is meaning?, this paper clarifies the meaning of language as the communicative intent that a parole intends to express, and distinguishes the concept \"meaning\" and \"truth\" as the truth is the meaning that is \"grounded\" to the real world. In section The octopus test, this paper detailedly tells a thought experiment of a super intelligent octopus who can mimic the human response by never receiving the knowledge of the grounded real world of the language meaning, by which this paper argues that it might be that how the language receiver decodes the communicative intends affects the conventional meaning of language. In section More constrained thought experiments, two more thought experiments are provided, training the JAVA and training the English LMs without providing the executing methods the communicative intends, and the paper argues that such tasks are impossible. In section Human language acquisition, this paper supports its idea by providing the example of human children's acquiring knowledge is not only grounded on the world image, but also in the interaction with other people. In section Distributional semantics, this paper argues that in NLP, two methods based on the instincts above are training distributional models on corpora augmented with perceptual data, and looking to interaction data (according to Wittgenstein's \"meaning in use\").

    "},{"location":"docs/3-dl/survey/explainable-nlp/#information-theory-based-compositional-distributional-semantics-2021","title":"Information Theory-based Compositional Distributional Semantics (2021)","text":"

    According to the abstract, the contribution of this paper can be concluded as proposing the notion of Information Theory-based Compositional Distributional Semantics (ICDS): (i) We first establish formal properties for embedding, composition, and similarity functions based on Shannon\u2019s Information Theory; (ii) we analyze the existing approaches under this prism, checking whether or not they comply with the established desirable properties; (iii) we propose two parameterizable composition and similarity functions that generalize traditional approaches while fulfilling the formal properties; and finally (iv) we perform an empirical study on several textual similarity datasets that include sentences with a high and low lexical overlap, and on the similarity between words and their description. In section Introduction, the author introduces Frege's concepts of compositionality and contextuality, which respectively refers to that \"the meaning of the whole is a function of the meaning of its parts and the syntactic way in which they are combined\", and that \"the meaning of words and utterances is determined by their context\". This section also introduces the main concern of lacking systematicity by the linguists to the NLP, where systematicity is defined as \"A system is said to exhibit systematicity if, whenever it can process a sentence, it can process systematic variants, where systematic variation is understood in terms of permuting constituents or (more strongly) substituting constituents of the same grammatical category.\" Thus, this section introduces that this paper aims to propose a novel system called Information Theory-based Compositional Distributional Semantics (ICDS). In section Related Work, the author introduces a set of properties in selective proper text representation paradigms which includes \"systematicity\", \"usage context\", \"continuity\", and \"information measurbility\", and introduces a series of previous work under this standard. In section Theoretical Framework, this paper first establishes a geometric interpretation of ICDS, that \"The direction of an embedding represents the pragmatic meaning, and the vector norm of embedding represents how much information the literal utterance provides about its meaning in the pragmatic context\", and then proposes the concept of ICDS as \"there are minimal linguistic units whose semantics are determined by their use and whose amount of information is determined by their specificity. On the other hand, the systematicity of language can be captured by compositional mechanisms while preserving the amount of information of the composite utterance\". Section Formal Definition and Properties formally defines the concepts involved in ICDS, where (\\(\\pi\\),\\(\\delta\\), \\(\\bigodot\\)) stand for \"embedding\", \"semantic similarity\", and \"composition function\" respectively. This section points out the embedding function properties (information measurability and angular isometry), composition function properties (composition neutral element, composition norm monotonicity, and sensitivity to stricture), and similarity function properties (angular distance simialrity monotonicity, orthogonal embedding similarity monotonicity, and equidistant embedding simialrity monotonicity). In section Function Analysis and Generalization, this research evaluates several current embedding vector with the proposed framework, while in section Experiment, the semantic representation abilities of several prevailing LLMs including BERT and GPT are evaluated.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#contrastive-explanations-for-model-interpretability-2021","title":"Contrastive Explanations for Model Interpretability (2021)","text":"

    This paper proposes a data augmentation method to generate counterexample on the bases of NLI datasets, and proves that by training on patterns \"why A rather than B\" with contrastive learning methods, the model performs better than the previous NLI baselines.

    "},{"location":"docs/3-dl/survey/explainable-nlp/#using-counterfactual-contrast-to-improve-compositional-generalization-for-multi-step-quantitative-reasoning-2023","title":"Using counterfactual contrast to improve compositional generalization for multi-step quantitative reasoning (2023)","text":""},{"location":"docs/3-dl/survey/llama3_405b/","title":"Llama-3.1-405B \u6280\u672f\u62a5\u544a","text":"

    :material-circle-edit-outline: \u7ea6 3436 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 11 \u5206\u949f

    "},{"location":"docs/3-dl/survey/llama3_405b/#_1","title":"\u7b80\u4ecb","text":"

    \u8fd9\u7bc7\u6280\u672f\u62a5\u544a\u662f MetaAI \u5728 2024 \u5e74 7 \u6708 23 \u65e5\u968f 405B \u6a21\u578b\u53d1\u5e03\u7684\u3002\u5148\u524d Llama 3 \u7cfb\u5217\u5df2\u7ecf\u53d1\u5e03\u8fc7 8B \u548c 70B \u4e24\u4e2a\u5927\u5c0f\u7684\u6a21\u578b\uff0c\u672c\u6b21\u53d1\u5e03\u7684\u6a21\u578b\u5728\u89c4\u6a21\u4e0a\u589e\u91cf\u975e\u5e38\u5927\u3002\u5c3d\u7ba1\u89c4\u6a21\u7684\u63d0\u5347\u4f7f\u5176\u6210\u4e3a\u6700\u5f3a\u7684\u5f00\u6e90\u5927\u8bed\u8a00\u5bf9\u8bdd\u6a21\u578b\uff08\u5728\u672c\u6587\u5199\u6210\u65f6\uff0c2024 \u5e74 8 \u6708 1 \u65e5\uff0c\u6839\u636e\u516c\u8ba4\u6bd4\u8f83\u53ef\u4fe1\u7684\u8bc4\u4ef7\u6307\u6807 Chatbot Arena\uff0c\u622a\u56fe\u5982\u4e0b\uff09\uff0c\u4f46\u672c\u6587\u5728 benchmark \u4e0a\u5c55\u73b0\u51fa\u6765\u7684\u6027\u80fd\u6570\u503c\uff0c\u76f8\u6bd4 70B \u63d0\u5347\u4e0d\u5927\uff0c\u666e\u904d\u5728 1-3 \u4e2a\u70b9\u3002\u4e14\u8003\u8651\u5230\u6a21\u578b\u5360\u7528\u7684 GPU \u6210\u672c\uff0c\u5bf9\u4e8e\u666e\u901a\u4eba\u65e5\u5e38\u7528\u9014\uff0c405B \u53ef\u80fd\u6027\u4ef7\u6bd4\u4e0d\u5982 70B \u9ad8\u3002

    \u62a5\u544a\u7684\u539f\u6587\u89c1\u6587\u672b ArXiv \u94fe\u63a5\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_2","title":"\u6587\u7ae0\u7ed3\u6784","text":"

    Llama-3.1-405B \u6709\u6587\u5b57\u3001\u89c6\u9891/\u56fe\u50cf\u548c\u8bed\u97f3\u7b49\u591a\u4e2a\u6a21\u6001\u7684\u80fd\u529b\u3002\u672c\u6587\u7684\u67b6\u6784\u5206\u4e3a\u591a\u4e2a\u7ae0\u8282\uff0c\u5148\u8bb2\u6587\u5b57\u80fd\u529b\u7684\u9884\u8bad\u7ec3\uff08pre-training\uff09\u3001\u5fae\u8c03\uff08post-training\uff09\u3001\u5b9a\u6027\u80fd\u529b\u3001\u5b9a\u91cf\u80fd\u529b\u3001\u5c40\u9650\u6027\u7b49\uff0c\u518d\u8bb2\u89c6\u9891/\u56fe\u50cf\u548c\u8bed\u97f3\u7684\u8bad\u7ec3\u8fc7\u7a0b\u548c\u6027\u80fd\u6570\u503c\u3002

    \u6280\u672f\u62a5\u544a\u539f\u6587\u7684\u7ed3\u6784\u5982\u4e0b\uff1a

    "},{"location":"docs/3-dl/survey/llama3_405b/#n","title":"n \u53e5\u8bdd\u4eae\u70b9","text":""},{"location":"docs/3-dl/survey/llama3_405b/#_3","title":"\u6027\u80fd","text":""},{"location":"docs/3-dl/survey/llama3_405b/#benchmarks","title":"Benchmarks \u9884\u89c8","text":"

    \u5728\u591a\u4e2a benchmark \u4e0a\u6d4b\u8bd5 Llama-3.1-405B \u7684\u6027\u80fd\u3002\u6b64\u5904\u60f3\u5bf9\u672c\u6587\u7528\u5230\u7684 benchmark \u8fdb\u884c\u4e00\u70b9\u6982\u8ff0\u3002

    pre-train \u9636\u6bb5\u7ed3\u675f\u540e\uff0c\u7528\u4e8e\u6d4b\u8bd5\u7684 benchmark \u6709\uff1a

    post-train \u9636\u6bb5\u7ed3\u675f\u65f6\uff0c\u6d4b\u8bd5\u7528\u7684 benchmark \u5982\u4e0b\uff1a

    "},{"location":"docs/3-dl/survey/llama3_405b/#_4","title":"\u6027\u80fd\u6570\u503c","text":"

    \u5728\u8fd9\u4e9b benchmark \u4e0a\u6d4b\u8bd5\u65f6\uff0c\u7531\u4e8e\u5355\u6b21\u7ed3\u679c\u4e0d\u7a33\u5b9a\uff08\u5148\u524d\u6211\u4eec\u666e\u904d\u7684\u505a\u6cd5\u5e38\u5e38\u662f\u591a\u6b21\u7ed3\u679c\u6c42\u5e73\u5747\u503c\u7b49\uff09\uff0c\u672c\u6280\u672f\u62a5\u544a\u91c7\u7528 Maddan et al.(2024) \u63d0\u51fa\u7684 95% confidence interval (CIs) \u65b9\u6cd5\uff0c\u901a\u8fc7\u8ba1\u7b97\u7f6e\u4fe1\u533a\u95f4\u6765\u4f30\u8ba1\u65b9\u5dee\u3002\u8fd9\u4e2a\u65b9\u6cd5\u5047\u8bbe\u6d4b\u8bd5\u5f97\u5230\u7684\u6570\u503c\u670d\u4ece\u6b63\u6001\u5206\u5e03\uff0c\u5982\u679c\u5355\u6b21\u6d4b\u8bd5\u5f97\u5230\u7684\u6570\u503c\u4e3a S\uff0c\u6570\u636e\u96c6\u5927\u5c0f\u4e3a N\uff0c\u90a3\u4e48\u7f6e\u4fe1\u533a\u95f4\u4e3a

    \\[ CI(S) = 1.96 \\times \\sqrt{\\frac{S \\times (1 - S)}{N}} \\]

    \u7531\u7f6e\u4fe1\u533a\u95f4\u5bbd\u5ea6\u9664\u4ee5\u4e34\u754c\u503c 1.96 \u53ef\u4ee5\u5f97\u5230\u6807\u51c6\u5dee -> \u65b9\u5dee\u3002

    post-train \u5b8c\u6210\u540e\uff0c\u7ed3\u679c\u7684\u603b\u8868\u5982\u4e0b

    \u53ef\u4ee5\u770b\u51fa\u5176\u5b9e Llama-3.1-405B \u5728 70B \u4e0a\u6709\u63d0\u5347\uff0c\u4f46\u76f8\u6bd4\u53c2\u6570\u91cf\u7684\u63d0\u5347\uff0c\u6027\u80fd\u63d0\u5347\u5e76\u4e0d\u662f\u5f88\u5927\uff0c\u5f88\u591a benchmark \u4e0a\u90fd\u5728 2-3 \u4e2a\u70b9\u3002\u8003\u8651\u5230\u524d\u9762\u63d0\u5230\u53ef\u80fd 405B \u53ef\u80fd\u8bad\u7ec3\u4e86 MoE \u548c dense Transformer \u4e24\u4e2a\u6a21\u578b\u4f46\u662f\u540e\u8005\u6ca1\u8bad\u6210\u529f\uff0c\u4e0d\u77e5\u9053\u53d1\u5e03\u7248 405B \u6027\u80fd\u6bd4\u9884\u671f\u4f4e\u662f\u4e0d\u662f\u4e5f\u662f\u8fd9\u4e2a\u539f\u56e0\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_5","title":"\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/llama3_405b/#pre-train","title":"Pre-train \u9884\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/llama3_405b/#_6","title":"\u6574\u4f53\u95ee\u9898","text":"

    \u9884\u8bad\u7ec3\u7275\u626f\u5230\u7684\u95ee\u9898\u6709\u56db\u5757\uff1a

    1. \u600e\u4e48\u628a\u6bd4\u8f83\u5927\u7684\u6570\u636e\u96c6\u5f04\u51fa\u6765
    2. \u600e\u4e48\u628a scaling law \u4f53\u73b0\u51fa\u6765\uff0c\u4f1a\u51b3\u5b9a\u7528\u591a\u5c11\u6570\u636e\u548c\u6a21\u578b\u53c2\u6570\u91cf\u662f\u591a\u5c11
    3. \u600e\u4e48\u6709\u6548\u5728 pre-train \u9636\u6bb5\u8bad\u7ec3\u8fd9\u4e48\u591a\u53c2\u6570
    4. \u600e\u4e48\u505a pre-train

    \u9884\u8bad\u7ec3\u5927\u7ea6\u7528\u4e86\u534a\u5e74\uff0c\u8c03\u53c2\u662f\u5e74\u521d\u5f00\u59cb\u7684\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_7","title":"\u6570\u636e\u6e05\u6d17","text":"

    \u7528\u5230\u7684\u6570\u636e\u662f\u5728\u4e92\u8054\u7f51\u4e0a common crawl \u4e0b\u6765\u7684\u622a\u81f3 2023 \u5e74\u7684\u6570\u636e\uff0c\u4e4b\u540e\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3002\u6570\u636e\u7684\u9009\u7528\u4e00\u822c\u5c5e\u4e8e\u516c\u53f8\u79d8\u5bc6\uff0c\u4e0d\u80fd\u8bb2\u592a\u6e05\u695a\u3002\u6e05\u6d17\u7684\u6b65\u9aa4\u867d\u7136\u4e5f\u6ca1\u6709\u8bb2\uff0c\u4e0d\u8fc7\u5927\u81f4\u9075\u5faa\uff081\uff09\u627e\u4e00\u6279\u6570\u636e\u89c2\u5bdf\u5927\u591a\u662f\u5982\u4f55\u810f\u7684 -> \uff082\uff09\u5199\u811a\u672c\u6d17\u6389\u8fd9\u79cd\u7279\u70b9 -> \uff083\uff09\u8fd4\u56de\uff081\uff09\u5faa\u73af\u3002\u6709\u660e\u786e\u8bb2\u7684\u6570\u636e\u6e05\u6d17\u539f\u5219/\u7c7b\u522b\u6709\u4ee5\u4e0b\u51e0\u6761\uff1a

    1. \u6d17\u6389 personally identifiable information (PII) \u5373\u4e00\u4e9b\u4e2a\u4eba\u59d3\u540d\u3001\u90ae\u7bb1\u3001url\uff0c\u548c\u6210\u4eba\u5185\u5bb9\uff1b\u4f46\u674e\u6c90\u8868\u793a\u8fd9\u4e24\u79cd\u4e1c\u897f\u4e5f\u4e0d\u4f1a\u6d17\u592a\u5e72\u51c0\uff0c\u524d\u8005\u6d17\u592a\u5e72\u51c0\u4e86\u53ef\u80fd\u4f1a\u4f7f\u8bad\u7ec3\u6587\u6863\u672c\u8eab\u7684\u610f\u601d\u6709\u53d8\u5316\uff0c\u540e\u8005\u592a\u5e72\u51c0\u4e86\u53ef\u80fd\u6a21\u578b\u5728\u4e00\u4e9b\u6253\u64e6\u8fb9\u7403\u5e94\u7528\u4e0a\u6548\u679c\u4e0d\u592a\u597d\uff0c\u6240\u4ee5\u505a\u6cd5\u53ef\u80fd\u662f\u5bf9\u6587\u6863\u9274\u5b9a\u4e00\u4e2a\u767e\u5206\u6bd4\uff0c\u5982\u679c\u5176\u4e2d\u9700\u8981\u6d17\u6389\u7684\u5185\u5bb9\u5360\u6bd4\u592a\u591a\uff0c\u5219\u4e0d\u8981\u4e86\u3002

    2. \u5728\u7ed3\u6784\u5316\u6587\u6863\u4e2d\u63d0\u53d6\u6587\u672c\uff0c\u6bd4\u5982\u53bb\u6389 html \u548c markdown \u7684\u6807\u7b7e\uff0c\u53ea\u4fdd\u7559\u6587\u672c\u3002

    3. \u5206\u522b\u505a\u4e86 url\u3001\u6587\u6863\u548c\u884c\u7ea7\u522b\u7684\u53bb\u91cd\u3002\u5728 url \u7ea7\u522b\uff0c\u4fdd\u7559\u4e86\u6240\u6709\u9875\u9762\u6700\u65b0\u7684\u7248\u672c\uff1b\u5728\u6587\u6863\u7ea7\u522b\uff0c\u4f7f\u7528\u4e86 MinHash \u7b97\u6cd5\uff1b\u5728\u884c\u7ea7\u522b\uff0c\u5c06\u6bcf 30M \u91cc\u8d85\u8fc7 6 \u6b21\u7684\u884c\u53bb\u9664\u6389\u4e86\uff0c\u8fd9\u663e\u8457\u63d0\u5347\u4e86\u8bc4\u6d4b\u8868\u73b0\u3002

    \u5176\u4e2d MinHash \u7b97\u6cd5\u662f\u4e00\u79cd\u5feb\u901f\u6bd4\u8f83\u4e24\u4e2a\u96c6\u5408\u76f8\u4f3c\u5ea6\u7684\u7b97\u6cd5\uff0c\u53ef\u4ee5\u901a\u8fc7\u6bd4\u8f83\u5355\u8bcd\u76f8\u4f3c\u5ea6\u6765\u5b9e\u73b0\u6587\u672c\u805a\u7c7b\u3002\u5b83\u9884\u8bbe\u4e24\u4e2a\u6587\u672c\u7684\u76f8\u4f3c\u5ea6\u662f\u901a\u8fc7\u8ba1\u7b97\u8bcd\u96c6 A \u548c\u8bcd\u96c6 B \u7684 Jaccard \u76f8\u4f3c\u5ea6 $ J(A, B) = \\frac{| A \\cap B |}{| A \\cup B |} $\u3002\u76ee\u7684\u662f\u4e0d\u9700\u8981\u5b9e\u9645\u8ba1\u7b97\u4e24\u4e2a\u96c6\u5408\u7684\u4ea4\u548c\u5e76\u3002\u5177\u4f53\u6211\u8ba4\u4e3a\u8fd9\u7bc7\u5e16\u5b50\u8bb2\u5f97\u5f88\u6e05\u6670 LSH\u7cfb\u52172\uff1aMinHash&LSH\u2014\u2014\u6587\u6863\uff08\u96c6\u5408\uff09\u76f8\u4f3c\u6027\u3002

    1. \u542f\u53d1\u5f0f\u8fc7\u6ee4\uff0c\u8fc7\u6ee4\u4e86\u4ee5\u4e0b\u4e09\u79cd\u5185\u5bb9\uff1a\u7528 n-gram \u8fc7\u6ee4\u4e86\u4e00\u4e9b\u884c\u91cd\u590d\u6ca1\u53bb\u6389\u7684\u5185\u5bb9\uff0c\u7528\u810f\u8bcd\u8868\u8fc7\u6ee4\u810f\u8bcd\uff0c\u7528 K-L \u6563\u5ea6\u8fc7\u6ee4\u5206\u5e03\u592a\u7279\u6b8a\u7684 token\u3002

    2. \u4ee3\u7801\u548c\u63a8\u7406\u6570\u636e\u3002\u4ece\u722c\u7684\u6570\u636e\u91cc\uff0c\u7528 fasttext \u6216 Llama 2 \u6765\u5224\u522b\u51fa\u4e00\u4e9b\u4ee3\u7801\u3001\u6570\u5b66\u7b49 STEM \u6587\u7ae0\u3002\u8fd9\u4e9b\u6587\u7ae0\u8fdb\u4e00\u6b65\u7528 DistlRoberta \u9009\u51fa\u4e86\u9ad8\u8d28\u91cf\u7684\u8bad\u7ec3\u6570\u636e\u3002

    3. \u591a\u8bed\u8a00\u6570\u636e\u3002\u7528 fasttext \u4ece\u722c\u4e0b\u6765\u7684\u6570\u636e\u4e2d\u8bc6\u522b\u51fa\u4e86 176 \u79cd\u8bed\u8a00\uff0c\u8fd9\u4e9b\u591a\u8bed\u8a00\u6570\u636e\u4e5f\u8fdb\u884c\u4e86\u53bb\u91cd\u3001\u7b5b\u9009\u7b49\u6e05\u6d17\u6b65\u9aa4\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_8","title":"\u6570\u636e\u6df7\u5408","text":"

    \u5982\u4f55\u51b3\u5b9a\u8bad\u7ec3\u6570\u636e\u7684\u5206\u5e03\u6bd4\u4f8b\uff1a

    \u8bad\u7ec3\u6570\u636e\u6df7\u5408\u6bd4\u4f8b\u7684\u603b\u7ed3\uff1a

    \u53ef\u89c1\u591a\u8bed\u8a00\u6570\u636e\u4e0d\u9700\u8981\u592a\u591a\uff0c\u4e3b\u8981\u77e5\u8bc6\u7528\u82f1\u8bed\u5b66\u8fc7\u540e\u53ef\u4ee5\u6cdb\u5316\u5230\u5176\u5b83\u8bed\u8a00\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#_9","title":"\u9000\u706b","text":"

    \u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u968f\u7740\u6a21\u578b\u9010\u6e10\u63a5\u8fd1\u8bad\u7ec3\u5b8c\u6210\uff0c\u9010\u6e10\u964d\u4f4e\u5bf9\u65b0\u6570\u636e\u7684\u6743\u91cd\uff0c\u53ef\u4ee5\u8ba9\u6a21\u578b\u66f4\u52a0\u7a33\u5b9a\u5730\u9002\u5e94\u65b0\u6570\u636e\uff0c\u800c\u4e0d\u4f1a\u5bfc\u81f4\u6a21\u578b\u53c2\u6570\u5267\u70c8\u6ce2\u52a8\u3002\u968f\u7740\u5b66\u4e60\u7387\u964d\u4f4e\uff0c\u53ea\u6709\u9ad8\u8d28\u91cf\u7684\u6570\u636e\u624d\u80fd\u663e\u8457\u63d0\u5347\u6a21\u578b\u7684\u6027\u80fd\u3002\u56e0\u6b64\u9000\u706b\u63d0\u4f9b\u4e86\u4e00\u79cd\u66f4\u6709\u6548\u7684\u65b9\u6cd5\u6765\u8bc4\u4f30\u5c0f\u578b\u7279\u5b9a\u9886\u57df\u6570\u636e\u96c6\u7684\u4ef7\u503c\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#model-architecture","title":"Model Architecture \u6a21\u578b\u67b6\u6784","text":"

    \u6027\u80fd\u7684\u63d0\u5347\u4e3b\u8981\u6765\u6e90\u4e8e\u6570\u636e\u8d28\u91cf\u7684\u63d0\u9ad8\u548c\u6a21\u578b\u66f4\u5927\u4e86\u3002

    \u6a21\u578b\u4e0e\u4e4b\u524d\u7684\u533a\u522b\uff1agroup query attention (GQA) \u53ef\u4ee5\u5e26\u6765\u5185\u5b58\u7684\u8282\u7701\u3002

    "},{"location":"docs/3-dl/survey/llama3_405b/#post-train","title":"Post-train \u5fae\u8c03","text":"

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_10","title":"\u591a\u6a21\u6001\u80fd\u529b","text":"

    \u89c6\u9891/\u56fe\u50cf\u80fd\u529b\u7684\u8bad\u7ec3\u5728\u6587\u5b57\u80fd\u529b\u8bad\u7ec3\u7ed3\u675f\u4e4b\u540e\uff0c\u6709\u989d\u5916\u7684 encoder \u548c decoder\uff0c\u8bad\u7ec3\u65f6\u5c06\u6587\u5b57\u80fd\u529b\u7684\u6743\u91cd\u51bb\u7ed3\uff0c\u53ea\u8c03\u5176\u5b83\u6a21\u6001\u7684\u53c2\u6570\u3002

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_11","title":"\u76f8\u5173\u5de5\u4f5c","text":"

    TODO

    "},{"location":"docs/3-dl/survey/llama3_405b/#_12","title":"\u53c2\u8003\u8d44\u6599","text":""},{"location":"docs/3-dl/survey/math-word-problem/","title":"Math Word Problem Survey","text":"

    :material-circle-edit-outline: \u7ea6 1080 \u4e2a\u5b57 :fontawesome-solid-code: 15 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f

    "},{"location":"docs/3-dl/survey/math-word-problem/#an-introduction-to-math-word-problems","title":"An Introduction to Math Word Problems","text":"

    The math word problem (MWP) aims to solve simple primary school math problems (in plain-text format) with deep learning methods. The problems usually consists of numbers no larger than 100 and only 5 operators (+, -, *, / and =). This blog is structured as follows. The Dataset part will introduce two main types, one indicating the locations of variables, and the other simply embedding the math formula within the natural language texts. The Methods parts will introduce several prevailing methods in solving this task, including both the models and workflows that improves the accuracy of models.

    "},{"location":"docs/3-dl/survey/math-word-problem/#surveys","title":"Surveys","text":""},{"location":"docs/3-dl/survey/math-word-problem/#the-gap-of-semantic-parsing-a-survey-on-automatic-math-word-problem-solvers-2019","title":"The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers (2019)","text":"

    This survey provides a comprehensive introduction to the MWP datasets and methods prior to 2019. This survey defines three stages of MWP solving, the Rule-based matching stage (1960-2010), Semantic parsing, feature engineering and statistical learning stage (2011-2017), and Deep learning and reinforcement learning stage (2017-2019).

