Merge a158c8bbf2 into dad0a3fd95

* Sync zh and zh-hant versions

* Update the list of contributors.

* Update time_complexity_simple_example.png

* Reduce size of the RGBA images for zh-hant version.

* Sync the zh-hant version of terminology.md

* Prepare 1.2.0 release

* Update the contributors list.

docs/chapter_preface/about_the_book.md

@@ -30,9 +30,9 @@
 
 ## 致谢
 
-本书在开源社区众多贡献者的共同努力下不断完善。感谢每一位投入时间与精力的撰稿人，他们是（按照 GitHub 自动生成的顺序）：krahets、Gonglja、nuomi1、codingonion、Reanon、justin-tse、hpstory、danielsss、curtishd、night-cruise、S-N-O-R-L-A-X、msk397、gvenusleo、RiverTwilight、gyt95、zhuoqinyue、Zuoxun、mingXta、hello-ikun、khoaxuantu、FangYuan33、GN-Yu、longsizhuo、mgisr、Cathay-Chen、guowei-gong、xBLACKICEx、K3v123、IsChristina、JoseHung、qualifier1024、pengchzn、Guanngxu、QiLOL、L-Super、WSL0809、Slone123c、lhxsm、yuan0221、what-is-me、rongyi、JeffersonHuang、longranger2、theNefelibatas、yuelinxin、xiongsp、nanlei、a16su、cy-by-side、gaofer、malone6、Wonderdch、hongyun-robot、XiaChuerwu、yd-j、bluebean-cloud、iron-irax、he-weilai、Nigh、MolDuM、Phoenix0415、XC-Zero、SamJin98、reeswell、NI-SW、Horbin-Magician、xjr7670、YangXuanyi、DullSword、iStig、qq909244296、jiaxianhua、wenjianmin、keshida、kilikilikid、lclc6、lwbaptx、luluxia、boloboloda、hts0000、gledfish、fbigm、echo1937、szu17dmy、dshlstarr、coderlef、czruby、beintentional、KeiichiKasai、xb534、ElaBosak233、baagod、zhouLion、yishangzhang、yi427、yabo083、weibk、wangwang105、th1nk3r-ing、tao363、4yDX3906、syd168、siqyka、selear、sdshaoda、noobcodemaker、chadyi、lyl625760、lucaswangdev、liuxjerry、0130w、shanghai-Jerry、JackYang-hellobobo、Javesun99、lipusheng、ShiMaRing、FreddieLi、FloranceYeh、Transmigration-zhou、fanchenggang、gltianwen、Dr-XYZ、curly210102、CuB3y0nd、youshaoXG、bubble9um、fanenr、52coder、foursevenlove、KorsChen、ZongYangL、hezhizhen、linzeyan、ZJKung、GaochaoZhu、yang-le、Evilrabbit520、Turing-1024-Lee、Suremotoo、Allen-Scai、Richard-Zhang1019、qingpeng9802、primexiao、nidhoggfgg、1ch0、MwumLi、ZnYang2018、hugtyftg、logan-qiu、psychelzh 和 Keynman 。
+本书在开源社区众多贡献者的共同努力下不断完善。感谢每一位投入时间与精力的撰稿人，他们是（按照 GitHub 自动生成的顺序）：krahets、coderonion、Gonglja、nuomi1、Reanon、justin-tse、hpstory、danielsss、curtishd、night-cruise、S-N-O-R-L-A-X、msk397、gvenusleo、khoaxuantu、RiverTwilight、rongyi、gyt95、zhuoqinyue、K3v123、Zuoxun、mingXta、hello-ikun、FangYuan33、GN-Yu、yuelinxin、longsizhuo、Cathay-Chen、guowei-gong、xBLACKICEx、IsChristina、JoseHung、qualifier1024、QiLOL、pengchzn、Guanngxu、L-Super、WSL0809、Slone123c、lhxsm、yuan0221、what-is-me、theNefelibatas、longranger2、cy-by-side、xiongsp、JeffersonHuang、Transmigration-zhou、magentaqin、Wonderdch、malone6、xiaomiusa87、gaofer、bluebean-cloud、a16su、Shyam-Chen、nanlei、hongyun-robot、Phoenix0415、MolDuM、Nigh、he-weilai、junminhong、mgisr、iron-irax、yd-j、XiaChuerwu、XC-Zero、seven1240、SamJin98、wodray、reeswell、NI-SW、Horbin-Magician、Enlightenus、xjr7670、YangXuanyi、DullSword、boloboloda、iStig、qq909244296、jiaxianhua、wenjianmin、keshida、kilikilikid、lclc6、lwbaptx、liuxjerry、lucaswangdev、lyl625760、hts0000、gledfish、fbigm、echo1937、szu17dmy、dshlstarr、Yucao-cy、coderlef、czruby、bongbongbakudan、beintentional、ZongYangL、ZhongYuuu、luluxia、xb534、bitsmi、ElaBosak233、baagod、zhouLion、yishangzhang、yi427、yabo083、weibk、wangwang105、th1nk3r-ing、tao363、4yDX3906、syd168、steventimes、sslmj2020、smilelsb、siqyka、selear、sdshaoda、Xi-Row、popozhu、nuquist19、noobcodemaker、XiaoK29、chadyi、ZhongGuanbin、shanghai-Jerry、JackYang-hellobobo、Javesun99、lipusheng、BlindTerran、ShiMaRing、FreddieLi、FloranceYeh、iFleey、fanchenggang、gltianwen、goerll、Dr-XYZ、nedchu、curly210102、CuB3y0nd、KraHsu、CarrotDLaw、youshaoXG、bubble9um、fanenr、eagleanurag、LifeGoesOnionOnionOnion、52coder、foursevenlove、KorsChen、hezhizhen、linzeyan、ZJKung、GaochaoZhu、hopkings2008、yang-le、Evilrabbit520、Turing-1024-Lee、thomasq0、Suremotoo、Allen-Scai、Risuntsy、Richard-Zhang1019、qingpeng9802、primexiao、nidhoggfgg、1ch0、MwumLi、martinx、ZnYang2018、hugtyftg、logan-qiu、psychelzh、Keynman、KeiichiKasai 和 0130w。
 