    "},{"location":"docs/3-dl/survey/math-word-problem/#towards-tractable-mathematical-reasoning-challenges-strategies-and-opportunities-for-solving-math-word-problems-2021","title":"Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problems (2021)","text":"

    This survey introduces the contemporary MWP datasets til 2021, and methods including rule-based, and neural network encoder-decoder structures. Specifically, this paper concludes three strategies for math word solving, (i) direct answer generation, (ii) expression tree generation for inferring answers, and (iii) template retrieval for answer computation. Considering the type of problem solving method, this paper concludes two classes. The first class is non-neural approaches (rule-base or pattern matching approaches, semantic parsing, and statistical machine learning approaches), within which a particular strategy of applying domain knowledge in classifying the problems (e.g. into change, part-whole and compare classes). The second class is neural approaches, including intuitions of (i) predicting the answer directly (ii) generating a set of equations or mathematical expressions and inferring answers from the by executing them (iii) retrieving the templates from a pool of templates derived from training data and augmenting numerical quantities to compute the answer. These neural approaches generally follow encoder-decoder architectures, which fall in four types (i) seq-to-seq (ii) Transformer-to-tree (iii) seq-to-tree (iv) graph-to-tree. Among the four methods, the tree-structured decoder attend both parents and siblings to generate the next token, while the bottom-up representation of sub-tree of a sibling could further help to derive better outcomes. The graph-based encoder aims to learn different types of relationships among the constituents of MWPs. This section also mentions that \"Data augmentation is a popular preprocessing technique to increase the size of training data\" (reverse operation-based augmentation techniques, different traversal orders of expression trees, and weak supervision). In section Math Reasoning in Neural Approaches, this paper mentions several further topics under math reasoning, interpretability and explainability, infusing explicit and definitive knowledge, and reinforcement learning.

    "},{"location":"docs/3-dl/survey/math-word-problem/#datasets","title":"Datasets","text":""},{"location":"docs/3-dl/survey/math-word-problem/#mawps-a-math-word-problem-repository-2016","title":"MAWPS: A Math Word Problem Repository (2016)","text":"

    sroy9/mawps: Code for MAWPS: A Math Word Problem Repository (github.com) The data format is as follows. 

    [\n{\n\"iIndex\": 1,\n\"sQuestion\": \"Joan found 70.0 seashells on the beach. She gave Sam some of her seashells . She has 27.0 seashells . How many seashells did she give to Sam ?\",\n\"lEquations\": [\"X=(70.0-27.0)\"],\n\"lSolutions\": [43.0]\n},\n]\n

    "},{"location":"docs/3-dl/survey/math-word-problem/#math23k-deep-neural-solver-for-math-word-problems-2017","title":"Math23k: Deep Neural Solver for Math Word Problems (2017)","text":"

    Deep Neural Solver for Math Word Problems (aclanthology.org) This dataset is in Chinese. 

    Problem: Dan have 2 pens, Jessica have 4 pens. How many pens do they have in total ? \nEquation: x = 4+2 \nSolution: 6\n

    "},{"location":"docs/3-dl/survey/math-word-problem/#mathqa-2019","title":"MathQA (2019)","text":"

    MathQA-Dataset (math-qa.github.io) This paper proposes a math dataset which enhances the AQuA dataset by providing fully-specified operational programs. This dataset has a diverse range of operators.

    "},{"location":"docs/3-dl/survey/math-word-problem/#math-2021","title":"MATH (2021)","text":"

    arxiv.org/pdf/2103.03874.pdf MATH is a LaTeX format dataset, with its answer highlighted in a square block.

    "},{"location":"docs/3-dl/survey/math-word-problem/#svmap","title":"SVMAP","text":"

    arkilpatel/SVAMP: NAACL 2021: Are NLP Models really able to Solve Simple Math Word Problems? (github.com) This dataset does not distinguish the data with the texts. An example data is as follows.

    "},{"location":"docs/3-dl/survey/math-word-problem/#gsm8k-grade-school-math-2021","title":"GSM8k: grade school math (2021)","text":"

    Collected by OpenAI, this dataset consists of math problems in natural language descriptions, with the math formulas highlighted with special notes.The numbers are not explicitly highlighted with special symbols. Several examples of the data format are as follows.

    "},{"location":"docs/3-dl/survey/math-word-problem/#draw","title":"DRAW","text":"

    Providing 1000 grounded word problems.

    "},{"location":"docs/3-dl/survey/math-word-problem/#algebra","title":"Algebra","text":""},{"location":"docs/3-dl/survey/math-word-problem/#asdiv","title":"AsDiv","text":""},{"location":"docs/3-dl/survey/math-word-problem/#multiarith","title":"MultiArith","text":""},{"location":"docs/3-dl/survey/math-word-problem/#singleeq","title":"SingleEq","text":""},{"location":"docs/3-dl/survey/math-word-problem/#methods","title":"Methods","text":""},{"location":"docs/3-dl/survey/math-word-problem/#models","title":"Models","text":"

    Prior to 2017, the models for solving MWP are mainly concerning with neural networks. After Transformer has been released in 2017, attention-based models have been thriving. The novel models based on Transformer are mainly modifying the encoder and decoder structures, among which there are graph-encoder and tree-decoders.

    "},{"location":"docs/3-dl/survey/math-word-problem/#graph-to-tree-learning-for-solving-math-word-problems-2020","title":"Graph-to-Tree Learning for Solving Math Word Problems (2020)","text":"

    This paper proposes a attention-based model Graph2Tree, consisting of graph-based encoder and a tree-based decoder. The math word problems are constructed into Quantity Comparison Graph.

    "},{"location":"docs/3-dl/survey/math-word-problem/#math-word-problem-solving-with-explicit-numerical-values-2021","title":"Math Word Problem Solving with Explicit Numerical Values (2021)","text":"

    A novel approach called NumS2T is proposed to solve MWP. NumS2T is constructed with (a) an attention-based seq2seq model to generate its math expressions, (b) a numerical value encoder to obtain the number-aware problem state which are then concatenated with the problem hidden state in (a) to obtain number-aware problem representation, and (c) a numerical properties prediction mechanism for comparing the paired numerical values, determining the category of each numeral and measuring whether they should appear in the target expression.!

    "},{"location":"docs/3-dl/survey/math-word-problem/#learning-to-reason-deductively-math-word-problem-solving-as-complex-relation-extraction-2022","title":"Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction (2022)","text":"

    This paper proposes a novel approach

    "},{"location":"docs/3-dl/survey/math-word-problem/#workflows","title":"Workflows","text":"

    Most of the recent works follow the method of knowledge distilling, which means to generate high quality data with LLMs and then train a small model with the generated (and sometimes then augmented) data. The workflow of such tasks mainly assembles that of the following paper.

    "},{"location":"docs/3-dl/survey/math-word-problem/#large-language-models-are-reasoning-teachers","title":"Large Language Models Are Reasoning Teachers","text":"

    This paper proposes a knowledge distilling method in solving math reasoning problems.

    "},{"location":"docs/3-dl/survey/math-word-problem/#solving-math-word-problems-via-cooperative-reasoning-induced-language-models-acl-2023","title":"Solving Math Word Problems via Cooperative Reasoning induced Language Models (ACL 2023)","text":"

    This paper develops a cooperative reasoning-induced PLM for solving MWPs called Cooperative Reasoning (CoRe), with a generator to generate reasoning paths and a verifier to supervise the evaluation.

    "},{"location":"docs/3-dl/survey/math-word-problem/#scaling-relationship-on-learning-mathematical-reasoning-with-large-language-models-2023","title":"Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023)","text":"

    This paper mainly focus on the following two questions: (i) Which is a better performance indicator of LLMs? (pre-training loss amount/model size) (ii) How to improve small model's performance by data augmentation? To answer the second question, this paper proposes a novel methods in data augmentation in the LLM data generation step which is called Rejection Finetuning (RFT). The algorithm of sampling data in RFT mainly adopts the thought of rejection sampling, which is expressed in the following pseudo-code. This paper assumes such an algorithm will yield as many as possible diverse reasoning paths. The workflow of the RFT method is illustrated as follows, where the SFT stands for supervised finetuning. With the novel method RFT, small models such as Llama-7b yields an accuracy of at most 49.7% on GSM8k, 14% higher than the previous SOTA method SFT.

    "},{"location":"docs/3-dl/survey/math-word-problem/#pal","title":"PAL","text":"

    This work is a prompt engineering work. 

    Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now? \nA: Roger started with 5 tennis balls. tennis_balls = 5 2 cans of 3 tennis balls each is bought_balls = 2 * 3 tennis balls. The answer is answer = tennis_balls + bought_balls \nQ: The bakers at the Beverly Hills Bakery baked 200 loaves of bread on Monday morning. They sold 93 loaves in the morning and 39 loaves in the afternoon. A grocery store returned 6 unsold loaves. How many loaves of bread did they have left?\n

    A: The bakers started with 200 loaves loaves_baked = 200 They sold 93 in the morning and 39 in the afternoon loaves_sold_morning = 93 loaves_sold_afternoon = 39 The grocery store returned 6 loaves. loaves_returned = 6 The answer is answer = loaves_baked - loaves_sold_morning - loaves_sold_afternoon + loaves_returned\n
    "},{"location":"docs/3-dl/survey/math-word-problem/#preview","title":"Preview","text":""},{"location":"docs/3-dl/survey/multilingual/","title":"Multilingual Task Survey","text":"

    :material-circle-edit-outline: \u7ea6 768 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    "},{"location":"docs/3-dl/survey/multilingual/#introduction","title":"Introduction","text":"

    \u591a\u8bed\u8a00\u6a21\u578b multilingual models \u5c31\u662f\u80fd\u89e3\u51b3\u591a\u8bed\u8a00\u4efb\u52a1\u7684\u6a21\u578b\u3002\u5728\u4e3b\u6d41\u8bad\u7ec3\u6570\u636e\u662f\u82f1\u8bed\u3001\u7a00\u6709\u8bed\u8a00\u6570\u636e\u7a00\u7f3a\u7684\u80cc\u666f\u4e0b\uff0c\u5982\u4f55\u5c06\u6a21\u578b\u80fd\u529b\u6cdb\u5316\u5230\u7a00\u6709\u8bed\u8a00\u662f\u91cd\u8981\u7684\u95ee\u9898\u3002\u9664\u4e86\u6700\u8fd1\u7684\u5927\u8bed\u8a00\u6a21\u578b\u5916\uff0c\u8fd8\u4f1a\u4ecb\u7ecd\u4f20\u7edf\u65b9\u6cd5\u548c\u4f20\u7edf\u6a21\u578b\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#survey","title":"Survey","text":""},{"location":"docs/3-dl/survey/multilingual/#a-survey-on-large-language-models-with-multilingualism-recent-advances-and-new-frontiers-2024","title":"A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers (2024)","text":""},{"location":"docs/3-dl/survey/multilingual/#_1","title":"\u7b80\u4ecb","text":"

    \u672c\u6587\u4ecb\u7ecd\u591a\u8bed\u8a00\u5927\u8bed\u8a00\u6a21\u578b\u7684\u8bad\u7ec3\u3001\u4f7f\u7528\u3001\u6311\u6218\u3001\u672a\u6765\u7814\u7a76\u65b9\u5411\u7b49\u3002\u7531 Beijing Jiaotong University, University of Montreal \u548c Tsinghua University \u53d1\u5e03\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_2","title":"\u8bad\u7ec3","text":""},{"location":"docs/3-dl/survey/multilingual/#_3","title":"\u6709\u591a\u8bed\u8a00\u80fd\u529b\u7684\u5927\u8bed\u8a00\u6a21\u578b\u6982\u89c8","text":""},{"location":"docs/3-dl/survey/multilingual/#_4","title":"\u591a\u8bed\u8a00\u63a8\u7406\u7b56\u7565","text":""},{"location":"docs/3-dl/survey/multilingual/#_5","title":"\u5b89\u5168\u6027","text":""},{"location":"docs/3-dl/survey/multilingual/#_6","title":"\u591a\u9886\u57df\u591a\u8bed\u8a00\u5927\u8bed\u8a00\u6a21\u578b","text":""},{"location":"docs/3-dl/survey/multilingual/#_7","title":"\u591a\u8bed\u8a00\u6570\u636e\u8d44\u6e90","text":""},{"location":"docs/3-dl/survey/multilingual/#_8","title":"\u591a\u8bed\u8a00\u8bc4\u6d4b","text":""},{"location":"docs/3-dl/survey/multilingual/#_9","title":"\u504f\u89c1\u548c\u516c\u5e73\u6027","text":""},{"location":"docs/3-dl/survey/multilingual/#models","title":"Models","text":""},{"location":"docs/3-dl/survey/multilingual/#datasets","title":"Datasets","text":""},{"location":"docs/3-dl/survey/multilingual/#studies","title":"Studies","text":""},{"location":"docs/3-dl/survey/multilingual/#do-llamas-work-in-english-2024-epfl","title":"Do Llamas Work in English? (2024, EPFL)","text":"

    \u731c\u60f3\uff1a\u591a\u8bed\u8a00\u6a21\u578b\uff08\u6bd4\u5982 Llama\uff09\u5728\u4f7f\u7528\u4ee5\u82f1\u8bed\u4e3a\u4e3b\u7684\u8bed\u6599\u8fdb\u884c\u8bad\u7ec3\u65f6\uff0c\u4f1a\u5c06\u82f1\u8bed\u4f5c\u4e3a\u4e00\u79cd\u601d\u8003\u7684\u4e2d\u95f4\u6b65\u9aa4 pivot language\u3002

    \u5b9e\u9a8c\u65b9\u6cd5\uff1a\u5bf9 Llama-2 \u7cfb\u5217\u6a21\u578b\uff0c\u8bbe\u8ba1\u6570\u636e\u5bf9 (\u975e\u82f1\u8bed\u63d0\u793a\u8bcd\uff0cnext token)\u3002\u4ece\u9876\u5c42\u5411\u91cf\u7a7a\u95f4 high-dimensional space \u63a2\u7d22\u4e2d\u95f4\u5d4c\u5165 intermediate embeddings \u5982\u4f55\u8ba1\u7b97\u4e0b\u4e00\u4e2a\u5355\u8bcd\u7684\u89c4\u5f8b\u3002

    \u53d1\u73b0\u4e09\u4e2a\u9636\u6bb5\uff1a

    \u4e00\u53e5\u8bdd\u603b\u7ed3\uff1aimtermediate embedding \u6240\u4ee3\u8868\u7684\u62bd\u8c61\u6982\u5ff5\u7a7a\u95f4 concept space \u66f4\u63a5\u8fd1\u82f1\u8bed\uff0c\u53ef\u80fd\u5bfc\u81f4\u591a\u8bed\u8a00\u6a21\u578b\u4e2d\u7684\u504f\u89c1\u95ee\u9898\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#language-specific-neurons-the-key-to-multilingual-capability-in-large-language-models-2024-ruc","title":"Language-Specific Neurons: The Key to Multilingual Capability in Large Language Models (2024, RUC)","text":""},{"location":"docs/3-dl/survey/multilingual/#_10","title":"\u80cc\u666f","text":"

    \u8bc6\u522b\u591a\u8bed\u8a00\u5927\u6a21\u578b\u91cc\uff0c\u4ea7\u751f\u7279\u5b9a\u8bed\u8a00\u80fd\u529b\u7684\u795e\u7ecf\u5143\u4ecd\u7136\u975e\u5e38 challenging\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_11","title":"\u65b9\u6cd5","text":"

    \u63d0\u51fa\u4e86 language activation probability entropy (LAPE) \u6765\u68c0\u6d4b\u5927\u8bed\u8a00\u6a21\u578b\u4e0d\u540c\u8bed\u8a00\u5bf9\u5e94\u7684\u795e\u7ecf\u5143\u3002

    LAPE: \u4e3a\u4e86\u51cf\u5c11 RLHF \u53ef\u80fd\u5e26\u6765\u7684\u5bf9\u8bed\u8a00\u504f\u597d\u7684\u7684\u5f71\u54cd\uff0c\u4e3b\u8981\u5173\u6ce8\u9884\u8bad\u7ec3\u8fc7\u7684\u6a21\u578b\uff0c\u800c\u4e0d\u662f\u5fae\u8c03\u540e\u7684\u6a21\u578b\u3002

    \u5bf9\u4e8e\u5728\u7b2c i \u5c42\u7684\u7b2c j \u4e2a neuron\uff0c\u5b9a\u4e49\u5728\u8bed\u8a00 k \u4e0a\u7684\u6fc0\u6d3b\u6982\u7387 activation probability

    \\[ p_{i,j}^k = E(I(act_fn(\\tilde{h}^iW_1^i)_j \\lt 0 | language\\spacek)) \\]

    I \u662f indicator function\uff08\u5f53\u7ed9\u5b9a\u6761\u4ef6\u4e3a\u771f\u65f6\uff0c\u6307\u793a\u51fd\u6570\u7684\u503c\u4e3a 1\uff1b\u5f53\u7ed9\u5b9a\u6761\u4ef6\u4e3a\u5047\u65f6\uff0c\u6307\u793a\u51fd\u6570\u7684\u503c\u4e3a 0\uff09\u3002

    \u4ee5\u6b64\u53ef\u4ee5\u83b7\u5f97\u6bcf\u4e2a\u795e\u7ecf\u5143\u5bf9\u8bed\u8a00\u7684\u5206\u5e03

    \\[ p_{i,j} = (p_{i,j}^1, ... , p_{i,j}^k, ... , p_{i,j}^l) \\]

    \u5b9a\u4e49\u4e0a\u8ff0\u5206\u5e03\u7684\u71b5\u4e3a language activation probability entropy (LAPE) \u3002

    \\[ LAPE_{i,j} = -\\sum^{l}_{k=1} p^{\\prime k}_{i,j} log(p^{\\prime k}_{i,j}) \\]

    \u4f7f\u7528 Llama-2, BLOOM, Mistral \u548c Phi-2 \u8fdb\u884c\u5b9e\u9a8c\uff0c\u53d1\u73b0\u8fd9\u4e9b\u795e\u7ecf\u5143\u4e3b\u8981\u5728\u9876\u5c42\u548c\u5e95\u5c42 embedding \u4e0a\u3002

    "},{"location":"docs/3-dl/survey/multilingual/#_12","title":"\u53d1\u73b0","text":""},{"location":"docs/3-dl/tools/","title":"Tools","text":"

    :material-circle-edit-outline: \u7ea6 13 \u4e2a\u5b57

    Any tool recommendations, or any tutorial or tutorial remmondations.

    "},{"location":"docs/3-dl/tools/#contents","title":"Contents","text":""},{"location":"docs/3-dl/tools/codabench/","title":"Codabench \u6bd4\u8d5b\u521b\u5efa\u6559\u7a0b","text":"

    :material-circle-edit-outline: \u7ea6 2098 \u4e2a\u5b57 :fontawesome-solid-code: 82 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f

    "},{"location":"docs/3-dl/tools/codabench/#_1","title":"\u7b80\u4ecb","text":"

    Codabench \u662f\u4e00\u4e2a\u4e3a\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u6bd4\u8d5b\u8bbe\u8ba1\u7684\u4f4e\u4ee3\u7801\u6a21\u578b\u6d4b\u8bd5\u5e73\u53f0\u3002\u5e73\u53f0\u63d0\u4f9b CPU\uff0c\u5141\u8bb8\u6bd4\u8d5b\u521b\u529e\u8005\u901a\u8fc7\u4e0a\u4f20\u811a\u672c\u548c\u6570\u636e\u7684\u65b9\u5f0f\u521b\u529e\u6bd4\u8d5b\uff0c\u5e76\u5141\u8bb8\u5176\u5b83\u7528\u6237\u4f7f\u7528\u5e73\u53f0 CPU \u6765\u8fd0\u884c\u4ee3\u7801\u5f97\u5230\u7ed3\u679c\u3002\u524d\u5e8f\u5de5\u4f5c\u662f CodaLab\uff0c2023 \u5e74 Codabench \u56e2\u961f\u4eff\u7167 CodaLab \u6539\u8fdb\u51fa\u4e86 Codabench\u3002

    Codabench \u7684\u4f18\u70b9\u662f\u63d0\u4f9b\u516c\u5171 CPU\uff0c\u4f7f\u6bd4\u8d5b\u521b\u529e\u65b9\u5728\u5c06\u6b63\u786e\u7b54\u6848\u4fdd\u5bc6\u7684\u60c5\u51b5\u4e0b\uff0c\u4e0d\u5fc5\u4eb2\u624b\u6536\u96c6\u53c2\u8d5b\u8005\u7684\u7b54\u6848\u5e76\u4e00\u4e00\u4eb2\u624b\u6d4b\u8bd5\uff0c\u800c\u662f\u5141\u8bb8\u7528\u6237\u81ea\u884c\u901a\u8fc7\u5e73\u53f0\u6d4b\u8bd5\u5e76\u5f97\u5230\u7ed3\u679c\uff0c\u51cf\u8f7b\u8d1f\u62c5\u3002\u800c\u7528\u6237\u4e5f\u53ef\u4ee5\u66f4\u8fc5\u901f\u77e5\u9053\u81ea\u5df1\u7684\u5206\u6570\uff0c\u4e0d\u5fc5\u7b49\u5f85\u6bd4\u8d5b\u65b9\u9a8c\u8bc1\u8fd9\u4e2a\u65f6\u95f4\u8f83\u957f\u7684\u6d41\u7a0b\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_2","title":"\u8fd0\u4f5c","text":"

    \u6bd4\u8d5b\u521b\u529e\u8005\u901a\u8fc7\u4e0a\u4f20\u6bd4\u8d5b\u914d\u7f6e\u540e\uff0c\u6bcf\u5f53\u6709\u7528\u6237\u52a0\u5165\u5e76\u63d0\u4ea4\u4e00\u4e2a\u8fd0\u884c\u8bf7\u6c42\uff0c\u5e73\u53f0\u5c06\u5728 CPU \u4e0a\u4e3a\u6bcf\u4e2a\u63d0\u4ea4\u521b\u5efa\u4e00\u4e2a Docker\uff0c\u5305\u542b\u6bd4\u8d5b\u521b\u529e\u8005\u63d0\u4f9b\u7684\u6bd4\u8d5b\u914d\u7f6e\u548c\u8be5\u7528\u6237\u63d0\u4ea4\u7684\u6570\u636e\uff0c\u5728 Docker \u4e2d\u8fd0\u884c\u6307\u5b9a\u8def\u5f84\u7684\u4ee3\u7801\uff0c\u5e76\u5c06\u7ed3\u679c\u663e\u793a\u5728\u5e73\u53f0\u5c55\u793a\u7684 terminal \u4e0a\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_3","title":"\u521b\u5efa","text":"

    \u5728 Codabench \u5b98\u7f51\u6ce8\u518c\u767b\u9646\u540e\uff0c\u70b9\u51fb\u53f3\u4e0a\u89d2 Benchmark -> Management\uff0c\u53ef\u4ee5\u9009\u62e9 Create \u6216 Upload \u6765\u521b\u5efa\u6bd4\u8d5b\u3002

    \u66f4\u63a8\u8350\u7528 Upload \u6765\u521b\u5efa\uff0c\u56e0\u4e3a UI \u7684\u7528\u6237\u63d0\u793a\u6bd4\u8f83\u6b20\u7f3a\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_4","title":"\u4e0a\u4f20\u521b\u5efa","text":"

    'bundle' \u6307\u6bd4\u8d5b\u521b\u5efa\u8005\u4e0a\u4f20\u7684\u538b\u7f29\u6587\u4ef6\u3002\u91cc\u9762\u542b\u6709\uff1a

    \u9700\u8981\u671f\u5f85\u7528\u6237\u4e0a\u4f20\uff1a

    \u4e0b\u9762\u4ecb\u7ecd\u51e0\u4e2a\u5b98\u65b9\u6587\u6863\u8bb2\u5f97\u4e0d\u592a\u6e05\u695a\u7684\u7ec6\u8282\u3002