-本书的代码审阅工作由 codingonion、curtishd、Gonglja、gvenusleo、hpstory、justin-tse、khoaxuantu、krahets、night-cruise、nuomi1 和 Reanon 完成（按照首字母顺序排列）。感谢他们付出的时间与精力，正是他们确保了各语言代码的规范与统一。
+本书的代码审阅工作由 coderonion、curtishd、Gonglja、gvenusleo、hpstory、justin-tse、khoaxuantu、krahets、night-cruise、nuomi1、Reanon 和 rongyi 完成（按照首字母顺序排列）。感谢他们付出的时间与精力，正是他们确保了各语言代码的规范与统一。
 
 在本书的创作过程中，我得到了许多人的帮助。
 

docs/index.html

@@ -258,9 +258,9 @@
             <h3>代码审阅者</h3>
             <div class="profile-div">
                 <div class="profile-cell">
-                    <a href="https://github.com/codingonion">
-                        <img class="profile-img" src="assets/avatar/avatar_codingonion.jpg" alt="Reviewer: codingonion" />
-                        <br><b>codingonion</b>
+                    <a href="https://github.com/coderonion">
+                        <img class="profile-img" src="assets/avatar/avatar_coderonion.jpg" alt="Reviewer: coderonion" />
+                        <br><b>coderonion</b>
                         <br><sub>Zig, Rust</sub>
                     </a>
                 </div>

en/docs/chapter_computational_complexity/performance_evaluation.md

@@ -2,10 +2,10 @@
 
 In algorithm design, we pursue the following two objectives in sequence.
 
-1. **Finding a Solution to the Problem**: The algorithm should reliably find the correct solution within the stipulated range of inputs.
+1. **Finding a Solution to the Problem**: The algorithm should reliably find the correct solution within the specified range of inputs.
 2. **Seeking the Optimal Solution**: For the same problem, multiple solutions might exist, and we aim to find the most efficient algorithm possible.
 
-In other words, under the premise of being able to solve the problem, algorithm efficiency has become the main criterion for evaluating the merits of an algorithm, which includes the following two dimensions.
+In other words, under the premise of being able to solve the problem, algorithm efficiency has become the main criterion for evaluating the quality of an algorithm, which includes the following two dimensions.
 
 - **Time efficiency**: The speed at which an algorithm runs.
 - **Space efficiency**: The size of the memory space occupied by an algorithm.
@@ -16,11 +16,11 @@ There are mainly two methods of efficiency assessment: actual testing and theore
 
 ## Actual testing
 
-Suppose we have algorithms `A` and `B`, both capable of solving the same problem, and we need to compare their efficiencies. The most direct method is to use a computer to run these two algorithms and monitor and record their runtime and memory usage. This assessment method reflects the actual situation but has significant limitations.
+Suppose we have algorithms `A` and `B`, both capable of solving the same problem, and we need to compare their efficiencies. The most direct method is to use a computer to run these two algorithms, monitor and record their runtime and memory usage. This assessment method reflects the actual situation, but it has significant limitations.
 
-On one hand, **it's difficult to eliminate interference from the testing environment**. Hardware configurations can affect algorithm performance. For example, algorithm `A` might run faster than `B` on one computer, but the opposite result may occur on another computer with different configurations. This means we would need to test on a variety of machines to calculate average efficiency, which is impractical.
+On one hand, **it's difficult to eliminate interference from the testing environment**. Hardware configurations can affect algorithm performance. For example, an algorithm with a high degree of parallelism is better suited for running on multi-core CPUs, while an algorithm that involves intensive memory operations performs better with high-performance memory. The test results of an algorithm may vary across different machines. This means we would need to test the algorithm on various machines to calculate average efficiency, which is impractical.
 
-On the other hand, **conducting a full test is very resource-intensive**. As the volume of input data changes, the efficiency of the algorithms may vary. For example, with smaller data volumes, algorithm `A` might run faster than `B`, but the opposite might be true with larger data volumes. Therefore, to draw convincing conclusions, we need to test a wide range of input data sizes, which requires significant computational resources.
+On the other hand, **conducting a full test is very resource-intensive**. As the volume of input data changes, the efficiency of the algorithms also changes. For example, with smaller data volumes, algorithm `A` might run faster than `B`, but with larger data volumes, the test results may be the opposite. Therefore, to draw convincing conclusions, we need to test a wide range of input data sizes, which requires excessive computational resources.
 
 ## Theoretical estimation
 
@@ -30,19 +30,20 @@ Complexity analysis reflects the relationship between the time and space resourc
 
 - "Time and space resources" correspond to <u>time complexity</u> and <u>space complexity</u>, respectively.
 - "As the size of input data increases" means that complexity reflects the relationship between algorithm efficiency and the volume of input data.
-- "The trend of growth in time and space" indicates that complexity analysis focuses not on the specific values of runtime or space occupied but on the "rate" at which time or space grows.
+- "The trend of growth in time and space" indicates that complexity analysis focuses not on the specific values of runtime or space occupied, but on the "rate" at which time or space increases.
 
 **Complexity analysis overcomes the disadvantages of actual testing methods**, reflected in the following aspects:
 
+- It does not require actually running the code, making it more environmentally friendly and energy efficient.
 - It is independent of the testing environment and applicable to all operating platforms.
 - It can reflect algorithm efficiency under different data volumes, especially in the performance of algorithms with large data volumes.
 
 !!! tip
 
-    If you're still confused about the concept of complexity, don't worry. We will introduce it in detail in subsequent chapters.
+    If you're still confused about the concept of complexity, don't worry. We will cover it in detail in subsequent chapters.
 
-Complexity analysis provides us with a "ruler" to measure the time and space resources needed to execute an algorithm and compare the efficiency between different algorithms.
+Complexity analysis provides us with a "ruler" to evaluate the efficiency of an algorithm, enabling us to measure the time and space resources required to execute it and compare the efficiency of different algorithms.
 
-Complexity is a mathematical concept and may be abstract and challenging for beginners. From this perspective, complexity analysis might not be the best content to introduce first. However, when discussing the characteristics of a particular data structure or algorithm, it's hard to avoid analyzing its speed and space usage.
+Complexity is a mathematical concept that might be abstract and challenging for beginners. From this perspective, complexity analysis might not be the most suitable topic to introduce first. However, when discussing the characteristics of a particular data structure or algorithm, it's hard to avoid analyzing its speed and space usage.
 
-In summary, it's recommended that you establish a preliminary understanding of complexity analysis before diving deep into data structures and algorithms, **so that you can carry out simple complexity analyses of algorithms**.
+In summary, it is recommended to develop a basic understanding of complexity analysis before diving deep into data structures and algorithms, **so that you can perform complexity analysis on simple algorithms**.

en/docs/chapter_preface/about_the_book.md

@@ -30,9 +30,9 @@ The main content of the book is shown in the figure below.
 