    "},{"location":"docs/3-dl/tools/codabench/#competitionyaml","title":"competition.yaml \u6587\u4ef6","text":"

    competition.yaml \u6587\u4ef6\u4e0d\u80fd\u6539\u540d\uff0c\u4e14\u5fc5\u987b\u4f4d\u4e8e .zip \u4e2d\u7684\u6700\u9876\u5c42\uff08\u5373\u591a\u9009 competition.yaml \u548c\u5176\u5b83\u6587\u4ef6\u5939\u540e\u521b\u5efa .zip\uff0c\u800c\u975e\u628a\u542b\u6709 competition.yaml \u548c\u5176\u5b83\u6587\u4ef6\u5939\u7684\u4e0a\u5c42\u6587\u4ef6\u5939\u521b\u5efa\u4e3a .zip\uff09\u3002\u5177\u4f53\u5982\u56fe\u6240\u793a\u3002\u4e0b\u6587\u6240\u63d0\u5230\u7684\u65e0\u9876\u5c42\u6587\u4ef6\u5939 / \u6587\u4ef6\u4f4d\u4e8e\u538b\u7f29\u5305\u9876\u5c42\uff0c\u90fd\u662f\u6307\u5982\u56fe\u6240\u793a\u7684\u538b\u7f29\u5305\u7ed3\u6784\u3002

    competition.yaml \u652f\u6301\u7684\u5b57\u6bb5\u6709\uff1a

    title: # \u6bd4\u8d5b\u540d\nversion: # 1 \u6307\u662f CodaLab bundle\uff0c2 \u6307 CodaBench bundle\uff0c\u533a\u522b\u662f\u6709\u4e9b competition.yaml \u5b57\u6bb5\u4e0d\u517c\u5bb9\ndescription: # \u6bd4\u8d5b\u63cf\u8ff0\nimage: # \u6bd4\u8d5b logo.png\nregistration_auto_approve: True  # do not require approval from organizers to join\ndocker_image: codalab/codalab-legacy:py39 # the Docker image in which submissions are run\uff0c\u7528\u6b64 default \u5373\u53ef\nenable_detailed_results: True # \u4e0d\u660e\uff0c\u53ef\u4ee5 default\n# Documentation web pages\nterms: pages/terms.md # \u5fc5\u987b\u6709\u4e00\u4e2a terms\npages:  # \u53ef\u4efb\u610f\u52a0\u9875\u9762\n- title: # e.g., Overview\nfile: # e.g., pages/overview.md\n# Definition of the tasks\ntasks:\n- index: 0\nname: # e.g., Development Task\ndescription: # \u63cf\u8ff0\nis_public: true   # \u516c\u5f00\u53ef\u89c1\ninput_data: # e.g., feedback_phase/input_data, \u6b64\u5904\u53ca\u4e0b\u5217\u8def\u5f84\u9700\u8981\u586b\u5199\u6240\u4e0a\u4f20 bundle \u91cc\u7684\u8def\u5f84\uff0c\u800c\u975e\u6240\u751f\u6210 Docker \u4e2d\u7684\nreference_data: # e.g., feedback_phase/reference_data\nscoring_program: # e.g., scoring_program\ningestion_program: # e.g., ingestion_program\nsolutions: []   # \u4e0d\u660e\n# Sample code submission\nsolutions:      # \u53ef\u80fd\u4f1a\u663e\u793a\u5728\u6bd4\u8d5b\u9996\u9875\u7684 resources \u5217\u8868\n- index: 0\ntasks:\n- 0\n- 1\npath: solution/\nphases:\n- index: 0\nname:             # phase \u6807\u9898\ndescription:      # \u63cf\u8ff0\nstart: 1-1-2024   # Month / Day / Year\nend: 1-30-2024    # end \u7ed3\u675f\u65f6\u95f4\u53ef\u4ee5\u7f3a\u5931\uff0c\u8868\u793a\u6c38\u8fdc\u53ef\u63d0\u4ea4\nmax_submissions_per_day: 5    # \u6700\u5927\u4f3c\u4e4e\u662f 100\uff1f\nmax_submissions: 100          # \u6700\u5927\u4f3c\u4e4e\u662f 10000\uff1f\nexecution_time_limit: 600     # \u6bcf\u6b21\u63d0\u4ea4\u5141\u8bb8\u7684\u6700\u957f\u8fd0\u884c\u65f6\u95f4\uff0c\u8d85\u8fc7\u8fd9\u4e2a\u65f6\u95f4\u5c06\u663e\u793a run time exceed\ntasks:            # \u4e0e\u8be5 phase \u5173\u8054\u7684 tasks\n- 0\nsolutions: []\nstarting_kit: # e.g., starting_kit, \u53ef\u80fd\u4f1a\u663e\u793a\u5728\u6bd4\u8d5b\u9996\u9875\u7684 resources \u5217\u8868\npublic_data: # e.g., starting_kit, feedback_phase/input_data\n# Fact sheets to add more information in the leaderboard\nfact_sheet: {                   # \u4f3c\u4e4e\u662f\u5c55\u793a\u5728 leaderboard \u4e2d\u652f\u6301\u7528\u6237\u4fee\u6539\u7684\u66f4\u591a\u4fe1\u606f\u3002`method_name` \u8be5\u5b57\u6bb5\u5e94\u4e0e\u4e0b\u65b9 `results` \u5e73\u7ea7\u3002\n\"method_name\": {\n\"key\": \"method_name\",\n\"type\": \"text\",\n\"title\": \"Method name\",\n\"selection\": \"\",\n\"is_required\": \"false\",\n\"is_on_leaderboard\": \"true\"\n}\n}\n# Leaderboard\nleaderboards:\n- index: 0\ntitle: Results                    # leaderboard \u7684 title\nkey: Results                      # `output.json` \u4e2d\u7528\u4e8e\u5b9a\u4f4d\u7684 key\nsubmission_rule: \"Force_Last\"     # \u53ef\u4ee5\u53bb\u6389\uff0c\u9ed8\u8ba4\u4f3c\u4e4e\u662f\u5141\u8bb8\u5c55\u793a\u591a\u4e2a\u7ed3\u679c\ncolumns:\n- title: Average Accuracy     # \u5728 output.json \u4e2d\uff0c\u8bfb\u53d6\u8be5 json \u7684\u54ea\u4e2a key\nkey: avg_accuracy           # `output.json` \u4e2d\u7528\u4e8e\u5b9a\u4f4d\u7684 key\nindex: 0                    # \u5c55\u793a\u5728 leaderboard \u8868\u683c\u4e2d\u7684\u7b2c\u51e0\u5217\nsorting: desc               # \u5347\u5e8f/\u964d\u5e8f\u6392\u5217\ncomputation: avg            # \u540c\u4e00\u7528\u6237\u7684\u591a\u4e2a\u63d0\u4ea4\uff0c\u6309\u4ec0\u4e48\u8ba1\u7b97\u65b9\u6cd5\u6392\u5e8f\uff1f\ncomputation_indexes:        # \u5728\u54ea\u4e00\u5217\u4e0a\u8ba1\u7b97\n- 1\n
    "},{"location":"docs/3-dl/tools/codabench/#scoring-program","title":"scoring program \u7684\u8def\u5f84\u8bf4\u660e","text":"

    \u5947\u5f02\u7684\u662f\uff0c\u6bd4\u8d5b\u8fd0\u884c\u65f6\u6240\u521b\u5efa\u7684 Docker \u4e2d\u6587\u4ef6\u7ed3\u6784\u5e76\u4e0d\u662f bundle \u7684\u7ed3\u6784\uff0c\u6216\u8005\u793a\u4f8b competition.yml \u4e2d\u6307\u793a\u7684\u8def\u5f84\uff0c\u800c\u662f\u4f1a\u628a\u5404\u79cd\u8d44\u6e90\u7ed3\u6784\u6253\u4e71\u653e\u5728\u4e0d\u540c\u7684\u4f4d\u7f6e\u3002\u5bf9\u6211\u4eec\u5f71\u54cd\u5c31\u662f\uff0c\u5982\u679c scoring program \u9700\u8981\u8bfb\u5176\u5b83\u6587\u4ef6\uff08\u591a\u4ee3\u7801\u6587\u4ef6 / gold answer \u7b49\uff09\uff0c\u5c31\u9700\u8981\u6309\u521b\u5efa\u597d\u7684 Docker \u4e2d\u7684\u65b0\u6587\u4ef6\u8def\u5f84\u8bfb\u53d6\u3002

    \u6bd4\u5982\uff0c\u5728\u6211\u7684\u6d4b\u8bd5\u4e2d\uff0cDocker \u7684\u5b9e\u9645\u6587\u4ef6\u5939\u7ed3\u6784\u5982\u4e0b\uff1a

    .\n- app\n    - codalab           // \u4e0d\u660e\n    - data              // \u4e0d\u660e\n    - input\n        - res           // \u7528\u6237\u7ed3\u679c\n        - ref           // gold anwser\n    - shared            // \u4e0d\u660e\n    - program           // \u6240\u4e0a\u4f20\u811a\u672c\n        - score.py\n        - metadata.yaml\n    - output            // \u811a\u672c\u8f93\u51fa\uff0c\u7528\u4e8e leaderboard \u8bfb\u53d6\n        - output.json\n

    \u5982\u679c\u4e0a\u8ff0\u8def\u5f84\u5728\u4f60\u7684\u6d4b\u8bd5\u4e2d\u4e0d work\uff0c\u53ef\u4ee5\u5148\u4e0a\u4f20\u4e00\u4e2a\u542b\u6709 competition.yaml / scoring program / reference data / result data / ingestion program \u7b49\u6240\u6709\u8d44\u6e90\u7684\u6d4b\u8bd5 bundle\uff0c\u8981\u6c42 scoring program \u8f93\u51fa Docker \u7684\u6587\u4ef6\u5939\u7ed3\u6784\u6811\uff0c\u5728 terminal \u4e2d\u4f9d\u6b21\u8bb0\u4e0b\u8d44\u6e90\u7684\u8def\u5f84\u3002

    "},{"location":"docs/3-dl/tools/codabench/#scoring-program_1","title":"scoring program \u7684\u8f93\u51fa\u8bf4\u660e","text":"

    scoring program \u5728\u8fd0\u884c\u5b8c\u6210\u540e\u88ab\u671f\u5f85\u5199\u4e00\u4e2a output.json \u6587\u4ef6\uff0c\u5176\u8def\u5f84\u5728\u524d\u4e00\u8282\u6709\u8bf4\u660e\u3002\u5176\u7ed3\u6784\u636e\u63a8\u6d4b\u5e94\u5f53\u662f\uff0c

    {\n\"leaderboards_key\": {\n\"column_key1\": 0,\n\"column_key2\": 0,\n...\n}\n}\n

    \u5176\u4e2d\u51e0\u4e2a 'key' \u5206\u522b\u5bf9\u5e94\u5728 competition.yaml \u7684 leaderboards \u8bbe\u7f6e\u4e2d\u81ea\u5b9a\u4e49\u7684 key\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_5","title":"\u5e38\u89c1\u62a5\u9519","text":"

    \u5c06 bundle \u62d6\u5165 Upload \u9875\u9762\u540e\uff0c\u5982\u679c\u62a5\u9519\u663e\u793a Creation Fail\uff0c\u6b64\u65f6\u9996\u5148\u5e94\u5f53\u68c0\u67e5\u662f\u5426\u6709 competition.yaml \u6587\u4ef6\uff0c\u6587\u4ef6\u540d\u548c\u5185\u5bb9\u683c\u5f0f\u6b63\u786e\uff0c\u5e76\u4e14\u4f4d\u4e8e\u538b\u7f29\u5305\u9876\u5c42\uff08\u53c2\u7167\u4e0a\u65b9\u538b\u7f29\u56fe\u793a\uff09\u3002\u4e00\u822c\u662f\u6b64\u9519\u8bef\u3002

    "},{"location":"docs/3-dl/tools/codabench/#bundle","title":"bundle \u6a21\u677f","text":"

    codalab/competition-examples/codabench \u5b98\u65b9\u63d0\u4f9b\u7684\u51e0\u4e2a bundle \u6a21\u677f\uff0c\u53ef\u4ee5\u5bf9\u6bd4 Codabench \u4e0a\u540c\u540d\u6bd4\u8d5b\u67e5\u770b\u521b\u5efa\u7ed3\u679c\uff0c\u5728\u672c\u4ed3\u5e93\u62ff\u4e00\u4e9b\u9700\u8981\u7684\u5199\u6cd5\u3002

    "},{"location":"docs/3-dl/tools/codabench/#ui","title":"UI \u521b\u5efa","text":"

    \u8fdb\u5165 Codabench \u9996\u9875\uff0c\u70b9\u51fb\u53f3\u4e0a\u89d2 Benchmark -> Management\uff0c\u9009\u62e9 Upload \u6765\u521b\u5efa\u6bd4\u8d5b\u3002

    \u9876\u5c42\u6709 Details / Participation / Pages / Phases / Leaderboard / Administrators \u516d\u4e2a\u9875\u9762\uff0c\u5176\u5b83\u8f83\u6613\u61c2\uff0c\u4e0d\u518d\u8d58\u8ff0\uff0cPhases \u7684\u8bbe\u7f6e\u6bd4\u8f83\u590d\u6742\u3002

    Phases \u6784\u6210\u6bd4\u8d5b\u4e3b\u4f53\u3002\u4e00\u4e2a\u6bd4\u8d5b\u53ef\u4ee5\u6709\u4e00\u4e2a\u6216\u591a\u4e2a phase\uff0c\u8fd9\u6837\u8bbe\u8ba1\u53ef\u80fd\u662f\u6709\u4e9b\u6bd4\u8d5b\u5206\u6210\u5728\u591a\u4e2a\u6570\u636e\u96c6\u4e0a\u6d4b\u8bd5\uff1b\u4e00\u4e2a phase \u53c8\u53ef\u4ee5\u5305\u542b\u591a\u4e2a tasks\uff0c\u53ef\u80fd\u662f\u4e3a\u4e86\u652f\u6301\u6709\u4e9b\u6bd4\u8d5b\u6bcf\u4e2a phase \u53c8\u6709\u591a\u4e2a\u6570\u636e\u96c6\u3002phase \u4e4b\u95f4\u4e0d\u5171\u4eab\u8d44\u6e90/Docker \u73af\u5883\uff0c\u540c\u4e00\u4e2a phase \u7684\u4e0d\u540c task \u4e4b\u95f4\u5171\u4eab\u8d44\u6e90/\u73af\u5883\u3002

    \u6700\u7b80\u5355\u7684\u65b9\u5f0f\u53ef\u4ee5\u53ea\u5b9a\u4e49\u4e00\u4e2a phase\u3002\u533a\u5206\u6570\u636e\u96c6\u751a\u81f3\u53ef\u4ee5\u53ea\u901a\u8fc7 scoring program \u6765\u5b9e\u73b0\u3002

    \u5728 phase \u7684 edit \u754c\u9762\u6700\u4e0b\u65b9\uff0c\u53ef\u4ee5\u901a\u8fc7 Manage tasks \u6309\u94ae\u6253\u5f00 task \u7684 edit \u754c\u9762\u3002

    \u8be5\u754c\u9762\u4e2d Submission / Datasets and programs / Bundles \u4e09\u4e2a\u9875\u9762\u90fd\u53ef\u4ee5\u5ffd\u89c6\uff0c\u53ea\u9700\u8981\u4f7f\u7528 Tasks \u8fd9\u4e2a\u9875\u9762\u3002

    task \u7684\u672c\u8d28\u610f\u4e49\u662f scoring program \u548c reference data / ingestion program / result data \u7684\u5173\u8054\u65b9\u5f0f\u3002

    \u5982\u679c\u5b9a\u4e49\u4e00\u4e2a phase \u6709\u591a\u4e2a tasks\uff0c\u5728\u7528\u6237\u63d0\u4ea4\u65f6\uff0c\u4f1a\u663e\u793a\u9009\u62e9\u63d0\u4ea4\u54ea\u4e2a task \u7684\u590d\u9009\u6846\u3002\u5f53\u590d\u9009\u6846\u88ab\u52fe\u9009\u65f6\uff0ctask \u6240\u5173\u8054\u7684 scoring program \u88ab\u8fd0\u884c\u3002

    \u5f53\u7136\u4e5f\u6709\u4e0d\u521b\u5efa\u591a\u4e2a task\uff0c\u5c06\u591a\u4e2a\u8bc4\u6d4b\u5408\u5e76\u4e3a\u4e00\u4e2a\u811a\u672c\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728\u811a\u672c\u91cc\u68c0\u6d4b\u7528\u6237\u4e0a\u4f20\u4e86\u54ea\u4e9b\u7ed3\u679c\uff0c\u636e\u6b64\u9009\u62e9\u8fd0\u884c\u54ea\u4e9b\u8bc4\u6d4b\u3002\u8fd9\u91cc scoring program \u7684\u8bbe\u8ba1\u81ea\u7531\u5ea6\u6bd4\u8f83\u9ad8\u3002

    \u5728 task \u7684\u7f16\u8f91\u9875\u9762\u91cc\uff0c

    \u8d44\u6e90\u6587\u4ef6\u5939\u540d\u5fc5\u987b\u4e0e\u6bd4\u8d5b\u521d\u59cb\u5316\u65f6 competition.yaml \u6307\u5b9a\u7684\u6587\u4ef6\u5939\u540d\u76f8\u540c\uff0c\u538b\u7f29\u5305\u540d\u548c\u5728\u8fd9\u91cc\u586b\u5199\u7684\u8d44\u6e90\u522b\u540d\u5219\u4efb\u610f\u3002\u4f8b\u5982\uff0c\u5728 competition.yaml \u4e2d\u6307\u5b9a\u4e86 reference data \u7684\u6587\u4ef6\u5939\u540d\u662f ref_data\uff0c\u90a3\u4e48\u5728\u4e0a\u4f20\u65f6\u4e5f\u9700\u8981\u5c06\u4e00\u4e2a\u540d\u4e3a ref_data \u7684\u6587\u4ef6\u5939\u8fdb\u884c\u538b\u7f29\u3002\u4f46\u662f\u538b\u7f29\u540e\u5f97\u5230\u7684\u538b\u7f29\u5305\u540d\u5b57\u968f\u610f\uff0c\u53ef\u4ee5\u53eb AAA.zip \u7b49\uff1b\u4e0a\u4f20\u540e\u5728 UI \u5904\u4f1a\u5141\u8bb8\u4f60\u4e3a\u8fd9\u6b21\u4e0a\u4f20\u7684\u8d44\u6e90\u8d77\u4e00\u4e2a\u522b\u540d\uff0c\u4e5f\u662f\u968f\u610f\u7684\uff0c\u53ef\u4ee5\u53eb ref_data20240925 \u7b49\u3002\u5982\u9047\u5230\u8d44\u6e90\u4e0a\u4f20\u5931\u8d25\u4f46\u65e0\u62a5\u9519\uff0c\u53ef\u4ee5\u4f18\u5148\u8003\u8651\u8fd9\u4e2a\u539f\u56e0\u3002

    \u6bcf\u4e2a task \u4e2d\uff0c\u5fc5\u987b\u6dfb\u52a0\u7684\u8d44\u6e90\u662f scoring program\uff0c\u6709\u8fd9\u4e2a\u624d\u80fd\u8fd0\u884c\u3002\u53ef\u6839\u636e\u9700\u8981\u6dfb\u52a0 reference data\u3002

    \u8d44\u6e90\u53ea\u6709\u5728\u6ca1\u6709\u4e0e\u4e4b\u5173\u8054\u7684 task \u65f6\u624d\u80fd\u88ab\u4ece\u8d44\u6e90\u5217\u8868\u4e2d\u5220\u9664\u3002\u5f53\u5b58\u5728\u6ca1\u6709 task \u5173\u8054\u7684\u8d44\u6e90\u65f6\uff0c\u4e0b\u9762 Quota and Cleanup \u4e2d\u4f1a\u9ad8\u4eae Delete unused datasets/programs\uff0c\u53ef\u4ee5\u70b9\u51fb\u4e00\u952e\u6e05\u9664\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_6","title":"\u4fee\u6539","text":"

    \u53ea\u652f\u6301\u901a\u8fc7 UI \u4fee\u6539\u3002\u4e0d\u80fd\u91cd\u65b0\u4e0a\u4f20 bundle\uff0c\u6bcf\u6b21\u91cd\u65b0\u4e0a\u4f20 bundle \u5c31\u89c6\u4e3a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u6bd4\u8d5b\u3002

    \u8fdb\u5165 Codabench \u9996\u9875 -> \u53f3\u4e0a\u89d2 Benchmark -> Management -> \u9009\u62e9\u4e00\u4e2a\u5df2\u6709\u7684\u6bd4\u8d5b\u53f3\u4fa7 Edit \u6309\u94ae\u3002

    \u5176\u4f59\u6b65\u9aa4\u540c\u4e0a\u65b9 ### UI \u521b\u5efa \u4e00\u8282\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_7","title":"\u4f7f\u7528","text":"
    1. \u63d0\u4ea4\uff1a\u4e0a\u4f20\u65e0\u9876\u5c42\u6587\u4ef6\u5939\u7684\u591a\u4e2a\u7ed3\u679c\u6587\u4ef6\u5939\u538b\u7f29\u5305\u3002\u8bfb\u6761\u7ed3\u675f\u540e\u5c06\u663e\u793a\u4e00\u4e2a running xxx\uff0c\u81ea\u52a8\u8fdb\u5165\u8fd0\u884c\u3002\u5982\u672a\u663e\u793a running \u8fd9\u4e2a\u6846\uff0c\u4e00\u822c\u662f\u5e73\u53f0 CPU \u7d27\u7f3a\uff0c\u53ef\u4ee5\u7b49\u5f85\u4e00\u6bb5\u65f6\u95f4\u518d\u5c1d\u8bd5\u3002\u5982\u679c\u663e\u793a\u5219\u8bf4\u660e\u5f00\u59cb\u8fd0\u884c\u4e86\u3002
    2. \u67e5\u770b\u7ed3\u679c\uff1a\u70b9\u51fb running xxx \u53ef\u4ee5\u67e5\u770b\u8fd0\u884c\u671f\u95f4\u7684 terminal \u8f93\u51fa\uff0c\u6b64\u5904 terminal \u662f\u6b63\u5e38\u7684 terminal\uff0c\u4f1a\u663e\u793a\u6240\u6709 warning / error / \u8f93\u51fa\u3002\u8fd0\u884c\u5b8c\u6210\u540e\u5e94\u5f53\u663e\u793a Finish\u3002
    3. \u67e5\u770b\u62a5\u9519\uff1a\u5982\u679c\u72b6\u6001\u4e0d\u662f Finish\uff0c\u5982 Scoring / Running / Error\uff0c\u53ef\u4ee5\u70b9\u51fb\u5f53\u524d\u63d0\u4ea4\u5bf9\u5e94\u7684\u72b6\u6001\u680f\u3002

    Download \u4e2d\u53ef\u4ee5\u4e0b\u8f7d\u5230\u7684\u5185\u5bb9\u4e0e logs \u4e2d\u80fd\u8f93\u51fa\u7684\u5185\u5bb9\u76f8\u4f3c\uff0c\u76f4\u63a5\u67e5\u770b logs \u5373\u53ef\u3002

    terminal \u7684\u5de6\u4fa7\u5206\u4e3a prediction \u548c scoring \u4e24\u79cd\uff0c\u5f53\u6709 ingestion program \u65f6\u7b2c\u4e00\u4e2a terminal \u624d\u4f1a\u6709\u8f93\u51fa\u3002stdout \u548c stderr \u5c06 terminal \u8f93\u51fa\u5206\u5f00\u4e86\uff0cstdout \u662f\u7a0b\u5e8f\u6307\u5b9a\u7684\u6b63\u5e38\u8f93\u51fa\uff0cstderr \u662f error \u8f93\u51fa\uff0c\u6709\u65f6\u5019\u4f1a\u5b58\u5728\u5176\u4e2d\u4e00\u4e2a\u6ca1\u6709\u8f93\u51fa\u7684\u60c5\u51b5\uff0c\u53ef\u5207\u6362\u67e5\u770b\u3002

    Leaderboard \u7684\u7ed3\u679c\u4e0d\u4f1a\u81ea\u52a8\u66f4\u65b0\u5230 Leaderboard\uff0c\u9700\u8981\u7528\u6237\u540c\u610f\u3002\u70b9\u51fb\u8fd0\u884c\u7ed3\u679c\u53f3\u4fa7\u7684\u6309\u94ae\u66f4\u65b0\u5230 Leaderboard\u3002

    "},{"location":"docs/3-dl/tools/codabench/#_8","title":"\u53c2\u8003\u8d44\u6599","text":"

    \u73b0\u6709\u5b98\u7f51\u53c2\u8003\u8d44\u6599\u4f3c\u4e4e\u90fd\u4e0d\u592a\u5168\u9762\uff0c\u4e0d\u80fd\u8986\u76d6\u5404\u79cd\u5e38\u89c1\u9519\u8bef\uff0c\u56e0\u6b64\u4e00\u4e9b\u521b\u5efa\u6b65\u9aa4\u548c\u884c\u4e3a\u662f\u901a\u8fc7\u6d4b\u8bd5\u548c\u63a8\u6d4b\u5f97\u77e5\u7684\u3002\u5982\u679c\u672c\u6587\u6709\u8bef\uff0c\u6b22\u8fce\u8054\u7cfb\u4f5c\u8005\u6539\u6b63\uff01

    "},{"location":"docs/3-dl/tools/nlp_resources/","title":"DL & NLP Resources","text":"

    :material-circle-edit-outline: \u7ea6 213 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u8fd9\u4e2a\u9875\u9762\u7528\u6765\u6536\u96c6 nlp \u5165\u95e8\u8d44\u6599\u7684 minimal closure\uff08\u6307\u8db3\u591f\u5b66\u4f1a\u7684\u6700\u5c0f\u8d44\u6e90\u96c6\u5408\uff09

    "},{"location":"docs/3-dl/tools/nlp_resources/#machine-learning-theory","title":"Machine Learning Theory","text":"

    Google\u7684\u4e00\u4e2a\u6559\u7a0b\uff0c\u91cc\u9762\u7684playground\u505a\u5f97\u6bd4\u8f83\u76f4\u89c2\uff0c\u65e0\u9700\u4ee3\u7801

    Machine Learning \u00a0|\u00a0 Google for Developers

    "},{"location":"docs/3-dl/tools/nlp_resources/#machine-learning-technology","title":"Machine Learning Technology","text":"

    TODO

    "},{"location":"docs/3-dl/tools/nlp_resources/#deep-learning-theory","title":"Deep Learning Theory","text":"

    TODO

    "},{"location":"docs/3-dl/tools/nlp_resources/#deep-learning-technology","title":"Deep Learning Technology","text":"

    Pytorch\u6559\u7a0b\uff0c\u53ef\u4ee5\u770b\u7740\u4ee3\u7801\u624b\u6284\u4e00\u4e0b

    Welcome to PyTorch Tutorials \u2014 PyTorch Tutorials 2.0.1+cu117 documentation

    numpy: numpy 100 exercise

    rougier/numpy-100: 100 numpy exercises (with solutions) (github.com)

    Pytorch

    PyTorch\u6df1\u5ea6\u5b66\u4e60\u5feb\u901f\u5165\u95e8\u6559\u7a0b\uff08\u7edd\u5bf9\u901a\u4fd7\u6613\u61c2\uff01\uff09\u3010\u5c0f\u571f\u5806\u3011_\u54d4\u54e9\u54d4\u54e9_bilibili

    Attention-based Models and Transformer

    Let's build GPT: from scratch, in code, spelled out. - YouTube

    "},{"location":"docs/3-dl/tools/nlp_resources/#natural-language-processing-theory","title":"Natural Language Processing Theory","text":"

    Stanford CS224N: NLP with Deep Learning | Winter 2021 | Lecture 1 - Intro & Word Vectors - YouTube

    "},{"location":"docs/3-dl/tools/nlp_resources/#natural-language-processing-technology","title":"Natural language processing technology","text":"

    Stanford CS 224N | Natural Language Processing with Deep Learning

    "},{"location":"docs/3-dl/tools/nlp_resources/#reinforcement-learning","title":"Reinforcement Learning","text":"

    \u8611\u83c7\u4e66EasyRL (datawhalechina.github.io)

    Codes:

    boyu-ai/Hands-on-RL: https://hrl.boyuai.com/ (github.com) datawhalechina/easy-rl: \u5f3a\u5316\u5b66\u4e60\u4e2d\u6587\u6559\u7a0b\uff08\u8611\u83c7\u4e66\uff09\uff0c\u5728\u7ebf\u9605\u8bfb\u5730\u5740\uff1ahttps://datawhalechina.github.io/easy-rl/

    "},{"location":"docs/3-dl/tools/nlp_resources/#computer-vision","title":"Computer Vision","text":"

    Computer Vision | Universit\u00e4t T\u00fcbingen (uni-tuebingen.de)

    "},{"location":"docs/4-opinion/","title":"Opinions","text":"

    :material-circle-edit-outline: \u7ea6 1 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/plan/","title":"Academic Plans \u5b66\u4e1a\u89c4\u5212","text":"

    :material-circle-edit-outline: \u7ea6 27 \u4e2a\u5b57

    !!! \u672c\u7ae0\u8282 bullshits \u548c exaggerations \u542b\u91cf 200%\uff0c\u76f8\u4fe1\u524d\u4e00\u5b9a\u8c28\u614e\u8c28\u614e\u518d\u8c28\u614e

    "},{"location":"docs/4-opinion/plan/24fall/","title":"24fall \u7533\u8bf7\u8bb0\u5f55","text":"

    :material-circle-edit-outline: \u7ea6 5341 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 18 \u5206\u949f

    \u5199\u4e8e 2024 \u5e74 3 \u6708\u5e95\uff0c\u7ed3\u679c\u5dee\u4e0d\u591a\u51fa\u4e86\uff0c\u6839\u636e\u7ed3\u679c\u53cd\u601d\u4e0b\u5728\u7533\u8bf7\u8def\u7a0b\u4e2d\u505a\u5f97\u5bf9\u4e0e\u4e0d\u5bf9\u7684\u5730\u65b9\uff0c\u5e76\u603b\u7ed3\u4e00\u4e9b\u6709\u7528\u8d44\u6e90\uff0c\u5e0c\u671b\u53ef\u4ee5\u5e2e\u5230\u548c\u6211\u4e00\u6837\u7eaf DIY \u7533\u8bf7\u7684\u540c\u5b66\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#master","title":"master \u9009\u6821","text":"

    master \u9009\u9879\u76ee\u4e3b\u8981\u7ecf\u5386\u4e86\u201c\u6dfb\u52a0\u5fc3\u613f\u5355\u201d+\u201c\u7b5b\u9009\u201d\u4e24\u4e2a\u6d41\u7a0b\u3002

    \u201c\u6dfb\u52a0\u5fc3\u613f\u5355\u201d\u4e00\u6b65\u4e3b\u8981\u53c2\u7167 zju \u5185\u90e8\u7684\u98de\u8dc3\u624b\u518c + OpenCSApp + GlobalCS + \u5370\u8c61\uff08e.g. \u5b66\u957f\u5b66\u59d0\uff0c1p3a\uff09\u7b49\uff0c\u5148\u5217\u51fa\u5927\u7ea6\u4e09\u4e94\u5341\u4e2a\u5408\u9002\u7684\u9879\u76ee\u3002

    \u201c\u7b5b\u9009\u201d\u4e00\u6b65\u4e2d\u518d\u8003\u8651\u5404\u79cd\u9650\u5236\u6761\u4ef6\uff08\u6bd4\u5982\u6211\u7684\uff1a\u5b66\u8d39\u9ad8/\u5c31\u4e1a\u5bfc\u5411\u7684/\u4e0d\u5b89\u5168\u7684/\u5f3a\u5236\u8bed\u8a00\u7684\u4e0d\u7533\uff09\uff0c\u4ee5\u53ca\u6240\u6709\u7533\u5230\u4e5f\u4e0d\u60f3\u53bb\u7684\u90a3\u79cd\u4fdd\u5e95\u9879\u76ee\u4e5f\u65e0\u9700\u7533\u8bf7\u3002 \u5b66\u8d39\u53ef\u4ee5\u53c2\u7167\u7684\u8d44\u6599\u6bd4\u5982 Compare cost of living between cities \u548c\u5404\u4e2a\u9879\u76ee\u5b98\u65b9\u62a5\u7684\u6570\u76ee\u3002

    \u53e6\u5916\u5728 UCSD CS37 \u7684\u9879\u76ee\u9875\u9762\u770b\u8fc7\u201c\u5982\u679c\u786e\u5b9a\u7533\u8bf7 PhD\uff0c\u5c31\u4e0d\u8981\u7533\u8bf7 master \u4e86\u201d\uff0c\u53ef\u80fd\u80fd\u4ee3\u8868\u4e00\u90e8\u5206\u5b66\u6821\u8fd9\u4e24\u79cd\u9879\u76ee\u7684\u5b9a\u4f4d\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#phd","title":"PhD \u9009\u5bfc","text":"

    \u6211\u9996\u5148\u9760\u8ddf\u7ec4\u91cc\u540c\u884c\u8ba4\u8bc6\u7684\u5b66\u957f\u5b66\u59d0\u4ea4\u6d41\uff0c\u88ab\u63a8\u8350\u4e86\u4e00\u4e9b\u5f53\u5e74\u6b63\u5728\u62db\u751f\u7684\u4f18\u79c0 prof\u3002\u6b64\u5916\u81ea\u5df1\u4e3b\u8981\u53c2\u8003\u4e86 CSrankings\uff0c\u6328\u4e2a\u6253\u5f00 Google Scholar \u53bb\u8bfb\u6587\u7ae0\u3002\u4e5f\u6709\u53d1\u6325\u6211\u7684\u793e\u725b\u5c5e\u6027\u53bb X(twitter) \u4e0a\u628a\u5927\u5bb6\u90fd\u5173\u6ce8\u7136\u540e\u5237\u6587\u7ae0\u8fd9\u6837\u505a\u3002\u7ecf\u5e38\u5237 Arxiv \u4e5f\u662f\u597d\u4e60\u60ef\uff0c\u53ef\u60dc\u6211\u8fd8\u6ca1\u517b\u6210\u3002\u8fd9\u4e9b\u90fd\u6709\u5229\u4e8e\u773c\u719f\u6559\u6388\uff0c\u4e00\u6bb5\u65f6\u95f4\u540e\u5c31\u53ef\u5f62\u6210\u81ea\u5df1\u7684\u9009\u62e9\u3002

    \u53e6\u5916\u9009\u5b66\u6821\u65f6\u5982\u9700\u53c2\u8003 Stipend\uff1aCSStipendRankings\u3002

    \u6700\u7ec8 master + PhD \u6211\u4e00\u5171\u7533\u8bf7\u4e86\u4f3c\u4e4e\u662f 14 \u4e2a\uff08\u542b 3 \u4e2a\u514d\u8d39\uff09\u3002\u8fd9\u4e2a\u6570\u76ee\u56e0\u4eba\u800c\u5f02\uff0c\u4e3b\u8981\u770b\u4e0e\u63a8\u8350\u4eba\u6c9f\u901a\u3002\u8eab\u8fb9\u4e5f\u6709\u670b\u53cb\u7533\u5230 50 \u4e2a\u7684\uff0c\u60ca\u4eba\u4f46\u662f\u5c0a\u91cd\u7406\u89e3\u3002

    \u6700\u65b0\u5728 24fall \u7fa4\u91cc\u770b\u5230\u7684\u9009\u5bfc\u5e08\u7684\u5176\u5b83\u5de5\u5177

    "},{"location":"docs/4-opinion/plan/24fall/#_1","title":"\u8bed\u8a00\u6210\u7ee9","text":"

    \u5982\u679c\u7533\u8bf7 PhD\uff0c\u90a3\u4e48\u5927\u5bb6\u7684\u7ecf\u9a8c\u6765\u770b\u8fc7\u7ebf\u5c31\u591f\uff0c\u4e0d\u592a\u4f1a\u4e25\u5361\uff0c\u91cd\u70b9\u65e0\u9700\u5728\u8bed\u8a00\u6210\u7ee9\u3002

    master \u5219\u5e94\u8be5\u662f\u8bed\u8a00\u6210\u7ee9\u8d8a\u9ad8\u8d8a\u597d\u4e86\uff0c\u5c24\u5176\u5982\u679c\u7ee9\u70b9 below average\uff0c\u90a3\u4e48\u8bed\u8a00\u786e\u5b9e\u9700\u8981\u8003\u9ad8\u4e00\u4e9b\u3002

    \u4ee5\u53ca\u6211\u5728\u7533\u8bf7\u5b63\u7684\u51e0\u4e2a\u6708\u91cc\u4e00\u76f4\u6ca1\u80fd\u6253\u5f00 GRE \u7684\u5b98\u7f51\uff08\u4e0d\u662f\u5bc6\u7801\u4e0d\u6b63\u786e\uff0c\u5bc6\u7801\u901a\u8fc7\u53d1\u90ae\u4ef6\u5c31\u80fd\u627e\u56de\u6765\u4e86\uff0c\u662f\u767b\u5f55\u540e\u8df3\u8f6c\u53ea\u80fd\u5230 error \u9875\u9762\uff09\uff0c\u6362\u7f51\u6362\u8bbe\u5907\u6362\ud83e\ude9c\u90fd\u8fd8\u662f\u4e00\u76f4\u5237\u65b0\u4e0d\u51fa\u6765\uff0c\u5bfc\u81f4\u8003\u4e86\u4e5f\u6ca1\u6cd5\u67e5\u5206\uff0c\u6ca1\u6cd5\u591a\u6dfb\u52a0\u9001\u5206\u3002\u56e0\u4e3a\u4e3b\u8981\u76ee\u6807\u8fd8\u662f\u7533 PhD \u4e8e\u662f\u6700\u540e\u5c31\u4e0d\u518d\u6323\u624e\u4e86\u3002GRE \u5b98\u7f51\u662f\u7ecf\u5e38\u62bd\u98ce\u7684\uff0c\u770b\u5230\u8eab\u8fb9\u4e00\u4e9b master \u7533\u8bf7\u8005\u4f1a\u9009\u62e9\u5728\u5927\u4e09\u5c31\u628a GRE \u8003\u51fa\u6765\uff0c\u5efa\u8bae\u4e5f\u50cf\u4ed6\u4eec\u4e00\u6837\u63d0\u524d\u51c6\u5907\uff0c\u5982\u679c\u4e5f\u767b\u9646\u4e0d\u8fdb\u53bb\uff0c\u591a\u6c42\u52a9\u6c42\u52a9\u8eab\u8fb9\u7684\u4eba\u501f\u8bbe\u5907\u8bd5\u8bd5\uff0c\u6700\u597d\u63d0\u524d\u51c6\u5907\uff0c\u907f\u514d\u5230\u7533\u8bf7\u5b63\u53d1\u73b0\u5f71\u54cd\u9001\u5206\u3002

    \u9001\u5206 Code \u8fd8\u6709\u4e00\u4e9b\u5e16\u5b50\u603b\u7ed3\u8fc7\u7684\uff08\u53ef\u81ea\u884c\u641c\u7d22\uff09\uff0cTG \u90fd\u662f\u7528\u7684\u662f\u540c\u4e00\u4e2a\u9001\u5206 Code\uff0c\u4ee5\u53ca GRE \u5728\u8003\u573a\u91cc\u90a3\u6b21\u514d\u8d39\u9001\u5206\u673a\u4f1a\u4e0d\u7528\u80cc\u9001\u5206 Code\uff0c\u5728\u8003\u573a\u91cc\u4e5f\u53ef\u4ee5\u6309\u6821\u540d\u641c\u7d22\u6dfb\u52a0\u7684\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_2","title":"\u63a8\u8350\u4fe1","text":"

    \u63a8\u8350\u4fe1\u5982\u4f55\u88ab\u5ba1\u6838\uff1a\u636e\u8bf4\u4e00\u822c\u5728\u62db\u751f\u5b98\u624b\u91cc\uff0c\u63a8\u8350\u4fe1\u662f\u4e0e\u7533\u8bf7\u8005\u7684\u5176\u5b83\u6750\u6599\u4e00\u8d77\u62fc\u6210\u4e00\u957f\u4efd\u591a\u9875 PDF \u4e00\u8d77\u88ab\u5ba1\u6838\u7684\uff0c\u51e0\u4efd\u63a8\u8350\u4fe1\u524d\u540e\u5e76\u5217\u3002\u6240\u4ee5\u5173\u4e8e\u201c\u98ce\u683c\u660e\u663e\u4e0d\u660e\u663e\u201d\u201c\u5f3a\u5ea6\u660e\u663e\u4e0d\u660e\u663e\u201d\u201c\u4f1a\u5ba1\u6587\u4ef6\u4fe1\u606f\u201d\u7b49\u95ee\u9898\u53ef\u4ee5\u60f3\u8c61\u4e00\u4e0b\u5ba1\u6750\u6599\u7684\u8fd9\u4e2a\u573a\u666f\uff0c\u4ece\u8fd9\u4e2a\u89d2\u5ea6\u6765\u8003\u8651\u3002

    \u5173\u4e8e\u627e\u591a\u4f4d\u63a8\u8350\u4eba\uff1a\u5927\u7ea6 12.2 \u53f7\u770b\u5230 PhD \u7533\u8bf7\u7fa4\u91cc\u6709\u4eba\u8bf4\uff0c\u5176\u5b9e\u4e0d\u8981\u627e 3 \u4e2a\u63a8\u8350\u4eba\u5c31\u7ed3\u675f\uff0c\u6700\u597d\u63d0\u524d\u627e 4 \u5230 5 \u4e2a\uff0c\u56e0\u4e3a\u591a\u4ea4\u6ca1\u6709\u5173\u7cfb\uff0c\u5927\u90e8\u5206\u5b66\u6821\u90fd\u6709\u6dfb\u52a0\u591a\u4e2a\u63a8\u8350\u4eba\u7684\u9009\u9879\uff08\u6211\u7684\u9009\u6821\u91cc\u53ea\u6709loo\u548cumich\u4e0a\u9650\u4e09\u4e2a\uff09\uff0c\u4f46\u662f\u7ecf\u5e38\u6709\u63a8\u8350\u4eba\u5fd9\u5fd8\u4e86\u6700\u540e\u6ca1\u4ea4\u7684\u60c5\u51b5\u3002\u518d\u95ee\u53e6\u4e00\u4e2a\u7fa4\uff0c\u5f97\u77e5\u5982\u679c\u662f US PhD\uff0c\u4e0d\u4f1a\u56e0\u4e3a\u6709\u4e00\u4e2a\u63a8\u8350\u4eba\u5fd8\u4e86\u4ea4\u62d2\u4f60\uff0c\u4f46\u662f\u5927\u591a master 3 \u5c01\u4ea4\u4e0d\u9f50\u5c31\u65e0\u6cd5\u5f00\u59cb\u5ba1\u6750\u6599\uff0c\u53ef\u80fd\u56e0\u6b64\u4e00\u76f4\u7559\u5728\u6c60\u5b50\u91cc\uff0c\u6216\u8005\u53ef\u80fd\u56e0\u6b64\u9ed8\u62d2\u3002\u4e5f\u6709\u542c\u8bf4\u5982\u679c\u672c\u8be5\u4ea4 3 \u5c01\u4ea4\u4e86 4 \u5c01\uff0c\u53ef\u80fd\u56e0\u6b64\u964d\u4f4e\u5176\u4e2d\u6700\u91cd\u8981\u7684\u90a3\u5c01\u7684\u6548\u529b\uff0c\u8fd9\u70b9\u5982\u679c\u6536\u5230 >3 \u5c01\u63a8\u8350\u4fe1\u5176\u5b9e\u53ef\u4ee5\u901a\u8fc7 exclude \u4e00\u4efd\u6765\u89e3\u51b3\uff0c\u7ecf\u9a8c\u6765\u770b\u70b9 exclude \u65f6\u63a8\u8350\u4eba\u5e94\u8be5\u4e0d\u4f1a\u6536\u5230\u901a\u77e5\u3002

    \u540c\u4e00\u5b66\u6821\u53ef\u4ee5\u5171\u7528\u63a8\u8350\u4fe1\u5417: \u4e00\u822c\u4e0d\u80fd\u3002\u6211\u7533\u8bf7\u7684\u5b66\u6821\u4e2d\u53ef\u4ee5\u7684\u6709

    \u63a8\u8350\u4fe1\u7cfb\u7edf\u4e0d\u5927\u667a\u80fd\u7684\u5730\u65b9:

    \u542c\u8bf4\u8fc7\u67e5 IP/MAC \u5730\u5740\u7684: \u76ee\u524d\u5927\u8305\u548c\u54e5\u5927\u6709\u89c1\u8fc7 DP \u6536\u5230\u5b66\u6821\u90ae\u4ef6\u8bf4\u67e5\u5230\u4fe1\u662f\u81ea\u5df1\u53d1\u7684\u3002\u636e\u6b64\u770b\u6765\u662f\u4e0d\u662f\u85e4\u6821\u4e25\u4e00\u4e9b\u3002IP/MAC addr \u5982\u679c\u67e5\u5e94\u8be5\u662f\u989d\u5916\u67e5\u7684\uff0c\u4e0d\u662f\u5ba1\u6750\u6599\u7684\u62db\u751f\u5b98\u8d1f\u8d23\u67e5\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_3","title":"\u5957\u74f7","text":"

    \u4e00\u5f00\u59cb\u770b\u5230\u7684\u6d88\u606f\u662f\u5957\u5230\u74f7\u624d\u80fd\u7533\u8bf7\uff0c\u540e\u6765\u770b\u5230 n+e's blog \u77e5\u9053\u4e5f\u4e0d\u4e00\u5b9a\uff0c\u5148\u6295\u4e86\u518d\u5957\u4e5f\u53ef\u4ee5\uff0c\u6709\u4e9b\u6559\u6388\u7279\u522b\u5fd9\uff0c\u53ef\u80fd\u62c5\u5fc3\u6709\u4e9b\u5b66\u751f\u804a\u4e86\u4e5f\u6ca1\u6295\uff0c\u53ef\u80fd\u503e\u5411\u5b66\u751f\u786e\u5b9e\u6295\u4e86\u518d\u804a\uff0c\u6216\u8005\u7b49\u5230\u4ed6\u4eec\u81ea\u5df1\u4ece\u6c60\u5b50\u91cc\u635e\u4eba\u7684\u65f6\u95f4\u7ebf\u518d\u804a\u3002\u4e5f\u53ef\u4ee5\u53c2\u8003\u5f3a prof \u548c\u5f3a committee \u5b66\u6821\u7684\u4e00\u4e9b\u540d\u5355\uff08\u76ee\u524d\u770b\u5230\u4e00\u4e2a CS PhD\u5f3acommittee&\u5f3aprofessor List(\u4ec5\u4f9b\u53c2\u8003) \u4e0d\u8fc7\u4e0d\u4e00\u5b9a\u5f88\u51c6\uff0c\u5370\u8c61\u4e2d\u91cc\u9762\u8bf4\u662f\u5f3a committee \u7684\u4e00\u4e9b\u4e5f\u6709\u4e0e prof \u804a\u597d\u5c31\u5f55\u4e86\u7684 DP\uff09\u3002

    double \u7684\u7fa4\u91cc\u8fd8\u6709\u4e2a\u670b\u53cb\u505a\u4e86\u4e2a\u533f\u540d google docs \u4f9b\u7fa4\u53cb\u5206\u4eab\u62ff\u5230\u9762\u8bd5\u7684\u5927\u81f4\u65f6\u95f4\u6bb5\uff0c\u5171\u4eab\u5404\u5b66\u6821\u9762\u8bd5\u53d1\u5230\u4ec0\u4e48\u8fdb\u5ea6\u4e86\uff0c\u53ef\u60dc\u8be5\u8868\u683c\u4e0d\u5e0c\u671b\u88ab\u5916\u4f20\u3002\u4ee5\u540e\u7684\u7533\u8bf7\u7fa4\u91cc\u5927\u5bb6\u4e5f\u53ef\u4ee5\u81ea\u53d1\u521b\u5efa\u4e00\u4e2a\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_4","title":"\u7f51\u7533","text":"

    \u5bfb\u627e\u7f51\u7533\u9875\u9762\u7684\u901a\u7528\u505a\u6cd5\u4e00\u822c\u662f\u641c\u7d22\u5f15\u64ce\u641c\u7d22 \u5b66\u6821\u548c program \u540d\u5b57 + application\uff0c\u7ed3\u679c\u524d\u51e0\u6761\u4e2d\u4e00\u822c\u5c31\u542b\u6b63\u786e\u7684\u7533\u8bf7\u754c\u9762\u3002\u7f51\u7533\u5185\u5bb9\u611f\u89c9\u8fd8\u662f\u9700\u8981\u81ea\u5df1\u586b\uff0c\u4e0d\u8981\u627e\u4ee3\u586b\uff0c\u4fe1\u606f\u5f88\u591a\uff0c\u975e\u672c\u4eba\u4e0d\u719f\u6089\u592a\u5bb9\u6613\u586b\u9519\u4e86\u3002

    \u4e0b\u9762\u8bb0\u5f55\u4e00\u4e9b program-specific \u7684\u5751\u70b9\u3002

    CMU: \u5982\u679c\u76f4\u63a5\u641c\u7d22 MLT application \u51fa\u73b0\u7684\u4ee5\u4e0b\u9875\u9762\u53ca\u7533\u8bf7\u94fe\u63a5\u662f\u627e\u4e0d\u5230MLT\u9879\u76ee\u7684

    Application Management (cmu.edu) \u8fd9\u4e2a\u9875\u9762\u548c\u4ee5\u4e0b\u622a\u56fe\u662f\u6b63\u786e\u7684\uff0c\u540c\u7406mscv\u548cmsaii\u4ec0\u4e48\u7684\u9879\u76ee\u4e5f\u5728\u8fd9\u91cc\u7533\u8bf7\u3002

    mscs \u7684 video essay \u662f\u63d0\u524d\u5f55\u597d\u4e86\u4e0a\u4f20\u5230 youtube \u8fd9\u79cd\u7684\uff0c\u53ef\u4ee5\u81ea\u5df1\u968f\u610f\u5f55\u591a\u6b21\uff0c\u4f46\u6211\u4f30\u8ba1\u4e0d\u8981\u62fc\u63a5\u75d5\u8ff9\u592a\u91cd\uff0c\u4e00\u53e3\u6c14\u8bf4\u4e0b\u6765\u6700\u597d\u3002\u5185\u5bb9\u6211\u8bb0\u5f97\u6ca1\u6709\u9650\u5236\uff0c\u968f\u610f\u8bbe\u8ba1\u81ea\u6211\u4ecb\u7ecd\uff0c\u636e\u8bf4\u4e3b\u8981\u662f\u4e3a\u4e86\u770b\u7533\u8bf7\u4eba\u6027\u683c\u3001\u53e3\u8bed\u3001\u8868\u8fbe\u80fd\u529b\u4e4b\u7c7b\u7684\u6f5c\u5728\u7279\u70b9\u3002

    \u5728\u7ec6\u5206\u7684\u90a3\u51e0\u4e2a ai \u9879\u76ee\u7684 video earry \u662f\u9650 3 \u6b21\u673a\u4f1a\uff0c\u6bcf\u6b21\u968f\u673a\u95ee\u9898\uff0c\u9650\u65f6\u51c6\u5907\uff0c\u9650\u65f6\u8bf4\u3002\u6211\u770b\u5230\u7684\u7f51\u4e0a\u7684\u5e16\u5b50\u8bf4\u597d\u50cf miis ini ece\uff08\u8bb0\u4e0d\u4f4f\u8fd9\u51e0\u4e2a\u9879\u76ee\u540d\u5b57\uff0c\u603b\u4e4b\u7c7b\u4f3c\uff09\u662f 30s \u51c6\u5907\uff0c180s \u8bf4\uff0c\u95ee\u7684\u95ee\u9898\u5927\u7c7b\u6709\uff1a\u4f60\u961f\u53cb\u600e\u4e48\u8bc4\u4ef7\u4f60\uff0c\u4f60\u6536\u5230\u7684\u961f\u53cb\u7684\u4e00\u6761\u8d1f\u9762\u8bc4\u4ef7\u662f\uff0c\u4f60\u600e\u4e48\u9886\u5bfc project\uff0c\u4e00\u4e2a\u6210\u529f\u7684 project \u5bf9\u4f60\u6765\u8bf4\u662f\u600e\u6837\u7684\uff0c\u4f60\u559c\u6b22\u4ec0\u4e48\u6c9f\u901a\u6a21\u5f0f\uff0c\u5bf9\u4f60\u6765\u8bf4\u4ec0\u4e48\u662f\u5f88\u96be\u505a\u7684\u51b3\u5b9a\uff0c\u4f60\u9047\u5230\u632b\u6298\u4e86\u4f1a\u600e\u4e48\u6837...\u8fd9\u79cd\u5f88\u8ddf course project \u548c\u5408\u4f5c\u6709\u5173\u7684\u3002

    \u4f46\u662f\u6211\u5728 mlt \u91cc\u6253\u5f00\u9047\u5230\u7684\u662f 10s \u51c6\u5907\uff0c210s \u8bf4\uff0c\u9047\u5230\u7684\u4e24\u4e2a\u95ee\u9898\u4f9b\u53c2\u8003:

    \u8fd9\u6837\u5f88\u7814\u7a76\u5bfc\u5411\u7684\u95ee\u9898\uff0c\u4e00\u822c\u90fd\u6765\u81ea SoP\u3002

    UWaterloo: \u7533\u8bf7\u5206\u4e3a\u4e24\u4e2a\u9636\u6bb5\uff0c\u7b2c\u4e00\u4e2a\u9636\u6bb5\u91cc\u4ea4\u6389\u624d\u80fd\u5728\u7b2c\u4e8c\u4e2a\u9636\u6bb5\u4e0a\u4f20 cv \u6587\u4e66 \u8bed\u8a00\u6210\u7ee9\u7b49\u4e1c\u897f\uff0c\u7b2c\u4e8c\u9636\u6bb5\u7684\u94fe\u63a5\u4f1a\u5728\u7b2c\u4e00\u9636\u6bb5\u540e 2-4 \u5929\u6536\u5230\u3002\u7533\u8bf7\u8d39\u5728\u7b2c\u4e00\u9636\u6bb5\u4ea4\u3002\u63a8\u8350\u4eba\u5728\u7b2c\u4e00\u9636\u6bb5\u6dfb\u52a0\uff0c\u90ae\u4ef6\u968f\u7740\u7b2c\u4e00\u9636\u6bb5\u63d0\u4ea4\u88ab\u53d1\u51fa\u3002\u7b2c\u4e00\u4e2a\u9636\u6bb5\u4e00\u5b9a\u8981\u6bd4 ddl \u63d0\u524d\u4e24\u4e09\u5929\u4ea4\u3002\u4e14 loo \u7684\u7cfb\u7edf\u597d\u50cf\u7ef4\u62a4\u6bd4\u8f83\u9891\u7e41\uff0c\u53ef\u4ee5\u591a\u9884\u7559\u4e00\u4e9b\u65f6\u95f4\u3002

    UT-Austin: \u540c\u7533\u8bf7\u5206\u4e3a\u4e24\u4e2a\u9636\u6bb5\uff0c\u7b2c\u4e00\u4e2a\u9636\u6bb5\u4ed8\u6b3e\uff0c\u5ba1\u6838 1-3 \u5929\u540e\u624d\u80fd\u5f00\u59cb\u7b2c\u4e8c\u4e2a\u9636\u6bb5\uff08\u542b\u6dfb\u52a0\u63a8\u8350\u4eba\u7b49\uff09\u3002\u7b2c\u4e00\u9636\u6bb5\u63d0\u4ea4\u4e00\u5b9a\u8981\u6bd4 ddl \u65e9\u4e24\u4e09\u5929\u3002