 ## Acknowledgements
 
-This book is continuously improved with the joint efforts of many contributors from the open-source community. Thanks to each writer who invested their time and energy, listed in the order generated by GitHub: krahets, codingonion, nuomi1, Gonglja, Reanon, justin-tse, danielsss, hpstory, S-N-O-R-L-A-X, night-cruise, msk397, gvenusleo, RiverTwilight, gyt95, zhuoqinyue, Zuoxun, Xia-Sang, mingXta, FangYuan33, GN-Yu, IsChristina, xBLACKICEx, guowei-gong, Cathay-Chen, mgisr, JoseHung, qualifier1024, pengchzn, Guanngxu, longsizhuo, L-Super, what-is-me, yuan0221, lhxsm, Slone123c, WSL0809, longranger2, theNefelibatas, xiongsp, JeffersonHuang, hongyun-robot, K3v123, yuelinxin, a16su, gaofer, malone6, Wonderdch, xjr7670, DullSword, Horbin-Magician, NI-SW, reeswell, XC-Zero, XiaChuerwu, yd-j, iron-irax, huawuque404, MolDuM, Nigh, KorsChen, foursevenlove, 52coder, bubble9um, youshaoXG, curly210102, gltianwen, fanchenggang, Transmigration-zhou, FloranceYeh, FreddieLi, ShiMaRing, lipusheng, Javesun99, JackYang-hellobobo, shanghai-Jerry, 0130w, Keynman, psychelzh, logan-qiu, ZnYang2018, MwumLi, 1ch0, Phoenix0415, qingpeng9802, Richard-Zhang1019, QiLOL, Suremotoo, Turing-1024-Lee, Evilrabbit520, GaochaoZhu, ZJKung, linzeyan, hezhizhen, ZongYangL, beintentional, czruby, coderlef, dshlstarr, szu17dmy, fbigm, gledfish, hts0000, boloboloda, iStig, jiaxianhua, wenjianmin, keshida, kilikilikid, lclc6, lwbaptx, liuxjerry, lucaswangdev, lyl625760, chadyi, noobcodemaker, selear, siqyka, syd168, 4yDX3906, tao363, wangwang105, weibk, yabo083, yi427, yishangzhang, zhouLion, baagod, ElaBosak233, xb534, luluxia, yanedie, thomasq0, YangXuanyi and th1nk3r-ing.
+This book is continuously improved with the joint efforts of many contributors from the open-source community. Thanks to each writer who invested their time and energy, listed in the order generated by GitHub: krahets, coderonion, Gonglja, nuomi1, Reanon, justin-tse, hpstory, danielsss, curtishd, night-cruise, S-N-O-R-L-A-X, msk397, gvenusleo, khoaxuantu, RiverTwilight, rongyi, gyt95, zhuoqinyue, K3v123, Zuoxun, mingXta, hello-ikun, FangYuan33, GN-Yu, yuelinxin, longsizhuo, Cathay-Chen, guowei-gong, xBLACKICEx, IsChristina, JoseHung, qualifier1024, QiLOL, pengchzn, Guanngxu, L-Super, WSL0809, Slone123c, lhxsm, yuan0221, what-is-me, theNefelibatas, longranger2, cy-by-side, xiongsp, JeffersonHuang, Transmigration-zhou, magentaqin, Wonderdch, malone6, xiaomiusa87, gaofer, bluebean-cloud, a16su, Shyam-Chen, nanlei, hongyun-robot, Phoenix0415, MolDuM, Nigh, he-weilai, junminhong, mgisr, iron-irax, yd-j, XiaChuerwu, XC-Zero, seven1240, SamJin98, wodray, reeswell, NI-SW, Horbin-Magician, Enlightenus, xjr7670, YangXuanyi, DullSword, boloboloda, iStig, qq909244296, jiaxianhua, wenjianmin, keshida, kilikilikid, lclc6, lwbaptx, liuxjerry, lucaswangdev, lyl625760, hts0000, gledfish, fbigm, echo1937, szu17dmy, dshlstarr, Yucao-cy, coderlef, czruby, bongbongbakudan, beintentional, ZongYangL, ZhongYuuu, luluxia, xb534, bitsmi, ElaBosak233, baagod, zhouLion, yishangzhang, yi427, yabo083, weibk, wangwang105, th1nk3r-ing, tao363, 4yDX3906, syd168, steventimes, sslmj2020, smilelsb, siqyka, selear, sdshaoda, Xi-Row, popozhu, nuquist19, noobcodemaker, XiaoK29, chadyi, ZhongGuanbin, shanghai-Jerry, JackYang-hellobobo, Javesun99, lipusheng, BlindTerran, ShiMaRing, FreddieLi, FloranceYeh, iFleey, fanchenggang, gltianwen, goerll, Dr-XYZ, nedchu, curly210102, CuB3y0nd, KraHsu, CarrotDLaw, youshaoXG, bubble9um, fanenr, eagleanurag, LifeGoesOnionOnionOnion, 52coder, foursevenlove, KorsChen, hezhizhen, linzeyan, ZJKung, GaochaoZhu, hopkings2008, yang-le, Evilrabbit520, Turing-1024-Lee, thomasq0, Suremotoo, Allen-Scai, Risuntsy, Richard-Zhang1019, qingpeng9802, primexiao, nidhoggfgg, 1ch0, MwumLi, martinx, ZnYang2018, hugtyftg, logan-qiu, psychelzh, Keynman, KeiichiKasai and 0130w.
 