    Umich\uff1a\u7f51\u7533\u7cfb\u7edf\u4e00\u5f00\u59cb\u56db\u4e94\u4e2a\u9875\u9762\u8981\u987a\u5e8f\u586b\u5b8c\uff08\u5305\u62ec\u6dfb\u52a0\u63a8\u8350\u4eba\u7684\u90e8\u5206\uff09\uff0c\u540e\u9762\u7684\u9875\u9762\u624d\u80fd\u8df3\u7740\u586b\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_5","title":"\u6587\u4e66","text":"

    \u6211\u5199\u6587\u4e66\u4e3b\u8981\u53c2\u7167\u7684\u8d44\u6599\u6709 CS-SOP, CMU sop guideline, \u548c\u4e24\u4e09\u4f4d\u5b66\u957f\u5b66\u59d0\u548c peer \u7684\u4fee\u6539\u610f\u89c1\u3002

    CV \u6211\u8ba4\u4e3a\u4e00\u822c\u5927\u5bb6\u505a\u51fa\u6765\u7684\u90fd\u6ca1\u95ee\u9898\uff0c\u5c11\u91cf\u503c\u5f97 comment \u7684\u4e00\u4e9b\u70b9\u6709\uff1a

    SOP

    SOP \u53ef\u4ee5\u7406\u89e3\u4e3a\u5173\u4e8e\u81ea\u5df1\u5b66\u672f\u7ecf\u5386\u548c\u8ba1\u5212\u7684\u4e00\u4efd\u6587\u4e66\u3002\u7ecf\u9a8c\u6765\u770b\u5982\u679c\u4e00\u4e9b\u5b66\u6821\u53ea\u8981\u6c42 PS \u4e0d\u8981\u6c42 SOP\uff0c\u90a3\u4e48 PS \u5e94\u5f53\u5f53\u4f5c\u4e00\u4e2a\u683c\u5f0f\u4e0d\u90a3\u4e48\u4e25\u683c\u7684 SOP \u6765\u5199\u3002

    \u6240\u6709\u9879\u76ee\u7684\u6587\u4e66\u52a0\u8d77\u6765\u5927\u7ea6\u751f\u4ea7\u4e86\u8fd1 20 \u4efd\uff0c\u5176\u4e2d\u5982\u679c\u5185\u5bb9\u76f8\u4f3c\u7684\u5408\u5e76\u4e3a\u540c\u4e00\u4efd\uff0c\u90a3\u5927\u6982\u4e5f\u6709\u516d\u4e03\u4efd\u5b8c\u5168\u4e0d\u540c\u7684\u3002\u4e00\u4e2a\u6709\u70b9\u7384\u5b66\u7684\u611f\u89c9\u662f\u6211\u4e13\u95e8\u4e3a\u5176\u5199\u4e86\u4e00\u4efd\u65b0\u6587\u4e66\u7684\u9879\u76ee\uff0cPhD \u5bfc\u5e08\u5c31\u53d1\u4e86\u9762\u8bd5\uff0cmaster \u5c31\u53d1\u4e86 offer\uff0c\u800c\u4ece\u522b\u7684\u9879\u76ee\u6539\u6539\u800c\u6765\u7684\u90a3\u4e9b\u4e00\u5b9a\u6ca1\u6709\u53d1\u9762\u8bd5/\u62ff offer\u3002\u6709\u53ef\u80fd\u56e0\u679c\u5173\u7cfb\u6709\u201c\u6211\u611f\u89c9\u4e0d\u4f1a\u4e2d/\u4e0d\u662f\u7279\u522b\u5408\u9002\u201d -> \u201c\u56e0\u6b64\u66f4\u52a0\u6ca1\u6709\u8ba4\u771f\u51c6\u5907\u6587\u4e66\u201d -> \u201c\u56e0\u6b64\u5f53\u7136\u62ff\u4e0d\u5230\u201d\u8fd9\u4e00\u5c42\u3002

    \u4e00\u822c\u662f\u81ea\u5df1\u62df\u597d\u8349\u7a3f\u540e\u4ea4\u7ed9\u5b66\u957f\u5b66\u59d0\u6216 peer \u6765\u6539\uff0c\u540e\u6765\u8d76 ddl \u5927\u5bb6\u90fd\u6bd4\u8f83\u5fd9\uff0c\u6709\u4e9b\u5c31\u81ea\u5df1\u5199\u597d\u76f4\u63a5\u4ea4\u4e86\u3002\u5012\u662f\u89c9\u5f97\u81ea\u5df1\u5199\u5b8c\u6709\u6ca1\u6709\u627e\u4eba review \u8fd9\u70b9\u5bf9\u7ed3\u679c\u7684\u5f71\u54cd\u6ca1\u6709\u5f88\u5927\uff0cPhD \u5bfc\u5e08\u4eec\u4e5f\u8868\u793a\u770b\u91cd\u7684\u66f4\u591a\u662f\u65b9\u5411 match \u4e0d match\uff0c\u4fe1\u606f\u8868\u8fbe\u6b63\u786e\u5230\u4f4d\u662f\u6700\u91cd\u8981\u7684\uff0c\u8bed\u8a00\u7f8e\u5316\u5012\u5728\u5176\u6b21\u3002\u4e14\u4e00\u4e9b\u5b66\u6821\uff08Waterloo, UW, Uchi\uff09\u6587\u4e66\u4e5f\u4f1a\u9650\u5236 500/1000 words\uff0c\u8fd9\u6837\u77ed\u7684\u9650\u5236\u91cc\u786e\u5b9e\u8868\u8fbe\u4e0d\u4e86\u591a\u5c11\uff0c\u4e5f\u8bf4\u660e\u4f20\u8fbe\u4fe1\u606f\u662f\u7b2c\u4e00\u4f4d\u7684\u3002\u81ea\u5df1\u5199\u4e5f\u6709\u4e00\u5957\u6bd4\u8f83\u9ad8\u6548\u7684\u6d41\u7a0b\uff0c\u7075\u611f\u6765\u6e90\u4e8e\u5927\u4e00\u4e0a EW1 \u7684\u9b54\u9b3c\u5916\u6559\u8001\u5e08\u8bb2\u7684 shitty first draft \u6982\u5ff5\uff1a\u7b2c\u4e00\u7a3f\u96be\u4e0b\u624b\u5e38\u5e38\u662f\u56e0\u4e3a\u60f3\u8981\u540c\u65f6\u517c\u987e\u4fe1\u606f\u548c\u8868\u8fbe\uff0c\u90a3\u4e48\u628a\u4e24\u4ef6\u4e8b\u62c6\u5f00\uff0c\u7b2c\u4e00\u7a3f\u5148\u4e00\u53e3\u6c14\u5199\u51fa\u4e2a\u8868\u8fbe\u4fe1\u606f\u5168\u9762\u6b63\u786e\u4f46\u7528\u8bed\u975e\u5e38 shitty \u7684\u6587\u7ae0\uff0c\u7b2c\u4e8c\u7a3f\u53ea\u987e\u4f18\u5316\u8868\u8fbe\uff0c\u90a3\u5c31\u4e0d\u4f1a\u5361\u58f3\u3002\u6211\u5199\u7684\u6d41\u7a0b\u4e5f\u5927\u81f4\u662f\u8fd9\u6837\uff0c\u5148\u628a\u6240\u6709\u60f3\u8868\u8fbe\u7684\u4fe1\u606f\u5410\u51fa\u6765\uff0c\u5f62\u6210\u4e00\u7bc7\u81f3\u5c11\u957f\u5f97\u50cf\u6587\u7ae0\u7684\u6587\u7ae0\uff08\u4f46\u751a\u81f3\u4e0d\u4f1a\u987e\u53ca\u7528\u4ec0\u4e48\u8bed\uff0c\u7ecf\u5e38\u4e00\u534a\u82f1\u8bed\u4e00\u534a\u4e2d\u6587\uff09\uff0c\u7136\u540e\u4e00\u6bb5\u4e00\u6bb5\u8f93\u5165 ChatGPT \u8bf7\u5b83 \"please refine this paragraph from a {\u6587\u4f53} for me: {paragraph}\"\uff0c\u518d\u4e00\u53e5\u4e00\u53e5\u6bd4\u5bf9 ChatGPT \u8f93\u51fa\u7ed3\u679c\u4e0e\u81ea\u5df1\u7684\u5199\u4f5c\uff0c\u624b\u52a8\u628a\u4e00\u4e2a\u89c9\u5f97\u66f4\u597d\u7684\u7ed3\u679c\u6572\u56de\u5230\u6587\u7ae0\u4e2d\uff08\u8fd9\u91cc\u6211\u4e2a\u4eba\u8ba4\u4e3a\u8fc7\u4e00\u904d\u8111\u5b50\u540e\u4eb2\u81ea\u51b3\u5b9a\u600e\u4e48\u6539\u662f\u6bd4\u76f4\u63a5\u590d\u5236\u66f4\u9ad8\u6548\u66f4\u660e\u667a\u7684\u65b9\u6cd5\uff0c\u56e0\u4e3a ChatGPT \u5bf9\u4e8e\u7533\u8bf7\u6587\u4e66\u7c7b\u7684\u6587\u4f53\u5e38\u5e38\u6709\u4e00\u5957\u7279\u522b\u56fa\u5b9a\u4e14\u5b98\u65b9\u7684\u7528\u8bcd\uff0c\u4f7f\u5176\u4e0d\u592a\u5408\u9002\u4e14\u592a\u5bb9\u6613\u8bc6\u522b\u51fa\u662f\u673a\u5668\u5199\u7684\uff09\u3002\u6700\u540e\u628a\u8fd9\u904d\u81ea\u5df1\u6539\u8fc7\u7684\u5199\u4f5c\u8fc7\u4e00\u904d grammarly \u68c0\u67e5\u8bed\u6cd5\uff0c\u7b80\u5355\u68c0\u67e5\u540e\u5c31\u57fa\u672c\u53ef\u4ee5\u5b9a\u7a3f\u4e86\u3002

    \u6b64\u5916\u8fd8\u6709\u4e00\u70b9\u662f\uff0c\u6211\u4e2a\u4eba\u8ba4\u4e3a\u5728\u5ba1\u6587\u4e66\u65f6\u6bcf\u4efd\u6587\u4e66 5-10 \u5206\u949f\uff0c\u53ef\u80fd\u6240\u6709\u4eba\u80fd\u4e00\u773c\u770b\u5230\u7684\u662f (1) \u5c0f\u6807\u9898 (2) \u52a0\u7c97\u7684\u5173\u952e\u8bcd\uff0c\u6700\u540e\u624d\u4f1a\u7ec6\u770b\u5927\u91cf\u666e\u901a\u6587\u5b57\u3002\u4e00\u4e2a\u4f8b\u5b50\u662f\u6211\u4e0a\u6b21\u53c2\u52a0\u4e00\u95e8\u8bfe\u7684 group tutorial \u65f6\uff0c\u5f53\u65f6\u5c0f\u7ec4\u6210\u5458\u5408\u5199\u4e86\u4e00\u4efd rp\uff0c\u5176\u4e2d\u6211\u5199\u7684\u662f\u6700\u6666\u6da9\u7684 lit review\uff0c\u5373\u4e13\u4e1a\u672f\u8bed\u5bc6\u5ea6\u6700\u9ad8\u8fd8\u53e5\u5b50\u6700\u957f\uff0c\u4f46\u662f\u6211\u7ed9\u6bcf\u4e2a\u5206\u4e3b\u9898\u52a0\u4e86\u5c0f\u6807\u9898\uff0c\u5176\u5b83\u540c\u5b66\u5199\u7684\u90e8\u5206\u6ca1\u6709\u52a0\u3002\u8001\u5e08\u5728\u4e0e\u6211\u4eec\u8c08\u8bdd\u7684\u95f4\u9699\u7784\u4e86\u51e0\u773c\u6211\u4eec\u7684\u6587\u4ef6\uff0c\u77ed\u77ed\u7684\u65f6\u95f4\u91cc\u5c31\u53ea\u770b\u8fdb\u53bb\u4e86 lit review \u7684\u5c0f\u6807\u9898\uff0c\u70b9\u8bc4\u4e86\u4e00\u4e0b\u8fd9\u90e8\u5206\u3002\u56e0\u6b64\u505a\u6e05\u6670\u7684\u5206\u6bb5\u548c\u5c0f\u6807\u9898\u5f88\u91cd\u8981\uff08\u8fd9\u91cc\u771f\u7684\u6709\u70b9\u50cf\u8bbe\u8ba1\u56db\u539f\u5219\uff0c\u5bf9\u6bd4/\u805a\u5408\uff09\uff0c\u5c24\u5176\u662f\u65f6\u95f4\u7cbe\u529b\u4e0d\u591f\u65f6\uff0c\u5176\u4e2d\u7684\u7ec6\u8282\u5185\u5bb9\u8bf4\u4e0d\u5b9a\u4e0d\u7528\u62a0\u592a\u7ec6\uff0c\u53ef\u80fd\u62db\u751f\u5b98\u548c prof \u5728\u77ed\u6682 review \u7684\u65f6\u95f4\u91cc\u6355\u6349\u5230\u7684\u4fe1\u606f\u4e5f\u53ea\u6709\u5c11\u91cf\u6700\u663e\u773c\u7684\u3002\u56e0\u6b64\u6211\u7684\u6bcf\u4efd\u6587\u4e66\u90fd\u505a\u4e86\u52a0\u7c97 \\noindent \u8fd9\u6837\u7684\u5c0f\u6807\u9898\u6765\u5f15\u5bfc\u62db\u751f\u5b98\uff0c\u4e0d\u77e5\u9053\u5408\u4e0d\u5408\u89c4\uff0c\u4f46\u662f\u5e94\u8be5\u4e5f\u6ca1\u6709\u89c4\u77e9\uff0c\u4e14 CS-SOP \u4e0a\u4e0d\u5c11\u6587\u4e66\u4e5f\u662f\u8fd9\u6837\u52a0\u5c0f\u6807\u9898\u5199\u7684\uff0c\u6211\u8ba4\u4e3a\u8fd9\u6837\u6bd4\u8f83\u6709\u5229\u6240\u4ee5\u5c31\u8fd9\u6837\u505a\u597d\u4e86\u3002

    \u9644\u81ea\u5df1\u9605\u8bfb CS-SOP \u540e\u5199\u81ea\u5df1\u7684 SOP \u524d\uff0c\u7ed9\u81ea\u5df1\u5199\u7684\u7ed3\u6784\u6307\u5bfc

    \u6211\u5728\u5199\u6587\u4e66\u4e4b\u524d\uff0c\u4e00\u76f4\u8ba4\u4e3a\u6211\u7684\u8fc7\u53bb\u7814\u7a76\u7ecf\u5386\u4e0e\u6211\u672a\u6765\u7684\u76ee\u6807\u65b9\u5411\u4e0d\u76f8\u4f3c\uff0c\u4f46\u662f\u6700\u540e push \u81ea\u5df1\u5fc5\u987b\u53bb\u5bfb\u627e\u4e00\u4e2a\u5e73\u8861\u70b9\uff0c\u5bfb\u627e\u80fd\u628a\u5b83\u4eec\u90fd\u6982\u62ec\u4f4f\u7684\u4e24\u4e09\u4e2a\u5c0f\u6807\u9898\u3002\u8fd9\u4e24\u4e09\u4e2a\u5c0f\u6807\u9898\u7684\u9009\u62e9\u9996\u5148\u8981\u670d\u52a1\u4e8e\u672a\u6765\u65b9\u5411\uff0c\u7136\u540e\u56e0\u4e3a\u8fc7\u53bb\u7684\u6bcf\u4e2a\u9879\u76ee\u4e0d\u53ef\u80fd\u53ea\u6709\u4e00\u4e2a\u5c5e\u6027/\u9886\u57df\uff0c\u53ef\u4ee5\u9009\u62e9\u80fd\u591f\u670d\u52a1\u4e8e\u672a\u6765\u65b9\u5411\u7684\u65b9\u9762\u6765\u652f\u6491\u8fd9\u4e9b\u5c0f\u6807\u9898\uff0c\u7528\u201c\u6211\u53d7\u5230\u4e86 xx \u65b9\u9762\u7684\u542f\u53d1\u201d\u201c\u5728\u505a\u8be5\u9879\u76ee\u7684\u65f6\u5019\u4e00\u76f4\u5728\u601d\u8003\u67d0\u65b9\u9762\u4e0d\u8db3\u201d\u4e4b\u7c7b\u7684\u8bdd\u8fde\u63a5\u8d77\u6765\u3002\u6700\u540e\u7684\u611f\u609f\u662f\u5199\u4f5c\u6587\u4e66\u7684\u8fc7\u7a0b\uff08\u63cf\u8ff0\u81ea\u5df1\u7684\u8fc7\u7a0b\uff09\u5373\u8ba4\u8bc6\u548c\u5b9a\u4e49\u81ea\u5df1\u8fc7\u53bb\u7684\u7814\u7a76\u7684\u8fc7\u7a0b\uff0c\u611f\u89c9\u5199\u5b8c\u540e\u6211\u5bf9\u4e4b\u524d\u7814\u7a76\u7684\u8ba4\u8bc6\u4e5f\u786e\u5b9e\u53d8\u6210\u4e86\u8fde\u8d2f\u7684\u4e00\u4e2a\u6574\u4f53\uff0c\u4e14\u4ea7\u751f\u4e86\u4e00\u4e9b\u5bf9\u672a\u6765\u7814\u7a76\u7684\u542f\u53d1\u3002

    \u4ee5\u53ca\u90e8\u5206\u9879\u76ee\u4e5f\u4f1a\u5728\u7f51\u7533\u9875\u9762\u7ed9\u51fa\u6587\u4e66\u5199\u4f5c\u6307\u5bfc\uff08e.g. UCSD, CMU\uff09\uff0c\u53ef\u7559\u610f\u9605\u8bfb\u8fd9\u4e9b\u6307\u5bfc\uff0c\u6309\u5177\u4f53\u9879\u76ee\u7684\u6765\u589e\u5220\u6539\u3002

    PS

    \u5982\u4e0a\u6587\u63d0\u5230\uff0c\u5982\u679c\u90e8\u5206\u5b66\u6821\u53ea\u8981\u6c42\u4e00\u4efd PS\uff0c\u90a3\u4e48\u5e94\u5f53\u662f\u9700\u8981\u5f53\u4f5c SOP \u6765\u5199\u5b66\u672f\u548c\u804c\u4e1a\u5185\u5bb9\u7684\u3002\u6211\u662f\u8fd9\u6837\u89c4\u5212\u7ed3\u6784\u7684\uff1a

    \u5982\u679c PS \u548c SOP \u540c\u65f6\u9700\u8981\uff0c\u90a3\u4e48 PS \u7528\u6765\u8bb2\u6545\u4e8b\u6bd4\u8f83\u597d\u3002\u6211\u6ca1\u6709\u8bbe\u8ba1\u4e00\u4efd\u901a\u7528\u7684\u6545\u4e8b\uff0c\u57fa\u672c\u662f\u770b\u9879\u76ee\u8981\u6c42\u3001\u5f55\u53d6\u504f\u597d\u7136\u540e\u5199\u5bf9\u5e94\u7684\u6545\u4e8b\uff0c\u6bd4\u5982 NEU MSCS \u6211\u5199\u4e86\u4e00\u7bc7\u201c\u81ea\u5df1\u5982\u4f55\u4e00\u76f4\u559c\u6b22 cs \u5e76\u4e00\u70b9\u4e00\u70b9\u505a\u5f00\u6e90\u9879\u76ee\u201d\u7684\u6545\u4e8b\uff0cRice \u8ba9\u5199\u4e00\u4e2a\u514b\u670d\u56f0\u96be\u7684\u6545\u4e8b\uff0c\u6211\u5c31\u5199\u6211\u53d7\u5230\u4e86\u4e00\u4e9b\u4e13\u4e1a\u6b67\u89c6\u4f46\u8fd8\u662f\u52aa\u529b\u53bb\u53c2\u4e0e CS \u8bfe\u7a0b\u548c\u793e\u7fa4\u7684\u7ecf\u5386\u3002\u8fd9\u4e24\u6bb5\u90fd\u662f\u6bd4\u8f83\u4e2a\u4eba\u5316\uff0c\u6709\u70b9 emotional\uff0c\u4f46\u662f\u4e3b\u9898\u53c8\u8ddf\u4e2a\u4eba\u54c1\u8d28\u548c\u5b66\u4e1a\u6709\u5173\u7684\uff0c\u6839\u636e\u9762\u8bd5\u6216 offer \u7b49\u9014\u5f84\u7684\u53cd\u9988\u6765\u770b\u611f\u89c9\u62db\u751f\u5b98\u8fd8\u6bd4\u8f83\u770b\u597d\u3002

    \u6210\u7ee9\u5355

    \u628a\u6210\u7ee9\u5355\u5217\u4e3a\u6587\u4e66\u662f\u56e0\u4e3a\u6211\u4ea4\u4e86\u4e00\u4efd\u975e\u5e38\u4e0d\u5bfb\u5e38\u7684\u6210\u7ee9\u5355\uff0c\u5728\u6210\u7ee9\u5355\u524d\u9762\u9644\u4e86 4 \u9875 cover letter \u8bba\u8ff0\u6211\u8fd9\u51e0\u5e74\u901a\u52e4\u7389\u6cc9\u5927\u6982\u82b1\u8d39\u603b\u65f6\u95f4\u591a\u5c11\uff0c\u6211\u7684\u603b\u5b66\u5206\u6bd4\u522b\u4eba\u591a\u591a\u5c11\uff0c\u6211\u7533\u8bf7\u540e\u6bd5\u4e1a\u524d\u9884\u8ba1\u5b8c\u6210\u7684\u8bfe\u7a0b\u8fd8\u6709\u54ea\u4e9b\uff0c\u603b\u4e4b\u786e\u5b9e\u4e0a\u8bfe\u7684\u5de5\u4f5c\u91cf\u5927\uff0c\u5e0c\u671b\u62db\u751f\u5b98\u4e5f\u80fd\u8003\u8651\u8fd9\u4e2a\u56e0\u7d20\u7b49\u3002\u4e5f\u4e0d\u77e5\u9053\u5408\u4e0d\u5408\u89c4\uff0c\u4f46\u8fd9\u4e9b\u4e1c\u897f\u786e\u5b9e\u4e0d\u77e5\u9053\u54ea\u91cc\u53bb\u5199\u3002\u76ee\u524d\u8fd8\u6ca1\u6709\u76f4\u63a5\u6216\u95f4\u63a5\u7684\u53cd\u9988\u80fd\u544a\u8bc9\u6211\u8fd9\u6837\u505a\u5bf9\u4e0d\u5bf9\u6216\u597d\u4e0d\u597d\u3002

    "},{"location":"docs/4-opinion/plan/24fall/#_6","title":"\u6691\u7814","text":"

    \u5bf9\u4e8e\u6691\u7814\u4e00\u4e2a\u6bd4\u8f83\u7b80\u5355\u7684 comment \u662f\u5982\u679c\u60f3\u7533\u5317\u7f8e PhD \u5c31\u76f4\u63a5\u53bb\u9676\u74f7\u5317\u7f8e\uff0c\u4e0d\u8981\u5728\u610f\u201c\u5317\u7f8e rank \u4e0d\u597d\u7684\u5b66\u6821\u662f\u4e0d\u662f\u4e0d\u5982\u522b\u7684\u5730\u533a rank \u597d\u7684\u5b66\u6821\u201d\uff0c\u56e0\u4e3a\u5730\u533a\u5185\u5708\u5b50\u7684\u8001\u5e08\u8fd8\u662f\u4f1a\u6bd4\u5730\u533a\u5916\u719f\u4e00\u4e9b\uff0c\u4e14\u90e8\u5206\u8001\u5e08\u6691\u7814\u7684\u98ce\u683c\u662f\u628a\u597d\u5b66\u751f\u63a8\u5411\u66f4\u597d\u7684\u8001\u5e08\u4ee5\u5efa\u7acb\u5b66\u672f connection\u3002\u4ee5\u53ca\u867d\u7136\u5728\u5317\u7f8e onsite \u7814\u7a76\u786e\u5b9e\u5bf9\u793e\u4ea4\u6709\u5229\uff0c\u4f46\u6761\u4ef6\u5f88\u96be\u5177\u5907\uff0c\u56e0\u4e3a\u7b7e\u8bc1\u529e\u7406\u96be\u5ea6\u5927\uff0c\u5bf9\u6559\u6388\u6765\u8bf4\u5e38\u5e38\u6295\u5165\u5927\u4e8e\u56de\u62a5\uff0c\u5b66\u751f\u9002\u5e94\u6210\u672c\u4e5f\u9ad8\uff0c\u4e0d\u4e00\u5b9a\u80fd\u6709\u5229\u4e8e\u6548\u7387\uff0c\u6240\u4ee5\u5982\u679c\u6709 prof \u8ddf\u6211\u8bf4\u4e0d\u613f\u4e3a\u6211\u529e\u7b7e\u8bc1\u6211\u662f\u80fd\u7406\u89e3\u7684\u3002online \u6548\u529b\u4e5f\u4e0d\u4f4e\u7684\u3002

    \u5e38\u5e74\u5f00\u653e\u7684\u51e0\u4e2a\u6691\u7814\uff08\u4e0d\u5168\u9762\uff0c\u5efa\u8bae\u591a\u65b9\u53c2\u8003\uff0c\u66f4\u5efa\u8bae\u5927\u80c6\u76f4\u63a5\u90ae\u4ef6\u5957\u74f7\uff09

    "},{"location":"docs/4-opinion/plan/24fall/#_7","title":"\u53c2\u8003\u8d44\u6599","text":"

    https://github.com/zhanglj37/Tutorial-on-PhD-Application

    "},{"location":"docs/4-opinion/plan/asundergrad/","title":"As An Undergrad \u672c\u79d1\u7684\u4e00\u8def\u8d70\u6765","text":"

    :material-circle-edit-outline: \u7ea6 284 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    \u4e00\u5207\u8981\u4ece\u5927\u5b66\u662f\u4ec0\u4e48\u7684\u5b9a\u4e49\u8c08\u8d77

    \u662f\u5426\u6709\u5fc5\u8981\u8c08\u8fd9\u4e48\u6839\u672c\uff1f\u6709

    \u3002\u3002\u3002\u6551\u547d

    \u5148\u5806\u79ef\u4e00\u4e9b\u60f3\u5bf9\u672a\u6765\u7684\u81ea\u5df1\u8bf4\u7684\u53e5\u5b50\u5427

    \u53c8\u56de\u5bb6\u770b\u5230\u8001\u5e08\u5728\u4f53\u7cfb\u7fa4\u6f47\u6d12\u7559\u4e0b\u4e00\u884c\uff1a\u201c\u8981\u5728\u6da7\u6c34\u6cc9\u58f0\u3001\u6797\u6d9b\u677e\u98ce\u3002\u201d\uff08\u6211\u6ca1\u6709\u67e5\u5230\u8fd9\u53e5\u7684\u51fa\u5904\uff0c\u7591\u4f3c\u662f\u201c\u4e00\u79cd\u5b64\u9ad8\u4e0d\u6613\u6500\uff0c\u6b64\u8eab\u53ea\u5408\u4f4f\u6df1\u5c71\u3002\u517b\u6210\u9cde\u7532\u4e3a\u9f99\u53bb\uff0c\u5316\u4f5c\u4e91\u6d9b\u5f85\u9e64\u8fd8\u3002\u58f0\u5165\u7a7a\u6797\u4eba\u5bc2\u5bc2\uff0c\u54cd\u5f52\u5e7d\u6da7\u6c34\u6f7a\u6f7a\u3002\u53ee\u5b81\u83ab\u628a\u677e\u98ce\u5356\uff0c\u7559\u5728\u5343\u5ca9\u4e07\u58d1\u95f4\u3002\u201d\u4e00\u9996\u8bd7\uff1f\uff09\u6709\u540c\u5b66\u63a5\uff1a\u6362\u4e2a\u5f62\u5f0f\u966a\u5927\u5bb6\uff0c\u90fd\u5728\u7684\u3002\u4e8e\u662f\u53c8\u611f\u5230\u4f55\u5fc5\u9053\u522b\uff0c\u6211\u5df2\u7ecf\u628a\u8fd9\u4e9b\u5e74\u5404\u4f4d\u6240\u6709\u4eba\u8d60\u4e88\u6211\u7684\u77e5\u8bc6\u3001\u6027\u683c\u3001\u89c2\u5ff5\u3001\u529b\u91cf\u5168\u90e8\u5e26\u5728\u8eab\u4e0a\u5e26\u8d70\u4e86\u3002

    "},{"location":"docs/4-opinion/plan/find1job/","title":"Find a job in academia or industries?","text":"

    :material-circle-edit-outline: \u7ea6 23 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/plan/find1job/#opinions","title":"Opinions","text":"

    In academia

    "},{"location":"docs/4-opinion/plan/find1job/#-","title":"-","text":"

    In industries

    "},{"location":"docs/4-opinion/plan/find1job/#-_1","title":"-","text":""},{"location":"docs/4-opinion/plan/find1job/#my-choice","title":"My Choice?","text":""},{"location":"docs/4-opinion/plan/find1job/#resources","title":"Resources","text":""},{"location":"docs/4-opinion/plan/survivezju/","title":"Survivezju","text":"

    :material-circle-edit-outline: \u7ea6 1 \u4e2a\u5b57

    Reference

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/","title":"ZJU English Major to CS","text":"

    :material-circle-edit-outline: \u7ea6 4032 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 13 \u5206\u949f

    \u26a0\ufe0f \u611f\u89c9\u5f53\u65f6\u5199\u5f97\u4e0d\u662f\u5f88\u597d\uff0c\u73b0\u5728\u5f88\u591a\u89c2\u5ff5\u53c8\u6709\u4e9b\u6539\u53d8\uff0c\u53ef\u80fd24\u5e74\u6625\u8282\u671f\u95f4\u7a7a\u4e0b\u6765\u4f1a\u518d\u8ba4\u771f\u6539\u4e00\u4e0borz

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_1","title":"\u672c\u6587\u6863\u662f\u4ec0\u4e48\uff1f","text":"

    \u7b14\u8005\u8f6c\u4e13\u4e1a\u8e29\u8fc7\u7684\u5751\u548c\u5bf9\u540e\u8f88\u7684\u5efa\u8bae\uff0c\u771f\u5fc3\u60f3\u5efa\u7acb\u8d77ZJU\u5185\u90e8\u826f\u597d\u7684\u4f20\u5e2e\u5e26\u6c1b\u56f4\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_2","title":"\u89c2\u5ff5&\u4e60\u60ef\u95ee\u9898","text":"

    \u5728\u5177\u4f53\u5efa\u8bae\u524d\u9996\u5148\u56de\u7b54\u4e00\u4e9b\u5e38\u6709\u7684\u62c5\u5fe7+\u505a\u4e00\u4e9b\u4e60\u60ef\u65b9\u9762\u7684\u63d0\u9192

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs","title":"\u6211\u80fd\u8f6c\u5230CS\u5417\uff1f","text":"

    \u80fd\u3002\u6709\u5982\u4e0b\u6848\u4f8b\uff08\u4e0d\u4ee3\u8868\u6240\u6709\u4eba\u613f\u610f\u88ab\u8054\u7cfb\u5230\uff0c\u4e0d\u4fdd\u8bc1\u63d0\u4f9b\u8054\u7cfb\u65b9\u5f0f\uff09

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#nlp","title":"NLP\u4e0d\u8981\u8bed\u8a00\u5b66\u540c\u5b66\u5417\uff1f","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#_3","title":"\u660e\u786e\u4e00\u4e2a\u5341\u5e74\u5230\u4e09\u5341\u5e74\u7684\u957f\u8fdc\u89c4\u5212\uff0c\u4e3b\u8981\u662f\u4ee5\u4e0b\u51e0\u4e2a\u95ee\u9898","text":"\u95ee\u9898 \u6211\u7684\u56de\u7b54 \u6211\u8981\u5728\u54ea\u91cc\u751f\u6d3b\uff0c\u56fd\u5185\u8fd8\u662f\u56fd\u5916\uff1f \u6211\u8f6cCS\u662f\u66f4\u591a\u56e0\u4e3a\u559c\u6b22\u7406\u5de5\u79d1\uff0c\u8fd8\u662f\u56e0\u4e3a\u559c\u6b22\u5de5\u8d44\uff1f \u6211\u8981\u8fdb\u5de5\u4e1a\u754c\uff0c\u53bb\u79d1\u6280\u4e92\u8054\u7f51\u516c\u53f8\u5de5\u4f5c\uff1b\u8fd8\u662f\u7559\u5728\u5b66\u672f\u754c\uff0c\u5728\u9ad8\u6821\u6216\u7814\u7a76\u6240\u5de5\u4f5c\uff1f \u6211\u8981\u505aCS\u9664NLP\u5176\u5b83\u7684\u65b9\u5411\uff0c\u5982\u7cfb\u7edf\u3001\u7f51\u7edc\u3001\u5b89\u5168\u3001CV\u6216\u7eaf\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u65b9\u5411\uff1b\u8fd8\u662f\u505a\u504f\u6df1\u5ea6\u5b66\u4e60\u7684NLP\u65b9\u5411\uff1b\u8fd8\u662f\u505a\u504f\u8bed\u8a00\u5b66\u7684NLP\u65b9\u5411\uff1f \u6211\u6709\u591a\u5c11\u7ecf\u8d39\uff1f \u6211\u591a\u5c11\u5e74\u5185\u9700\u8981\u8f6c\u597d\u4e13\u4e1a\uff1f"},{"location":"docs/4-opinion/plan/zju_ling_cs/#_4","title":"\u89c4\u5212\u4eba\u751f\u4e2d\u8be5\u505a/\u4e0d\u8be5\u505a\u7684\u4e8b\u7684\u4e24\u4e2a\u51c6\u5219","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_1","title":"\u628a\u81ea\u5df1\u770b\u6210CS\u4eba","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_2","title":"CS\u6709\u8001\u5e08\u540c\u5b66\u770b\u4e0d\u8d77\u6211\u600e\u4e48\u529e\uff1f","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_3","title":"\u5b66\u4e0d\u597dCS\uff0c\u662f\u4e0d\u662f\u56e0\u4e3a\u5b66\u82f1\u8bed\u8bfe\u4f7f\u6211\u53d8\u4e0d\u806a\u660e\u4e86\uff1f","text":"

    \u4e0d\u662f\u7684\u3002 - \u7406\u8bba\u4e0a\u662f\u5b8c\u5168\u53ef\u4ee5\u5b66\u597d\u7684\u3002NLP\u5708\u6709\u5f88\u591a\u7814\u7a76\u8005\u8bfb\u8fc7\u8bed\u8a00\u5b66\u548cCS\u53cc\u672c\u79d1\uff0c\u4ee3\u8868AP\u6709AllenNLP Noah Smitch, Colimbia University Zhou Yu\uff08ZJU\u7684\u672c\u79d1\uff09. \u8bfb\u8bed\u8a00\u5b66\u6ca1\u6709\u803d\u8bef\u4ed6\u4eec\u7684\u8111\u5b50\uff0c\u53cd\u800c\u662f\u4e00\u4e2a\u5f88\u597d\u7684idea\u6765\u6e90\u3002\u6211\u611f\u89c9\u6709\u5f88\u591a\u5929\u624d\u7684\u6848\u4f8b\u53ef\u4ee5\u8bc1\u660e\u4eba\u7684\u77e5\u8bc6\u5bb9\u91cf\u548c\u5b66\u4e60\u80fd\u529b\u4e0a\u9650\u662f\u8d85\u51fa\u5927\u5bb6\u60f3\u8c61\u7684\uff0c\u5b66\u4e24\u4e2a\u4e13\u4e1a\u8fd9\u4ef6\u5c0f\u4e8b\u8fdc\u8fdc\u5728\u8fd9\u4e2a\u4e0a\u9650\u4e4b\u4e0b\u3002\u6211\u6c38\u8fdc\u8ba4\u4e3a\u6bc5\u529b\u548c\uff08\u5bf9\u81ea\u5df1\u4eba\u751f\u4e0a\u9650\u7684\uff09\u60f3\u8c61\u529b\u6bd4\u5f53\u524d\u80fd\u529b\u66f4\u6709\u51b3\u5b9a\u4f5c\u7528\u3002 - \u5b9e\u9645\u82f1\u8bed\u4e13\u4e1a\u53bbCS\u53cc\u4e13\u4e1a\u5bb9\u6613\u5403\u4f4e\u7ee9\u70b9\u7684\u539f\u56e0\uff0c\u5f80\u5f80\u4e0d\u662f\u80fd\u529b\u667a\u529b\u4e0d\u8db3\uff0c\u800c\u662f\u6709\u4fe1\u606f\u5dee\uff1a\u751f\u6d3b\u5728\u6587\u79d1\u7684\u6563\u6f2b\u73af\u5883\u4e2d\u96be\u4ee5\u77e5\u9053\u5927\u90e8\u5206\u540c\u5b66\u7684\u81ea\u5b66\u8fdb\u5ea6\uff0c\u548c\u5982\u679c\u67d0\u4e9b\u8bfe\u7a0b\u6709\u5b9e\u8df5\u4e0a\u7684\u5751\uff0c\u6ca1\u6709\u4e0e\u5927\u90e8\u961f\u4e00\u8d77\u5b66\u4e60\u7684\u540c\u5b66\u5c31\u96be\u4ee5\u77e5\u9053\u600e\u6837\u7075\u6d3b\u5e94\u5bf9\u3002\u6240\u4ee5\u5efa\u8bae\u4e0e\u540c\u5b66\u4e00\u8d77\u5b66\u4e60\uff0c\u53c2\u89c1\u4e0b\u4e00\u6761\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#cscs","title":"\u8981\u62e5\u6709\u4e00\u4e2a\u6216\u51e0\u4e2a\u540c\u6837\u8de8\u4e13\u4e1a\u5b66CS\u7684\u670b\u53cb\uff0c\u6216\u76f4\u63a5\u878d\u5165\u540c\u4e00\u7ea7\u7684CS\u672c\u79d1\u751f\u5708\u5b50\u91cc\u3002\u5982\u679c\u5b9e\u5728\u6ca1\u6709\uff0c\u4e00\u4e9b\u5176\u5b83\u5de5\u79d1\u7684\u540c\u5b66\u4e5f\u53ef\u4ee5\u3002","text":"

    \u540c\u5b66\u7684\u7528\u5904\u6709\uff1a - \u5e2e\u52a9\u4f60\u8ddf\u4e0a\u5b66\u4e60\u8282\u594f\u3002CS\u7684\u751f\u6d3b\u8282\u594f\u662f\u82f1\u8bed\u4e13\u4e1a\u76842\u500d\uff0c\u662f\u7406\u79d1\u4e13\u4e1a\u76841.5\u500d\uff0c\u5982\u679c\u51b3\u5b9a\u8f6c\u4e13\u4e1a\u662f\u9700\u8981\u4e3b\u52a8\u63d0\u9ad8\u4e00\u4e0b\u751f\u6d3b\u8282\u594f\u7684\uff0c\u505a\u4e8b\u79ef\u6781\u4e00\u70b9\uff0c\u544a\u522b\u62d6\u5ef6\u3002 - \u4e92\u76f8\u63a8\u8350\u597d\u7684\u81ea\u5b66\u8d44\u6599\uff0c\u4e92\u76f8\u5206\u4eab\u7b14\u8bb0\u548c\u8ba8\u8bba\u9898\u76ee\uff0c\u5206\u5de5\u6574\u7406\u671f\u672b\u590d\u4e60\u8d44\u6599\uff0c\u671f\u672b\u4e92\u76f8\u63d0\u95ee\uff0c\u5f62\u6210\u81ea\u5b66\u6c1b\u56f4\uff0c\u8282\u7701\u4e00\u4e9b\u8e29\u5751\u65f6\u95f4\u3002 - \u5982\u679c\u67d0\u4e9b\u8bfe\u7a0b\u5b89\u6392\u6709\u6559\u5b66\u4e8b\u6545\uff0c\u4f60\u53ef\u4ee5\u53ca\u65f6\u77e5\u9053\u5927\u90e8\u5206\u540c\u5b66\u662f\u600e\u6837\u5e94\u5bf9\u7684\uff0c\u53ca\u65f6\u8c03\u6574\u81ea\u5df1\u7684\u5e94\u5bf9\u63aa\u65bd\uff0c\u9632\u6b62\u5982\u679c\u6210\u7ee9\u5360\u6bd4\u7a81\u7136\u8c03\u6574\uff0c\u81ea\u5df1\u5c06\u52aa\u529b\u82b1\u5728\u4e86\u6700\u540e\u5360\u6210\u7ee9\u6bd4\u91cd\u5f88\u5c0f\u7684\u5730\u65b9\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_5","title":"\u8981\u591a\u8bb0\u7b14\u8bb0","text":"

    \u8bb0\u7b14\u8bb0\u662f\u8d39\u66fc\u5b66\u4e60\u6cd5\u7684\u6295\u5165\u4ea7\u51fa\u6bd4\u6700\u9ad8\u7684\u5b9e\u8df5\u5f62\u5f0f\uff0c\u5373\u65e2\u5e2e\u52a9\u68c0\u67e5\u7406\u89e3\uff0c\u7b14\u8bb0\u53c8\u9020\u798f\u540e\u4eba\u3002\u4f60\u53ef\u4ee5\u79c9\u627f\u5f00\u6e90\u7cbe\u795e\uff0c\u50cf\u524d\u8f88\u4e00\u6837\u591a\u5c06\u7b14\u8bb0\u516c\u5e03\u9020\u798f\u540e\u4eba\uff08\u4e0d\u8fc7\u8bf7\u9075\u5b88\u8bda\u4fe1\u5b88\u5219\uff09\u3002\u975e\u5e38\u5e0c\u671bZJU\u80fd\u9010\u6e10\u5f62\u6210\u8f83\u597d\u7684\u4f20\u5e2e\u5e26\u6c1b\u56f4\uff0c\u8ba9\u540e\u8f88\u4e5f\u6709\u826f\u597d\u6821\u53cb\u8d44\u6e90\u53ef\u4eab\u7528\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_6","title":"\u6211\u53ef\u4ee5\u4ee5\u600e\u6837\u7684\u8eab\u4efd\u672c\u79d1\u6bd5\u4e1a\uff1f\u6211\u6709\u54ea\u4e9b\u53ef\u884c\u7684\u51fa\u8def\uff1f","text":"

    \u4ee5\u4e0b\u8fd9\u4e9b\u90fd\u662f\u53ef\u80fd\u505a\u5230\u7684\uff0c\u6211\u4e5f\u5206\u522b\u5217\u51fa\u4e86\u6211\u8ba4\u4e3a\u9700\u8981\u51c6\u5907\u7684\u80cc\u666f\u3002 - \u51fa\u56fdms\uff1a\u7ee9\u70b9\uff0c\u6691\u7814/\u5b9e\u4e60 - \u51fa\u56fd\u76f4\u63a5phd\uff1a\u6691\u7814\uff0cpaper - \u672c\u6821\u76f4\u535a\uff1a\u7ee9\u70b9\uff0c\u8fdb\u672c\u6821\u7ec4\uff0c\u590f\u4ee4\u8425\uff0cpaper - \u8de8\u6821\u76f4\u535a\uff1a\u7ee9\u70b9\uff0c\u5bf9\u65b9\u6821\u590f\u4ee4\u8425\uff0cpaper - \u5de5\u4f5c\uff1a\u5237\u9898\uff0c\u5b9e\u4e60 \u5176\u4e2d\u6211\u8ba4\u4e3a\u503c\u5f97\u6ce8\u610f\u7684\u8fd8\u6709\uff0c\u5177\u4f53\u6700\u597d\u7531\u8bfb\u8005\u518d\u54a8\u8be2\u76f8\u5e94\u8eab\u4efd\u7684\u4eba\u7684\u5efa\u8bae\u3002\u672c\u6761\u9002\u7528\u524d\u9762\u6240\u8ff0\u201c20\u4e2a\u4eba\u5efa\u8bae\u201d\u51c6\u5219\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_7","title":"\u8bfe\u7a0b","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#cs_4","title":"CS\u5fc5\u4fee\u8bfe","text":"

    \u9996\u5148\u8981\u660e\u786e\u4e00\u4e2a\u8ba4\u77e5\u95ee\u9898\uff1a\u8bfbCS\u53cc\u5b66\u4f4d\u662f\u4e00\u4e2a\u539f\u5b50\u6027\u7684\u4e8b\u52a1\uff0c\u8981\u4e48\u4e0d\u8bfb\uff0c\u8981\u4e48\u6309\u9700\u6c42\u8bfb\u5b8c\u6216\u8f85\u4fee\u6216\u53cc\u5b66\u4f4d\uff0c\u8fd9\u4e24\u79cd\u9009\u62e9\u90fd\u662f\u6295\u5165\u4ea7\u51fa\u6bd4\u8f83\u9ad8\u7684\uff1b\u6295\u5165\u4ea7\u51fa\u6bd4\u6700\u4f4e\u7684\u662f\u8bfb\u4e00\u534a\uff08\u5fae\u8f85\u4fee\u6216\u53cc\u4e13\u4e1a\uff09\u3002 \u8be5\u56fe\u4e2d\u9664\u6570\u7406\u57fa\u7840\u6a21\u5757\u4e0d\u662f\u53cc\u5b66\u4f4d\u5fc5\u4fee\uff0c\u5176\u5b83\u662f\u5fc5\u4fee\u3002 \uff08\u8fd9\u4e2a\u56fe\u4e0d\u77e5\u9053\u4e3a\u4ec0\u4e48\u6709\u4e2a\u7ea2\u5708\uff0c\u627e\u4e0d\u5230\u539f\u56fe\u4e86\uff0c\u6279\u8bc4cyh\u540c\u5b66\u4e71\u753b\uff09

    \u9009\u4e0d\u4e0aCS\u7684\u8bfe\u600e\u4e48\u529e\uff1f - \u6700\u6709\u6548\uff1a\u8865\u9009+\u5728\u8865\u9009\u7684\u51e0\u5929\u91cc\u7ebf\u4e0b\u53bb\u9009\u8bfe\u529e\u6216\u7ed9\u9009\u8bfe\u529e\u53d1\u90ae\u4ef6\u3002\u674e\u6653\u8001\u5e08\u548c\u5f20\u4f20\u534e\u8001\u5e08\u90fd\u5f88nice\uff0c\u8868\u793a\u81ea\u5df1\u5f88\u60f3\u9009\u8bfe\uff0c\u8ddf\u8001\u5e08\u8bf4\u660e\u539f\u56e0\u3002 - \u7b2c\u4e8c\u6709\u6548\uff1a\u5982\u679c\u4efb\u8bfe\u8001\u5e08\u5728\u8ba1\u9662\u8bdd\u8bed\u6743\u8f83\u5927\uff0c\u8bf7\u4efb\u8bfe\u8001\u5e08\u5e2e\u5fd9\u8ddf\u9009\u8bfe\u529e\u8bf4\uff0c\u80fd\u4fdd\u8bc1\u4f60\u9009\u4e0a\u8be5\u8001\u5e08\u7684\u8bfe\u3002 - \u7b2c\u4e09\u6709\u6548\uff1a\u9009\u8bfe\u65f6\u4e0eCS\u7684\u540c\u5b66\u5546\u91cf\uff0c\u505a\u51fa\u65f6\u95f4\u6b63\u597d\u7684\u4e00\u4e9b\u8bfe\u8868\u3002\u53ef\u80fd\u6d89\u53ca\u5230\u201c\u7528\u4e00\u4e9b\u8bfe\u5835\u4f4f\u53e6\u4e00\u4e9b\u8bfe\u201d\u8fd9\u79cd\u590d\u6742\u64cd\u4f5c\uff0c\u6240\u4ee5\u5408\u4f5c\u6bd4\u8f83\u5212\u7b97\u3002

    \u600e\u4e48\u5b66\uff1f - ZJU\u8bfe\u7a0b\u5171\u4eab\u8ba1\u5212 https://github.com/QSCTech/zju-icicles - \u56fe\u7075\u73ed\u8bfe\u7a0b\u901f\u901a\u8ba1\u5212 https://github.com/ZJU-Turing/TuringCourses - \u4e00\u4f4d\u5b66\u957f\u7684\u4f18\u8d28\u7b14\u8bb0 \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4\uff01 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4 (xuan-insr.github.io) - \u4e00\u4f4d\u5b66\u957f\u7684\u4f18\u8d28\u7b14\u8bb0 https://github.com/Zhang-Each/CourseNoteOfZJUSE

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#ai","title":"AI","text":"

    AI\u8bfe\u4e00\u822c\u6bd4CS\u8bfe\u597d\u9009\uff0c\u4f46\u662f\u5982\u679c\u9009\u4e0d\u4e0a\u4e5f\u8bf7\u9075\u7167\u4e0a\u6761\u4e2d\u7684\u5efa\u8bae\u3002 \u975e\u5fc5\u8981\u4e0d\u9009AI\u8bfe\uff0cAI\u8bfe\u6700\u5927\u7684\u6536\u83b7\u662f\u5728\u7b80\u5386\u4e0a\u4f5c\u4e3a\u4e00\u4e2a90+\u8bfe\u7a0b\u51fa\u73b0\uff0c\u57fa\u672c\u5b66\u4e0d\u5230\u4e1c\u897f\uff08\u9664\u4e86NLP\u8bfe\u6211\u611f\u89c9\u542c\u8bfe\u6536\u83b7\u633a\u5927\u7684\uff09\uff0c\u4e3b\u8981\u9760\u81ea\u5b66\u540e\u5377\u51fa\u5927\u4f5c\u4e1a\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_8","title":"\u8bed\u8a00\u5b66","text":"

    \u56e0\u4e3a\u82f1\u4e13\u57f9\u517b\u65b9\u6848\u8fd8\u662f\u8981\u6c42\u4fee\u5927\u91cf\u4e13\u4e1a\u8bfe\u7684\uff0c\u611f\u89c9\u53ef\u4ee5\u5c3d\u91cf\u628a\u8bed\u8a00\u5b66\u6a21\u5757\u591a\u4fee\u4e00\u70b9\uff0c\u6709\u4e9b\u5728\u8fdb\u7ec4\u7684\u65f6\u5019\u53ef\u80fd\u8fd8\u662f\u8ba4\u53ef\u7684\u3002 \u4ee5\u4e0b\u8bfe\u7a0b\u5982\u679c\u62ff\u4e86\u9ad8\u5206\u503c\u5f97\u5728\u7b80\u5386\u4e0a\u4e00\u63d0 - \u5f53\u4ee3\u8bed\u8a00\u5b66 - \u8bed\u97f3\u5b66 - \u53e5\u6cd5\u5b66 - \u5fc3\u7406\u8bed\u8a00\u5b66 - \u8bed\u4e49\u5b66 - \u8bed\u7528\u5b66 - \u8bed\u6599\u5e93\u8bed\u8a00\u5b66

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_9","title":"\u6570\u5b66","text":"

    \u5bf9\u4e8ePhD\u3001\u627e\u5de5\u548c\u56fd\u5185\u76f4\u535a\uff1a \u53ef\u80fd\u4e0d\u9700\u8981\u6570\u5b66\u3002\u3002\u3002\u8ba4\u4e3a\u6700\u597d\u4e0d\u8981\u989d\u5916\u9009\u6570\u5b66\u8bfe \u6211\u81f3\u4eca\u9047\u5230\u7684\u8001\u5e08\u6ca1\u6709\u56e0\u4e3a\u6211\u7b80\u5386\u4e0a\u4efb\u4f55\u6570\u5b66\u76f8\u5173\u7684\u4e1c\u897f\u800c\u5f55\u6211\u6216\u62d2\u6211\u7684\uff0c\u90fd\u662f\u53ea\u95ee\u7f16\u7a0b\u3002 CS\u4e13\u4e1a\u8bfe\u91cc\u7684\u79bb\u6563\u6570\u5b66\u548c\u8ba1\u7b97\u7406\u8bba\uff08\u548c\u53ef\u80fd\u8fd8\u6709\u6570\u903b\uff09\u5df2\u7ecf\u8db3\u591f\u57f9\u517b\u6570\u5b66\u601d\u7ef4\u3002 \u5982\u679c\u62c5\u5fc3\u6570\u636e\u5206\u6790\u548c\u7edf\u8ba1\u6280\u80fd\uff0c\u6587\u6570\u91cc\u636e\u8bf4\u5e94\u7528\u7edf\u8ba1\u5b66\u8fd9\u95e8\u8bfe\u7a0b\u6bd4\u9ad8\u7b49\u6570\u5b66\u597d\u4f7f\uff0c\u8fd8\u6709\u673a\u4f1a\u7684\u540c\u5b66\u53ef\u4ee5\u8bd5\u4e00\u4e0b\u3002