-The code review work for this book was completed by codingonion, Gonglja, gvenusleo, hpstory, justin‐tse, khoaxuantu, krahets, night-cruise, nuomi1, and Reanon (listed in alphabetical order). Thanks to them for their time and effort, ensuring the standardization and uniformity of the code in various languages.
+The code review work for this book was completed by coderonion, Gonglja, gvenusleo, hpstory, justin‐tse, khoaxuantu, krahets, night-cruise, nuomi1, Reanon and rongyi (listed in alphabetical order). Thanks to them for their time and effort, ensuring the standardization and uniformity of the code in various languages.
 
 Throughout the creation of this book, numerous individuals provided invaluable assistance, including but not limited to:
 

en/docs/index.html

@@ -258,9 +258,9 @@
             <h3>Code reviewers</h3>
             <div class="profile-div">
                 <div class="profile-cell">
-                    <a href="https://github.com/codingonion">
-                        <img class="profile-img" src="../assets/avatar/avatar_codingonion.jpg" alt="Reviewer: codingonion" />
-                        <br><b>codingonion</b>
+                    <a href="https://github.com/coderonion">
+                        <img class="profile-img" src="../assets/avatar/avatar_coderonion.jpg" alt="Reviewer: coderonion" />
+                        <br><b>coderonion</b>
                         <br><sub>Zig, Rust</sub>
                     </a>
                 </div>

mkdocs.yml

@@ -9,7 +9,7 @@ site_dir: site
 repo_name: krahets/hello-algo
 repo_url: https://github.com/krahets/hello-algo
 edit_uri: tree/main/docs
-version: 1.1.0
+version: 1.2.0
 
 # Copyright
 copyright: Copyright &copy; 2024 krahets<br>The website content is licensed under <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a>

zh-hant/codes/c/chapter_stack_and_queue/array_deque.c

@@ -111,16 +111,29 @@ int popLast(ArrayDeque *deque) {
     return num;
 }
 
+/* 返回陣列用於列印 */
+int *toArray(ArrayDeque *deque, int *queSize) {
+    *queSize = deque->queSize;
+    int *res = (int *)calloc(deque->queSize, sizeof(int));
+    int j = deque->front;
+    for (int i = 0; i < deque->queSize; i++) {
+        res[i] = deque->nums[j % deque->queCapacity];
+        j++;
+    }
+    return res;
+}
+
 /* Driver Code */
 int main() {
     /* 初始化佇列 */
     int capacity = 10;
+    int queSize;
     ArrayDeque *deque = newArrayDeque(capacity);
     pushLast(deque, 3);
     pushLast(deque, 2);
     pushLast(deque, 5);
     printf("雙向佇列 deque = ");
-    printArray(deque->nums, deque->queSize);
+    printArray(toArray(deque, &queSize), queSize);
 
     /* 訪問元素 */
     int peekFirstNum = peekFirst(deque);
@@ -131,18 +144,18 @@ int main() {
     /* 元素入列 */
     pushLast(deque, 4);
     printf("元素 4 佇列尾入列後 deque = ");
-    printArray(deque->nums, deque->queSize);
+    printArray(toArray(deque, &queSize), queSize);
     pushFirst(deque, 1);
     printf("元素 1 佇列首入列後 deque = ");
-    printArray(deque->nums, deque->queSize);
+    printArray(toArray(deque, &queSize), queSize);
 