    \u5bf9\u4e8ems\uff1a \u786e\u5b9e\u6709\u4e00\u4e9b\u9879\u76ee\u8981\u6c42\u4fee\u8fc7\u4e00\u4e9b\u6570\u5b66\u8bfe\u7a0b\uff0c\u4f8b\u5982\u521a\u770b\u5230SUTD\u7684ISTD ms\u8981\u6c42\u4e24\u5b66\u671f\u5fae\u79ef\u5206\uff0c\u4e00\u5b66\u671f\u7ebf\u4ee3\u548c\u4e00\u5b66\u671f\u6982\u7edf\uff0c\u8fd9\u79cd\u65e0\u7591\u662f\u6bd4\u8f83\u4e0d\u53cb\u597d\u7684\u9879\u76ee\u4e86\u3002 \u4e5f\u6709\u6bd4\u8f83\u53cb\u597d\u7684\u9879\u76ee\uff0c\u5317\u7f8e\u4e00\u4e9b0\u57fa\u7840\u8f6c\u7801\u9879\u76ee\u53ef\u53c2\u7167OpenCSapp\uff0c\u82f1\u56fd\u7684IC\u548cUCL\u5728\u524d\u5e74\u4e5f\u5f00\u4e86\u96f6\u57fa\u7840\u8f6c\u7801\u9879\u76ee\uff0c\u4e0d\u8fc7\u51fa\u8def\u548c\u542b\u91d1\u91cf\u9700\u8981\u81ea\u5df1\u8861\u91cf\uff0c\u8fd8\u662f\u5efa\u8bae\u201c\u54a8\u8be220\u4e2a\u4eba\u201d\u51c6\u5219\u3002\u4ee3\u8868dp\u662f18\u7ea7SJTU\u82f1\u8bed\u4e13\u4e1a\uff0c4\u6bb5\u79d1\u7814\u6216\u4e92\u8054\u7f51\u5382NLP\u4ea7\u54c1\u5b9e\u4e60\uff0c\u5c11\u91cf\u9ad8\u5206\u6570\u5b66\u548c\u7f16\u7a0b\u8bfe\u7a0b\uff0c\u7ee9\u70b990+ \u2192 IC CS ms

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_10","title":"\u7ee9\u70b9","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#_11","title":"\u79d1\u7814","text":""},{"location":"docs/4-opinion/plan/zju_ling_cs/#nlp_1","title":"\u5982\u4f55\u9009\u9898\uff1fNLP\u6709\u54ea\u4e9b\u65b9\u5411\u53ef\u505a\uff1f","text":"

    \u53c2\u7167\u8fd9\u4e9b\u9876\u4f1a\u90fd\u6709\u4ec0\u4e48track\uff0c\u4e0b\u9762\u662f\u6700\u8fd1\u4e00\u671f\u6bcf\u4e2atrack\u7684best paper - Best Papers - ACL 2023 (aclweb.org) - Best Paper Awards - emnlp 2022 (balhafni.github.io) - Transactions of the Association for Computational Linguistics (transacl.org) - Announcing the NAACL 2022 Best Paper Awards! - NAACL-HLT 2022

    \u7279\u522b\u5730\uff0c\u60f3\u5230NLP\u91cc\u6bd4\u8f83\u7eaf\u8bed\u8a00\u5b66\u7684\u4e3b\u9898/\u65b9\u6cd5\u4e5f\u6709\u4e00\u4e9b\uff0c\u6709\u5982\u4e0b\u51e0\u4e2a \u4e3a\u4ec0\u4e48\u8981\u8bb2\u8fd9\u4e00\u5757\u56e0\u4e3a\u62c5\u5fc3\u4f60\u5728\u9762\u8bd5\u7684\u65f6\u5019\u4f1a\u9700\u8981\u5411\u8001\u5e08\u8bc1\u660e\u4f60\u7684\u53e6\u4e00\u90e8\u5206\u4e13\u4e1a\u77e5\u8bc6\u4e5f\u662f\u6709\u7528\u7684 \u4e00\u822c\u6b27\u6d32\u7684NLP\u4f1a\u504f\u8bed\u8a00\u5b66\u4e00\u70b9 - \u5b9e\u9a8c\u8bed\u97f3\u548c\u97f3\u7cfb\u5b66 - \u7528\u8bed\u8a00\u5b66\u77e5\u8bc6\u505a\u6570\u636e\u548c\u6570\u636e\u589e\u5f3a - AI\u4e2d\u7684\u4f26\u7406\u9053\u5fb7\u95ee\u9898 - \u7a00\u6709\u8bed\u8a00\u6316\u6398

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_12","title":"\u5982\u4f55\u9009\u5bfc\uff1f","text":"

    \u56fd\u5916\u5bfc\u5e08\uff1a\u5e38\u8bfb\u6bcf\u5e74\u7684\u9876\u4f1a\u6709\u610f\u601d\u8bba\u6587\uff0c\u5e76\u53c2\u7167CSRankings: Computer Science Rankings\uff0c\u5173\u6ce8\u5b66\u672f\u5708\u517b\u597d\u53f7\u540e\u5e38\u5237Twitter \u56fd\u5185\u6821\u5185\u5bfc\u5e08\uff1a\u5982\u679c\u6709\u60f3\u8be2\u95ee\u7684\u5bfc\u5e08\u540d\u5355\u53ef\u4ee5\u90ae\u4ef6\u95ee\u6211 \u9009\u5bfc\u6216\u8005\u8054\u7cfbPhD\u7684\u65f6\u5019\u5982\u679c\u63a5\u5230\u7684\u4efb\u52a1\u662f\u4e8c\u4f5c\u4e09\u4f5c\u5f80\u540e\uff0c\u5f88\u53ef\u80fd\u662f\u6253\u767d\u5de5\uff0c\u57fa\u672c\u53ef\u4ee5\u62d2\u7edd\u3002\u9664\u975e\u4f60\u8ba4\u4e3a\u4f60\u627f\u62c5\u7684\u5de5\u4f5c\u8f83\u4e3a\u91cd\u8981\uff0c\u8001\u5e08\u53ef\u4ee5\u7ed9\u4f60\u63a8\u8350\u4fe1\uff0c\u4e8c\u4f5c\u4e09\u4f5c\u7684\u4f5c\u7528\u53ef\u80fd\u6ca1\u6709\u63a8\u8350\u4fe1\u5927\u3002 \u5982\u679c\u7533\u8bf7PhD\uff0c\u63a8\u8350\u4fe1\u7684\u529b\u5ea6\uff1a\u4f60\u4e0e\u63a8\u8350\u4eba\u7684\u4ea7\u51fa\u5f88\u91cd\u8981+\u76ee\u6807PhD\u5bfc\u8ba4\u8bc6\u7684\u4eba > \u4f60\u4e0e\u63a8\u8350\u4eba\u7684\u4ea7\u51fa\u5f88\u91cd\u8981+\u76ee\u6807PhD\u5bfc\u4e0d\u8ba4\u8bc6\u7684\u4eba > \u5176\u5b83

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_13","title":"\u7533\u8bf7","text":"

    \u56e0\u4e3a\u4fdd\u7814\u548c\u627e\u5de5\u6211\u786e\u5b9e\u4e0d\u61c2\uff0c\u8fd9\u91cc\u6682\u65f6\u53ea\u5199\u7533\u8bf7\u4e86\u3002\u540e\u7eed\u6709\u8bf7\u5171\u540c\u4f5c\u8005\u6269\u5c55\u5185\u5bb9\u7684\u8ba1\u5212\uff0c\u5982\u613f\u610f\u8d21\u732e\u8bf7\u8054\u7cfb\u6211\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#check-point","title":"Check Point","text":"

    \u5927\u4e00\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u4e13\u5fc3\u5b66\u4e13\u4e1a\u8bfe \u5927\u4e8c\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u8fdb\u7ec4\uff0c\u5b66\u4f1apytorch\uff0c\u8bad\u8fc7\u4e00\u4e9b\u5e38\u7528\u7684\u6a21\u578b \u5927\u4e09\u6691\u5047\u7ed3\u675f\u65f6\uff1a\u4ea7\u51fa\u4e00\u4f5c\u6216\u5171\u4e00\u8bba\u6587

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_14","title":"\u6211\u8981\u4e0d\u8981\u627e\u4e2d\u4ecb\uff1f","text":"

    \u4e0d\u8981\u3002 \u539f\u56e0\u4e00\uff1aCS\u7684\u5728\u7ebf\u514d\u8d39\u8d44\u6599\u8db3\u591f\u4f7f\u7528 \u539f\u56e0\u4e8c\uff1a\u4e2d\u4ecb\u7684\u4fe1\u606f\u66f4\u65b0\u901f\u5ea6\u8d76\u4e0d\u4e0aCS\u5b66\u79d1\u7684\u53d1\u5c55\u901f\u5ea6

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_15","title":"\u6211\u7533\u8bf7\u53ef\u4ee5\u53c2\u8003\u54ea\u4e9b\u8d44\u6599\uff1f","text":"

    \u7533\u8bf7MS - \u5317\u7f8e\u7684CS master Home - Open CS Application - \u9664\u5317\u7f8e\u5916\u7684\u5176\u5b83CS master Global CS (global-cs-application.github.io) - \u4e00\u4ea9\u4e09\u5206\u5730/\u5bc4\u6258\u5bb6\u56ed\u7b49\u8bba\u575b - CC98\u4e0a\u6bcf\u4e00\u5e74CS\u7684\u98de\u8dc3\u624b\u518c

    \u7533\u8bf7PhD - \u6b27\u7f8eNLP\u5708\u5bf9PhD\u7533\u8bf7\u7684\u5efa\u8bae https://github.com/zhijing-jin/nlp-phd-global-equality - \u4e86\u89e3\u5b66\u79d1\u4f18\u52bf\u5b66\u6821\u548c\u5bfc\u5e08 CSRankings: Computer Science Rankings - \u6ce8\u518c\u4e00\u4e2aTwitter\u8d26\u53f7\uff0c\u5f00\u59cb\u5173\u6ce8NLP\u5708\u7684PhD\u548cAP\uff0c\u5404\u79cd\u7533\u8bf7\u673a\u4f1a\u4ed6\u4eec\u90fd\u4f1a\u5c3d\u5feb\u53d1\u5e03\u7684\u3002\u6bd4\u5982\u4f60\u53ef\u4ee5\u5148\u4eceAndrew Ng\u3001Christopher Manning\u3001Geoffrey Hinton\u8fd9\u79cd\u8001\u6559\u6388\u5173\u6ce8\u8d77\uff0c\u7136\u540e\u5173\u6ce8\u4ed6\u4eec\u7684\u5173\u6ce8\u8fd9\u6837\u6765\u641e\u3002 - \u5173\u6ce8\u4e00\u4ea9\u4e09\u5206\u5730/CC98/\u4e00\u4e9b\u5fae\u4fe1\u516c\u4f17\u53f7/\u77e5\u4e4e\u7684\u62db\u751f\u4fe1\u606f

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_16","title":"\u6295\u9012\u6691\u7814\u6ce8\u610f\u4e8b\u9879","text":"

    \u6d41\u7a0b\u540c\u7533\u8bf7PhD \u5df2\u7ecf\u719f\u8bc6\u7684\u5bfc\u5e08\u63a8\u8350\u662f\u6700\u5feb\u7684\uff1b\u5426\u5219\u5c31\u81ea\u5df1\u6d77\u6295\uff0c\u6295\u53d1\u5e03\u8fc7\u62db\u751f\u5e7f\u544a\u6216\u4e3b\u9875\u8868\u660e\u6b63\u5728\u62db\u751f\u7684\u8001\u5e08\u662f\u6700\u5feb\u7684\u3002\u6709\u7684\u65f6\u5019\u53ef\u4ee5\u5c1d\u8bd5\u6295\u8ba4\u8bc6\u7684PhD\uff0c\u56e0\u4e3a\u6691\u7814\u671f\u95f4\u5927\u90e8\u5206\u60c5\u51b5\u8fd8\u662f\u8ddf\u7740PhD\u6253\u5de5\u3002 \u5982\u679c\u8001\u5e08\u7ed9\u4f60\u7684\u8d23\u4efb\u6bd4\u8f83\u91cd\uff0c\u4e14\u4f60\u6709\u6bd4\u8f83\u597d\u7684\u5de5\u4f5c\u73af\u5883\uff0c\u6211\u8ba4\u4e3a\u7ebf\u4e0a\u7ebf\u4e0b\u533a\u522b\u4e0d\u5927\u3002 \u60f3\u53bb\u5317\u7f8e\u5c31\u5957\u5317\u7f8e\uff0c\u6211\u89c9\u5f97\u6700\u597d\u4e0d\u8981\u627e\u8df3\u677f\uff0c\u6709\u5317\u7f8e\u7684\u7ebf\u4e0a\u6691\u7814\u4e5f\u5f88\u597d\uff0c\u53ea\u8981\u662f\u4f60\u4e00\u4f5c\uff0c\u65f6\u957f6\u4e2a\u6708\u4ee5\u4e0a\uff0c\u6bcf\u5468\u6c47\u62a5\u8fdb\u5ea6\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_17","title":"\u6295\u9012\u5b9e\u4e60\u6ce8\u610f\u4e8b\u9879","text":"

    \u9700\u8981\u5b9e\u4e60 iff \u4f60\u6253\u7b97\u627e\u5de5or\u8bfb\u5b8c\u7855\u58eb\u627e\u5de5\uff0c\u7533\u8bf7\u5b66\u672f\u7c7bms\u548cPhD\u7684\u8bdd\uff0c\u5b9e\u4e60\u4e0d\u5f3a\u6c42\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#-xuan-insrgithubio","title":"- \ud83c\udff3\ufe0f\u200d\ud83c\udf08 \u603b\u89c8 - \u54b8\u9c7c\u6684\u7684\u4ee3\u7801\u7a7a\u95f4 (xuan-insr.github.io) \u627e\u6691\u671f\u5b9e\u4e60\u548c\u79cb\u62db\u7684\u7ecf\u9a8c\u5e16","text":"

    http://www-cc98-org-s.webvpn.zju.edu.cn:8001/topic/4950730

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#_18","title":"\u5173\u4e8e\u7b14\u8005&\u8054\u7cfb\u7b14\u8005","text":"

    \u7b14\u8005\u4f30\u8ba1\u662f\u4ece\u82f1\u8bed\u4e13\u4e1a\u8f6cNLP\u89c4\u5212\u6700\u4e0d\u987a\u3001\u8fdb\u5ea6\u6700\u66f2\u6298\u7684\u4e00\u4e2a\u3002\u8fd9\u4efd\u6587\u6863\u4e0d\u662f\u4ec0\u4e48\u6210\u529f\u7ecf\u9a8c\u5206\u4eab\uff0c\u6211\u5e76\u4e0d\u6210\u529f\uff0c\u53ea\u662f\u60f3\u628a\u6211\u8e29\u8fc7\u7684\u5751\u544a\u8bc9\u540e\u4eba\uff0c\u5e0c\u671b\u5c11\u6709\u4eba\u91cd\u8e48\u6211\u7684\u8986\u8f99\u3002\u6211\u89c9\u5f97\u6211\u7684\u9ad8\u4e2d\u548c\u672c\u79d1\u8fc7\u5f97\u592a\u574e\u5777\u4e86\uff0c\u771f\u8bda\u5730\u60f3\u5e2e\u52a9\u5b66\u5f1f\u5b66\u59b9\uff0c\u5e0c\u671b\u4f60\u4eec\u4e00\u5207\u987a\u5229\u3002\u8bfb\u8005\u53ef\u4ee5\u4ee5\u6211\u4f5c\u4e3a\u57fa\u51c6\uff0c\u5728\u56db\u5e74\u540e\u4e0d\u80fd\uff08\u5f53\u7136\u5982\u679c\u65e9\u505a\u89c4\u5212\uff0c\u4e00\u76f4\u5728\u52aa\u529b\uff0c\u4e5f\u4e0d\u4f1a\uff09\u6bd4\u6211\u66f4\u5dee\u3002\u6bd5\u7adf\u4e00\u6761\u8def\u8d70\u7684\u4eba\u591a\u4e86\uff0c\u540e\u4eba\u4e00\u5b9a\u662f\u8981\u8d8a\u8d70\u8d8a\u987a\u7684\u3002

    \u5982\u6709\u5efa\u8bae\u6216\u7591\u95ee\u8bf7\u901a\u8fc7\u90ae\u4ef6\u8054\u7cfb\u6211 RuoxiNing@outlook.com\u3002

    "},{"location":"docs/4-opinion/plan/zju_ling_cs/#recommended-readings","title":"Recommended Readings","text":""},{"location":"docs/4-opinion/tools/","title":"Introducing my tools! \u6211\u7684\u5de5\u5177\u7bb1\uff01","text":"

    :material-circle-edit-outline: \u7ea6 47 \u4e2a\u5b57

    \u8bb0\u5f55\u4e00\u70b9\u597d\u7528\u7684\u5de5\u5177

    "},{"location":"docs/4-opinion/tools/#contents","title":"Contents \u76ee\u5f55","text":""},{"location":"docs/4-opinion/tools/#_1","title":"\u96f6\u6563\u5de5\u5177","text":"

    \u96f6\u6563\u7684\u5c31\u653e\u5728\u8fd9\u91cc

    "},{"location":"docs/4-opinion/tools/#_2","title":"\u5728\u7ebf\u6253\u65f6\u95f4\u8f74\u5de5\u5177","text":"

    https://judes.me/lrc_editor/

    "},{"location":"docs/4-opinion/tools/howtocite/","title":"How to cite elegantly?","text":"

    :material-circle-edit-outline: \u7ea6 17 \u4e2a\u5b57

    "},{"location":"docs/4-opinion/tools/howtocite/#which-format","title":"Which format?","text":""},{"location":"docs/4-opinion/tools/howtocite/#in-text-citation","title":"In-text citation","text":""},{"location":"docs/4-opinion/tools/howtocite/#references","title":"References","text":""},{"location":"docs/4-opinion/tools/howtocite/#tools","title":"Tools","text":"

    ... But the best tool is by hand

    "},{"location":"docs/4-opinion/tools/notes/","title":"\u5bf9\u7b14\u8bb0\u5de5\u5177\u548c\u4fe1\u606f\u8bb0\u5f55\u7684\u601d\u8003","text":"

    :material-circle-edit-outline: \u7ea6 423 \u4e2a\u5b57 :fontawesome-solid-code: 3 \u884c\u4ee3\u7801 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f

    "},{"location":"docs/4-opinion/tools/notes/#_2","title":"\u4e3a\u4ec0\u4e48\u8981\u5199\u8fd9\u4e9b\u7b14\u8bb0","text":"

    \u672c\u6765\u60f3\u5199\u591a\u4e00\u70b9\u7684\uff0c\u4f46\u662f\u592a\u61d2\u4e86

    "},{"location":"docs/4-opinion/tools/notes/#_3","title":"\u7b14\u8bb0\u5de5\u5177\uff1f","text":"

    \u5bf9\u6211\u6765\u8bf4\u4e00\u4e2a\u5b8c\u5168\u9762\u5411\u8fc7\u7a0b\u7684 -> \u4e00\u4e2a\u5b8c\u5168\u9762\u5411\u5bf9\u8c61\u7684

    \u6bd4\u5982 notion \u662f\u9762\u5411\u6d41\u7a0b\u7684

    \u800c\u5982\u679c\u8981\u6709\u7ed3\u6784\u5199\u4f5c\uff0c\u5c31\u7528 mkdocs

    "},{"location":"docs/4-opinion/tools/notes/#notionobsidian","title":"\u9009\u62e9Notion\u548cObsidian","text":"

    \u5148\u5199\u4e00\u4e2a\u7b80\u5355\u7684\u7ed3\u8bba

    \u4f18\u70b9/\u5de5\u5177 Notion Obsidian \u8bed\u6cd5 \u81ea\u5df1\u7684\u4e00\u5957\u8bed\u6cd5\uff0c\u90e8\u5206\u662fmarkdown \u7eafmarkdown \u4e66\u5199\u901f\u5ea6 \u6162 \u5feb \u6587\u6863\u6574\u9f50\u7a0b\u5ea6 \u9ad8 \u4f4e \u90e8\u7f72\u5230mkdocs\u96be\u6613 \u6613\uff0c\u53ef\u76f4\u63a5\u7528 \u96be\uff0c\u9700\u8c03\u6574\u5f88\u591a\u683c\u5f0f \u5bfc\u51fa\u4e2d\u6587\u652f\u6301\u7a0b\u5ea6 \u53ea\u6709\u4e09\u79cd\u5b57\u4f53\uff0c\u90e8\u5206\u4e2d\u6587\u7f3a\u5b57 \u5b57\u4f53\u591a\uff0c\u652f\u6301\u6bd4\u8f83\u597d

    \u76ee\u524d\u6211\u9009\u62e9\u7684 workflow: \u5b8c\u5168\u629b\u5f03 Ob \u4e86\uff01

    graph TD\n    \u542c\u5199 --> Notion \n    Notion -- \u6709\u65f6\u95f4 --> mkdocs\n
    "},{"location":"docs/4-opinion/tools/notes/#_4","title":"\u6587\u732e\u7ba1\u7406\u5de5\u5177","text":"

    TODO

    \u5176\u5b9e\u4ed3\u5e93\u91cc\u672c\u6587\u4ef6\u5939\u4e0b\u7684asset\u91cc\u73b0\u5728\u6709\u4e2a\u600e\u4e48\u914d\u7f6ezotero\u7684ppt\uff0c\u592a\u61d2\u6ca1\u65f6\u95f4\u6574\u8fc7\u6765\uff0c\u53ef\u4ee5\u5148\u53bb\u4ed3\u5e93\u91cc\u627e\u627eorz

    "},{"location":"docs/4-opinion/tools/notes/#_5","title":"\u8bba\u6587\u7b14\u8bb0","text":"

    TODO

    "},{"location":"docs/4-opinion/tools/notes/#todolist","title":"TODOlist\uff1f","text":"

    \u5bf9\u6211\u6765\u8bf4\u4e5f\u9700\u8981\u4e00\u4e2a\u9762\u5411\u8fc7\u7a0b\u7684\uff08\u60f3\u5230\u9700\u8981\u505a\u6240\u4ee5\u8bb0\u4e0b\u6765\u7684\u6a21\u7cca\u4efb\u52a1\uff09+ \u4e00\u4e2a\u9762\u5411\u5bf9\u8c61\u7684\uff08\u4e00\u4e2a\u6709\u660e\u786e\u8d77\u6b62\u65f6\u95f4\u7684\u3001\u7ed3\u675f\u6807\u5fd7\u7684\u4efb\u52a1\uff09\u3002

    \u524d\u8005\u6211\u5e0c\u671b\u662f\u4e00\u4e2a\u53ef\u4ee5\u65e0\u9650\u6269\u5c55\u7684 list\uff0c\u5e76\u4e14\u5141\u8bb8\u6dfb\u52a0\u5404\u79cd sublist -> \u4e00\u4e2a\u5f88\u8212\u670d\u7684 markdown \u7f16\u8f91\u5668\u5373\u53ef\u3002

    \u540e\u8005\u5219\u6700\u597d\u6709\u5929\u3001\u5468\u3001\u6708\u7b49 view \u53ef\u4ee5\u770b\u4efb\u52a1\u7684 availability\u3002

    \u6211\u73b0\u5728\u7684\u65b9\u6cd5

    "},{"location":"docs/5-life/","title":"C'est la vie","text":"

    :material-circle-edit-outline: \u7ea6 4 \u4e2a\u5b57

    "},{"location":"docs/5-life/portfolio/","title":"Portfolio for CMU METALS Application","text":"

    :material-circle-edit-outline: \u7ea6 80 \u4e2a\u5b57

    Hi there! \ud83d\udc4b

    This site is a temporary portfolio for CMU METALS application.

    "},{"location":"docs/5-life/portfolio/#frontend-works","title":"Frontend Works","text":"Glyph

    Gun violence in US visualization

    "},{"location":"docs/5-life/portfolio/#graphic-design","title":"Graphic Design","text":"Calendar Card1 Card2 Card3

    logo

    "},{"location":"docs/5-life/annual-summary/","title":"Annual Summary \u5e74\u5ea6\u603b\u7ed3","text":"

    :material-circle-edit-outline: \u7ea6 10 \u4e2a\u5b57

    "},{"location":"docs/5-life/annual-summary/#contents","title":"Contents \u76ee\u5f55","text":""},{"location":"docs/5-life/annual-summary/2024/","title":"2024","text":"

    :material-circle-edit-outline: \u7ea6 967 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f

    Never believe in anything that claims to bring you success, never, never, never.

    We are what we talk about every day. Talking about math and science and technology makes us full of math and science and technology. Talking about the school administration fills us with nothing but only makes rule adaptors. Talking about unserious entertainment chores makes us trivial characters. Talking about the name of technologies instead of the real details and ideas behind them makes us only excited at the thoughts of 'I will learn/am learning this technology soon!' and become distracted suddenly after clicking into a post or a video about it.

    The topic of rules and policies also reminds me of the story of a senior professor who works on computational syntax in the school of international studies at my undergrad school, who ended his 10-year career here and joined another school of a similar (or slightly lower) ranking in Shanghai this year. I saw in his annual summary a sentence going like, in the next 10 years I plan to deal less with the administration materials and procedures but to put the stress on the research that I am really fond of; now given this change in my career, this goal seems pretty at hand.

    I sneered for sharing the same feeling with this prof. After joining UWaterloo, I felt that it was the first time in a long time that I was cared for by people around (administrators, profs, colleagues) as an ordinary student -- not because I was doing anything excellent -- in fact, I lagged behind my peers too much. And this is the reason why I should tell myself from time to time, that feeling well for now does not mean feeling well for good. Don't trust your feelings cause it does not lead you to the goal.

    To be specific in my researches -- I am mainly in (or to say, leading?) 3 researches this year, and none of them finally yields any paper. Sarcastically, another research that I am not leading was accepted fluently by a top conference (I sincerely thank the talented first author and other helpful co-workers who made the acceptance of this work so undoubtful on the meanwhile of critizing my unintelligence).

    I reflected a lot from the rest 3 research on why they currently failed (at least according to my criteria). The first research is a stupid (sorry) benchmark, whose birth now appears too reckless to me -- I was too slow to catch up with the user demands so now few people are using it. I think I will hereby say that I will not make a benchmark unless I desperately feel that a great number of people, or a few but important people, are or will be in need of it, or that I will be the only person who can make it across the world and during the following at least 10 years. Besides, my poor code and data management at the beginning of the year also led to several pitfalls which took me a great amount of time to fix, so now I would like to set up rules for myself, that is to always use unchangeable data ID to identify data pieces and to always consider the searching efficiency when designing the data structure, and to always think of reusing codes (thus I should maintain them more with oop structures). For the rest two projects which are on syntax and multimodal information encoding, I always felt that I didn't know how to introduce them to others esp. my roommates -- always commented that I had no improvement on the models and thus my research was of no use. Okay, I have no words to refute so how to refute will be one of the important questions that I will address in my papers.

    Here should have been another paragraph about my another research. It was such a painful experience collaborating with those collaborators that I don't want to recall and write it down here. If you are interested, let's talk about it privately.

    I spent much time pondering on choosing the industry or academia, some time looking for an internship, and little time submitting applications, and got response from none. I browsed several posts discussing the career planning for PhDs in the middle of which I found a website open-sourcing the salaries of employed professors from each Canadian university, with their real name. I am a bit shocked by the mere salaries of full professors. A solution to this question also desperately awaits in the following year.

    I also traveled a lot and watched a lot of musicals and operas this year (if you are interested in my recommendations, I am working on a list of my favorite musical works), but again I think I should talk about them less and less, since we will become what we talk about. Let's make our conversations full of technologies and ideas that will nurture our knowledge and thoughts.

    Anyway, my primary new year's resolution for 2025 is that,

    to have a paper such that, whenever people talk about this research area, they think of me; and whenever they think of me, they think of my paper.

    This will be the foundation of anything else.

    Besides, I hope I can have time to

    It was the most determined year and it was the most confused year, and it will be the most confused year and it will be the most determined year. I'm ready to see.

    "},{"location":"docs/5-life/read-watch-listen/","title":"Read, Watch, Listen \u4e66\u5f71\u97f3","text":"

    :material-circle-edit-outline: \u7ea6 14 \u4e2a\u5b57

    "},{"location":"docs/5-life/read-watch-listen/#my-top-10-updating","title":"My Top 10 (Updating)","text":""},{"location":"docs/5-life/read-watch-listen/#contents","title":"Contents","text":""},{"location":"docs/5-life/read-watch-listen/music-theory/","title":"\u4e50\u7406","text":"

    :material-circle-edit-outline: \u7ea6 3094 \u4e2a\u5b57 :material-clock-time-two-outline: \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 10 \u5206\u949f

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_2","title":"\u6982\u8ff0","text":"

    \u4e00\u4e9b\u7269\u7406\u6982\u5ff5

    \u4e50\u7406\u7684\u57fa\u7840\u89c4\u5219\u6709\u4e09\u6761

    \u4ee5\u53ca\u4ee5\u6b64\u5ef6\u4f38\u7684\u51e0\u6761\u89c4\u5219

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_3","title":"\u58f0\u97f3","text":"

    !!! \ud83d\udca1 TODO: \u8fd9\u4e2a\u663e\u793a\u9891\u7387\u7684\u662f\u4ec0\u4e48\u5de5\u5177\uff1f

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_4","title":"\u7eaf\u97f3","text":"

    \u53ea\u5305\u542b\u4e00\u79cd\u9891\u7387\u7684\u97f3\u79f0\u4e3a\u7eaf\u97f3\u3002

    \u591a\u79cd\u9891\u7387\u590d\u5408\u5728\u4e00\u8d77\u7684\u97f3\u79f0\u4e3a\u590d\u5408\u97f3\u3002

    \u5b9e\u9645\u6f14\u594f\u4e2d\uff0c\u4e00\u822c\u6bd4\u5982\u6f14\u594f\u67d0\u9891\u7387\u7684\u97f3\u65f6\uff0c\u4e5f\u4f1a\u540c\u65f6\u4ea7\u751f2\u500d\u9891\u7387\uff08\u7b2c2\u6cdb\u97f3\uff0c\u57fa\u97f3\uff09\u30013\u500d\u9891\u7387\uff08\u7b2c3\u6cdb\u97f3\uff09\u2026\u7b49\u97f3\u3002\u8fd9\u662f\u7531\u4e8e\u58f0\u97f3\u5728\u7a7a\u6c14\u4e2d\u4f20\u64ad\u65f6\u53cd\u5c04\uff0c\u53cd\u5c04\u540e\u7684\u6ce2\u5f62\u4f1a\u4e0e\u539f\u6ce2\u5f62\u53e0\u52a0\u4ea7\u751fN\u500d\u6cdb\u97f3\u3002\u6bcf\u4e2a\u4e50\u5668\u7684\u97f3\u8272\u4e0d\u540c\uff0c\u672c\u8d28\u4e0a\u662f\u5b83\u4eec\u7684\u6cdb\u97f3\u7684\u632f\u5e45\u4e0e\u57fa\u97f3\u4e0d\u540c\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_5","title":"\u94a2\u7434","text":""},{"location":"docs/5-life/read-watch-listen/music-theory/#_6","title":"\u5c0f\u63d0\u7434","text":"

    \u51cf\u5f31\u5e45\u5ea6\u6ca1\u6709\u94a2\u7434\u5927\uff0c\u6240\u4ee5\u6bd4\u94a2\u7434\u5c16\u9510\uff08\u56e0\u4e3a\u9891\u7387\u8d8a\u9ad8\u8d8a\u5c16\u9510\uff09

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_7","title":"\u53cc\u7c27\u7ba1","text":"

    \u7b2c2\u6cdb\u97f3\u6bd4\u57fa\u97f3\u5927

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_8","title":"\u97f3\u5f8b","text":"

    \u97f3\u5f8b\u53ef\u4ee5\u8ba4\u4e3a\u662f\u6307\u4e00\u79cd\u201c\u9009\u62e9\u54ea\u4e9b\u9891\u7387\u6765\u4f5c\u4e3a\u4e00\u4ef6\u4e50\u5668\u7684\u97f3\u201d\u8fd9\u79cd\u89c4\u5219\u6216\u4ee5\u6b64\u9009\u51fa\u6765\u7684\u4e00\u7ec4\u9891\u7387\u3002\u5982\u679c\u5177\u4f53\u4e00\u70b9\u6765\u8bb2\uff0c\u4e50\u5668\u53ef\u4ee5\u62bd\u8c61\u6210\u4e00\u7ec4\u957f\u5ea6\u4e0d\u540c\u7684\u5f26\uff0c\u7531\u4e8e\u957f\u5ea6\u4e0d\u540c\u6240\u4ee5\u53d1\u51fa\u4e0d\u540c\u9891\u7387\u7684\u97f3\uff0c\u800c\u4e50\u5668\u8bbe\u8ba1\u8005\u6700\u5173\u5fc3\u7684\u95ee\u9898\u5c31\u662f\u600e\u6837\u8bbe\u8ba1\u8fd9\u7ec4\u5f26\u957f\uff08\u8fd9\u7ec4\u9891\u7387\uff09\uff0c\u4ee5\u4f7f\u53d1\u51fa\u7684\u9891\u7387\u6700\u7b26\u5408\u542c\u4f17\u5fc3\u4e2d\u90a3\u4e9b\u548c\u8c10\u7684\u97f3\u3002

    \u4e00\u4e2a\u5e38\u8bc6\u662f\uff0c\u4e00\u822c\u9700\u8981\u5dee\u5f02 5% \u53ca\u4ee5\u4e0a\u7684\u4e24\u4e2a\u9891\u7387\uff0c\u53ef\u4ee5\u88ab\u6b63\u5e38\u4eba\u5206\u8fa8\u4e3a\u4e24\u4e2a\u4e0d\u540c\u7684\u97f3\u3002\u6240\u4ee5\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u6700\u5c0f\u5dee\u8ddd\u4e0d\u5fc5\u5c0f\u4e8e\u8fd9\u4e2a\u9891\u7387\u5dee\u3002

    \u5728\u6b64\u989d\u5916\u63d0\u51fa\u4e00\u4e2a\u97f3\u7a0b\u7684\u5b9a\u4e49\uff1a\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u9891\u7387\u4e4b\u5dee\u53eb\u97f3\u7a0b\u3002\u6211\u4eec\u5728\u8fd9\u91cc\u4e3b\u8981\u5173\u5fc3\u7684\u97f3\u7a0b\u662f\u4e00\u4e2a\u516b\u5ea6\u3002

    \u8bbe\u5b9a\u97f3\u5f8b\u7684\u8457\u540d\u505a\u6cd5\u4e3b\u8981\u6709\u4ee5\u4e0b\u4e09\u79cd\uff0c\u4e09\u5206\u635f\u76ca\u6cd5\uff0c\u4e94\u5ea6\u76f8\u751f\u6cd5\uff0c\u548c\u5341\u4e8c\u5e73\u5747\u5f8b\uff0c\u6211\u4eec\u4f9d\u6b21\u4ecb\u7ecd\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_9","title":"\u8c03\u6027","text":"

    \u8c03\u6027\u4e3b\u8981\u5305\u542b\u4e86\u8c03\u9ad8\uff08\u4e3b\u97f3\uff09\u4e0e\u8c03\u5f0f\u4e24\u5927\u65b9\u9762\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_10","title":"\u8c03\u5f0f","text":"

    \u674e\u91cd\u5149\u300a\u57fa\u672c\u4e50\u7406\u901a\u7528\u6559\u7a0b\u300b\u4e2d\u5b9a\u4e49\u8c03\u5f0f\u4e3a

    \u51e0\u4e2a\u97f3\uff08\u4e00\u822c\u4e0d\u8d85\u8fc7\u4e03\u4e2a\uff0c\u4e0d\u5c11\u4e8e\u4e09\u4e2a\uff09\u6309\u7167\u4e00\u5b9a\u7684\u5173\u7cfb\uff08\u9ad8\u4f4e\u5173\u7cfb\u3001\u7a33\u5b9a\u4e0e\u4e0d\u7a33\u5b9a\u7684\u5173\u7cfb\u7b49\uff09\u8054\u7ed3\u5728\u4e00\u8d77\uff0c\u6784\u6210\u4e00\u4e2a\u97f3\u7ec4\u7ec7\uff0c\u5e76\u4ee5\u67d0\u4e00\u4e2a\u97f3\u4e3a\u4e2d\u5fc3\uff0c\u8fd9\u4e2a\u97f3\u7ec4\u7ec7\u5c31\u53eb\u201c\u8c03\u5f0f\u201d\u3002

    \u8c03\u5f0f\u4e4b\u95f4\u7684\u5dee\u5f02\u65e2\u6709\u97f3\uff0c\u4e5f\u6709\u97f3\u7a0b

    e.g. \u5206\u6790\u4e24\u4e2a\u8c03\u6bcf\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u97f3\u7a0b\u5173\u7cfb\u3002

    \u53e6\u4e00\u4e2a\u56de\u7b54\u5219\u8bf4\u533a\u522b\u5728\u4e0e\u4e3b\u97f3\u4e4b\u95f4\u7684\u97f3\u7a0b\u5173\u7cfb\u3002\u5e94\u8be5\u662f\u4e00\u6837\u7684\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_11","title":"\u5173\u7cfb\u5927\u5c0f\u8c03\u548c\u4e94\u5ea6\u5708","text":"

    \u4e0a\u8ff0\u4e24\u4e2a\u8c03\u662f\u5173\u7cfb\u5927\u5c0f\u8c03\uff0c\u4e5f\u5c31\u662f\u53ea\u6709\u5faa\u73af\u987a\u5e8f\u6539\u53d8\u4e86\uff0c\u5347\u964d\u5173\u7cfb\u662f\u76f8\u540c\u7684\u3002\u4ee5\u6b64\u6211\u4eec\u5f97\u5230\u4e00\u4e2a\u4e94\u5ea6\u5708

    \u8fd9\u4e2a\u56fe\u4e0a\u53ef\u4ee5\u5f97\u5230\u7684\u4fe1\u606f\u6709\uff1a

    \u5982\u4f55\u9ad8\u6548\u8bb0\u5fc6\u4e94\u5ea6\u5708\uff1a

    \u4e0a\u534811\u70b9\uff0cFat Cat Go Down And Eat Bread\uff0c\u6240\u4ee5\u4e94\u5ea6\u5708\u4ece11\u70b9\u5f00\u59cb\u987a\u65f6\u9488\u65b9\u5411\u662fFCGDAEB

    \u4e0b\u53486\u70b9\uff0cGo Down And Eat Bread\uff0c\u4ece6\u70b9\u65b9\u5411\u5f00\u59cb\u53c8\u662fGDAEB\uff0c\u7531\u4e8e\u662f\u665a\u4e0a\u6240\u4ee5\u90fd\u8981\u964d\u534a\u97f3

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_12","title":"\u5927\u8c03\u4e0e\u5c0f\u8c03","text":"

    \u4e0a\u8ff0\u4f8b\u5b50\u4e2d\u5f15\u5165\u4e86\u5927\u8c03\u4e0e\u5c0f\u8c03\u7684\u6982\u5ff5\u3002\u4e00\u4e2a\u66f4\u6b63\u5f0f\u7684\u5b9a\u4e49\u5982\u4e0b

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_13","title":"\u8c03\u53f7","text":"

    \u5f53\u628a\u4e0a\u8ff0\u97f3\u7a0b\u5173\u7cfb\u5957\u5165\u4e00\u4e2a\u7528\u4efb\u610f\u4e3b\u97f3\u5f00\u59cb\u7684\u97f3\u8282\uff0c\u5c31\u4f1a\u51fa\u73b0\u5e26\u5404\u79cd\u5347\u964d\u53f7\u7684\u8c03\u6027\uff0c\u6bcf\u79cd\u6709\u4e00\u4e2a\u8c03\u53f7\u6765\u547d\u540d\u3002

    \u8c03\u53f7\u7684\u4e00\u4e2a\u8bb0\u5fc6\u89c4\u5219\u662f

    \u53d7\u9650\u4e8e\u4ee5\u524d\u7684\u5f8b\u5236\u548c\u6bcf\u4e2a\u97f3\u9891\u7387\u4e4b\u95f4\u7684\u6bd4\u4f8b\u5173\u7cfb\uff0c\u4ee5\u524d\u662f\u65e0\u6cd5\u968f\u610f\u7ad9\u6362\u8c03\u6027\u7684\uff0c\u56e0\u4e3a\u5982\u679c\u8f6c\u6362\uff0c\u97f3\u7b26\u4e4b\u95f4\u7684\u6bd4\u4f8b\u5c31\u4e0e\u4e4b\u524d\u4e0d\u4e00\u6837\u4e86\u3002\u4f46\u56e0\u4e3a\u6709\u5341\u4e8c\u5e73\u5747\u5f8b\uff0c\u8f6c\u8c03\u53d8\u5f97\u968f\u610f\u3002

    \u4e0a\u8ff0\u8ba8\u8bba\u7684\u4e94\u5ea6\u5708\u548c\u5927\u5c0f\u8c03\u662f\u7406\u8bba\u5f97\u51fa\u7684\uff0c\u53ef\u80fd\u4e5f\u53ef\u4ee5\u79f0\u4e3a\u81ea\u7136\u97f3\u9636\u8c03\u5f0f\uff0c\u5f85\u8003\u8bc1\u3002\u4e0b\u9762\u6765\u4ecb\u7ecd\u4e00\u4e9b\u5386\u53f2\u4e0a\u5e38\u7528\u7684\u7ecf\u5178\u8c03\u5f0f\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#7","title":"7\u79cd\u4e2d\u53e4\u8c03\u5f0f\uff08\u6559\u4f1a\u8c03\u5f0f\uff09","text":"\u6559\u4f1a\u8c03\u5f0f \u97f3\u540d \u534a\u97f3\u95f4\u9694 \u7279\u70b9 Ionian\u5927 CDEFGAB 2212221 \u5927\u8c03\uff0c\u542c\u8d77\u6765\u660e\u6717\u5f00\u9614 Dorian DEFGABC 2122212 \u6c11\u65cf\u97f3\u4e50\uff0c\u5e38\u7528\u4e8e\u6e38\u620f\u548c\u7535\u5f71\u97f3\u4e50 Phrygian EFGABCD 1222122 \u5c0f\u4e8c\u5ea6\u7684Phrygian\u8c03\u5f0f\u542c\u8d77\u6765\u6c89\u91cd\uff0c\u5e38\u7528\u4e8e\u60b2\u5267\u7535\u5f71\u97f3\u4e50 Lydian FGABCDE 2221221 \u6ca1\u6709\u7eaf\u56db\u5ea6\u7684Lydian\u8c03\u5f0f\u9065\u8fdc\u6d69\u701a\uff0c\u6709\u79d1\u5e7b\u611f\uff0c\u5e38\u7528\u4e8e\u79d1\u5e7b\u7535\u5f71\u97f3\u4e50\u3002 Mixoly GABCDEF 2212212 \u6bd4\u5927\u8c03\u91cd\u53e0\u7387\u9ad8\uff08\u5177\u4f53\u91cd\u53e0\u7387\u7684\u8ba1\u7b97\u53ef\u4ee5\u89c1\u4e0b\u65b9\u5e16\u5b50\uff09\uff0c\u4e14\u660e\u6717\u751f\u52a8\u7684Mixoly\u5e38\u7528\u84dd\u8c03\u548c\u786c\u6838\u6447\u6eda Aeolian\u5c0f ABCDEFG 2122122 \u67d4\u548c\u6697\u6de1 Locrian BCDEFGA 1221222 \u6ca1\u6709\u7eaf\u4e94\u5ea6\u7684Locrian\u542c\u8d77\u6765\u6050\u6016\u9ed1\u6697\uff0c\u5e38\u7528\u4e8e\u707e\u96be\u6050\u6016\u7535\u5f71\u97f3\u4e50

    \u4e00\u4e2a\u6559\u4f1a\u8c03\u5f0f\u4e2d\u5177\u6709\u7684\u5ea6\u4e0e\u542c\u611f\u7684\u5173\u7cfb\u5206\u6790\u5982\u8fd9\u4e2a\u5e16\u5b50\u6240\u793a\uff1a

    \u97f3\u7a0b - \u97f3\u4e50\u7406\u8bba\u7684\u79d1\u5b66\u4e0e\u8d77\u6e90 - \u97f3\u4e50\u7406\u8bba\u81ea\u5b66\u5165\u95e8\u57fa\u7840\u6559\u7a0b (pianoabrsm.com)

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_14","title":"\u8c03\u53f7\u4e0e\u60c5\u7eea\u8272\u5f69\u7684\u5173\u7cfb","text":"

    \u81ea\u7136\u97f3\u9636\u5404\u8c03\u5f0f\u4e0e\u60c5\u7eea\u8272\u5f69\u7684\u5173\u7cfb\u3002\u5f88\u6709\u610f\u601d

    \u6211\u7684\u4e2a\u4eba\u89c2\u70b9\uff08TODO \u5f85\u66f4\u65b0\uff09

    \u8c03\u5f0f \u8272\u5f69 \u610f\u8c61 C \u5927\u8c03 C \u5c0f\u8c03 D \u5927\u8c03 \u91d1\u8272 \u91d1\u78a7\u8f89\u714c\u7684\u5bab\u6bbf D \u5c0f\u8c03 E \u5927\u8c03 E \u5c0f\u8c03 F \u5927\u8c03 F \u5c0f\u8c03 \u58a8\u84dd\u8272 \u9ed1\u4e91\u5bc6\u5e03\u6d77\u6d6a\u7ffb\u6d8c G \u5927\u8c03 G \u5c0f\u8c03 A \u5927\u8c03 A \u5c0f\u8c03 \u51b0\u5ddd\u84dd \u707f\u70c2\u9633\u5149\u4e0b\u95ea\u8000\u7684\u51b0\u5ddd B \u5927\u8c03 B \u5c0f\u8c03"},{"location":"docs/5-life/read-watch-listen/music-theory/#_15","title":"\u548c\u58f0\u7406\u8bba","text":"

    \u62cd\u97f3\u90fd\u662f\u548c\u58f0\uff0c\u4f46\u662f\u548c\u58f0\u4e0d\u4e00\u5b9a\u4ea7\u751f\u62cd\u97f3\uff0c\u56e0\u4e3a\u8d85\u51fa\u4eba\u8033\u53ef\u4ee5\u542c\u5230\u7684\u9891\u7387\u7684\u4e0d\u7b97\u62cd\u97f3\uff0c\u4e0d\u540c\u4e50\u5668\u53d1\u51fa\u7684\u4e5f\u4e0d\u53eb\u62cd\u97f3\uff0c\u540c\u65f6\u62cd\u97f3\u4e5f\u4e25\u683c\u8981\u6c42\u6240\u6709\u97f3\u7684\u9891\u7387\u8d77\u59cb\u4f4d\u7f6e\u4e25\u683c\u5bf9\u9f50\uff0c\u800c\u548c\u58f0\u53ea\u8981\u6709\u540c\u65f6\u53d1\u58f0\u7684\u65f6\u523b\u5373\u53ef\u3002

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_16","title":"\u548c\u58f0\u4e0e\u548c\u8c10\u7a0b\u5ea6\u7684\u5173\u7cfb","text":"

    \u9996\u5148\u6709\u76f8\u90bb\u4e24\u4e2a\u97f3\u4e4b\u95f4\u7684\u9891\u7387\u6bd4\u7ea6\u4e3a 1.06\uff08\u8bb0\u4e3ap\uff09\u3002\u5404\u4e2a\u97f3\u7a0b\u7684\u9891\u7387\u6bd4\uff08\u5373\uff0c\u76f8\u8ddd\u67d0\u4e2a\u97f3\u7a0b\u7684\u4f4e\u97f3\u4e0e\u9ad8\u97f3\u9891\u7387\u4e4b\u6bd4\uff09\u5219\u53ef\u4ee5\u7531\u5176\u97f3\u6570t\u6309\u516c\u5f0f\u7b97\u5f97 \\(1/2^{2t/12} = 1/06^{-2t}\\) \uff0c\u5176\u4e2d\uff0c\u7b49\u5f0f\u5de6\u8fb9\u662f\uff0c\u7b49\u5f0f\u53f3\u8fb9\u662f

    \u4e8e\u662f\u5f97\u5230\u7684\u6240\u6709\u5173\u7cfb\uff08\u5e76\u7ecf\u8fc7\u5b9e\u9a8c\uff09\u5f97\u5230\u4e00\u4e2a\u7ecf\u9a8c\u8868\u683c\u3002\u8fd9\u4e2a\u8868\u683c\u5e94\u8be5\u6700\u65e9\u662f\u7531\u516c\u5143\u524d\u6bd5\u8fbe\u54e5\u62c9\u65af\u5f97\u51fa\u7684\uff0c\u4ed6\u8868\u8ff0\u4e3a\uff1a\u4e24\u4e2a\u97f3\u7684\u7434\u5f26\u957f\u4e4b\u6bd4\u7684\u6700\u5927\u516c\u7ea6\u6570\u8d8a\u5c0f\uff0c\u4e24\u4e2a\u97f3\u540c\u65f6\u5f39\u594f\u5c31\u8d8a\u548c\u8c10\u3002\uff08\u5982\u679c\u56de\u5fc6\u6211\u4eec\u4e0a\u9762\u8ba8\u8bba\u7684\u6cdb\u97f3\uff0c\u6cdb\u97f3\u91cd\u53e0\u6bd4\u4f8b\u8d8a\u9ad8\u5c31\u8d8a\u548c\u8c10\uff09

    \u5341\u4e8c\u5e73\u5747\u5f8b\u97f3\u9ad8\u53c2\u8003\u7ebf\uff1a

    \u53ef\u67e5\u9605\u7684\u548c\u8c10\u4e0e\u4e0d\u548c\u8c10\u8868\u683c\uff1a

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_17","title":"\u4f34\u594f","text":"

    \u6bcf\u79cd\u8c03\u5f0f\u53ef\u91c7\u7528\u7684\u548c\u5f26\u79cd\u7c7b\uff0c\u53ef\u4ee5\u7528\u4ee5\u4e0b\u8868\u683c\u6765\u67e5\u9605\u3002

    \u4f34\u594f\u4e0d\u4e00\u5b9a\u662f\u548c\u5f26\u4e2d\u6240\u6709\u97f3\u4e00\u8d77\u5f39\uff0c\u4e5f\u53ef\u4ee5\u62c6\u89e3\u3002\u5e38\u89c1\u7684\u62c6\u89e3\u6cd5\u6709

    \u4e09\u548c\u5f26\u8f6c\u4f4d TODO

    \u6bd4\u5982\u6709\u4e00\u4e2a\u4e09\u548c\u5f26CEG\uff0c\u79f0\u4e3a\u539f\u4f4d\uff0c\u5c06C\u53d8\u6210\u9ad8\u516b\u5ea6\u7684C\uff0c\u79f0\u4e3a\u7b2c\u4e00\u8f6c\u4f4d\uff0c\u5728\u7b2c\u4e00\u8f6c\u4f4d\u57fa\u7840\u4e0a\u5c06E\u53d8\u6210\u9ad8\u516b\u5ea6\u7684E\uff0c\u79f0\u4e3a\u7b2c\u4e8c\u8f6c\u4f4d\u3002

    \u7ec8\u6b62\u5f0f TODO

    \u4e0d\u5b8c\u5168\u7ec8\u6b62\u5f0f TODO

    \u4e03\u548c\u5f26 TODO

    \u548c\u5f26 - \u97f3\u4e50\u7406\u8bba\u7684\u79d1\u5b66\u4e0e\u8d77\u6e90 - \u97f3\u4e50\u7406\u8bba\u81ea\u5b66\u5165\u95e8\u57fa\u7840\u6559\u7a0b (pianoabrsm.com)

    "},{"location":"docs/5-life/read-watch-listen/music-theory/#_18","title":"\u53c2\u8003\u8d44\u6599","text":""},{"location":"docs/5-life/read-watch-listen/musicals/","title":"Musicals","text":"

    :material-circle-edit-outline: \u7ea6 7 \u4e2a\u5b57

    Musical Recommendations

    "},{"location":"docs/5-life/read-watch-listen/musicals/#austrian-german-musicals","title":"Austrian & German Musicals","text":"

    TODO

    "}]} \ No newline at end of file diff --git a/sitemap.xml.gz b/sitemap.xml.gz index 529fe3b61fe458d8532e729a3890458b26954f33..0bf7dffe553b249f97f34a25b57259111d554a1b 100644 GIT binary patch delta 14 VcmdnZwwsMrzMF%ibR(-7GXNhj1Ev4~ delta 14 VcmdnZwwsMrzMF%?e