     /* 元素出列 */
     int popLastNum = popLast(deque);
     printf("佇列尾出列元素 = %d ，佇列尾出列後 deque= ", popLastNum);
-    printArray(deque->nums, deque->queSize);
+    printArray(toArray(deque, &queSize), queSize);
     int popFirstNum = popFirst(deque);
     printf("佇列首出列元素 = %d ，佇列首出列後 deque= ", popFirstNum);
-    printArray(deque->nums, deque->queSize);
+    printArray(toArray(deque, &queSize), queSize);
 
     /* 獲取佇列的長度 */
     int dequeSize = size(deque);

zh-hant/codes/c/chapter_stack_and_queue/array_queue.c

@@ -74,10 +74,23 @@ int pop(ArrayQueue *queue) {
     return num;
 }
 
+/* 返回陣列用於列印 */
+int *toArray(ArrayQueue *queue, int *queSize) {
+    *queSize = queue->queSize;
+    int *res = (int *)calloc(queue->queSize, sizeof(int));
+    int j = queue->front;
+    for (int i = 0; i < queue->queSize; i++) {
+        res[i] = queue->nums[j % queue->queCapacity];
+        j++;
+    }
+    return res;
+}
+
 /* Driver Code */
 int main() {
     /* 初始化佇列 */
     int capacity = 10;
+    int queSize;
     ArrayQueue *queue = newArrayQueue(capacity);
 
     /* 元素入列 */
@@ -87,7 +100,7 @@ int main() {
     push(queue, 5);
     push(queue, 4);
     printf("佇列 queue = ");
-    printArray(queue->nums, queue->queSize);
+    printArray(toArray(queue, &queSize), queSize);
 
     /* 訪問佇列首元素 */
     int peekNum = peek(queue);
@@ -96,7 +109,7 @@ int main() {
     /* 元素出列 */
     peekNum = pop(queue);
     printf("出列元素 pop = %d ，出列後 queue = ", peekNum);
-    printArray(queue->nums, queue->queSize);
+    printArray(toArray(queue, &queSize), queSize);
 
     /* 獲取佇列的長度 */
     int queueSize = size(queue);
@@ -111,7 +124,7 @@ int main() {
         push(queue, i);
         pop(queue);
         printf("第 %d 輪入列 + 出列後 queue = ", i);
-        printArray(queue->nums, queue->queSize);
+        printArray(toArray(queue, &queSize), queSize);
     }
 
     // 釋放記憶體

zh-hant/docs/chapter_appendix/terminology.md

@@ -50,6 +50,7 @@
 | front of the queue             | 队首           | 佇列首         |
 | rear of the queue              | 队尾           | 佇列尾         |
 | hash table                     | 哈希表         | 雜湊表         |
+| hash set                       | 哈希集合       | 雜湊集合       |
 | bucket                         | 桶             | 桶             |
 | hash function                  | 哈希函数       | 雜湊函式       |
 | hash collision                 | 哈希冲突       | 雜湊衝突       |

zh-hant/docs/chapter_preface/about_the_book.md

@@ -30,9 +30,9 @@
 
 ## 致謝
 
-本書在開源社群眾多貢獻者的共同努力下不斷完善。感謝每一位投入時間與精力的撰稿人，他們是（按照 GitHub 自動生成的順序）：krahets、Gonglja、nuomi1、codingonion、Reanon、justin-tse、hpstory、danielsss、curtishd、night-cruise、S-N-O-R-L-A-X、msk397、gvenusleo、RiverTwilight、gyt95、zhuoqinyue、Zuoxun、mingXta、hello-ikun、khoaxuantu、FangYuan33、GN-Yu、longsizhuo、mgisr、Cathay-Chen、guowei-gong、xBLACKICEx、K3v123、IsChristina、JoseHung、qualifier1024、pengchzn、Guanngxu、QiLOL、L-Super、WSL0809、Slone123c、lhxsm、yuan0221、what-is-me、rongyi、JeffersonHuang、longranger2、theNefelibatas、yuelinxin、xiongsp、nanlei、a16su、cy-by-side、gaofer、malone6、Wonderdch、hongyun-robot、XiaChuerwu、yd-j、bluebean-cloud、iron-irax、he-weilai、Nigh、MolDuM、Phoenix0415、XC-Zero、SamJin98、reeswell、NI-SW、Horbin-Magician、xjr7670、YangXuanyi、DullSword、iStig、qq909244296、jiaxianhua、wenjianmin、keshida、kilikilikid、lclc6、lwbaptx、luluxia、boloboloda、hts0000、gledfish、fbigm、echo1937、szu17dmy、dshlstarr、coderlef、czruby、beintentional、KeiichiKasai、xb534、ElaBosak233、baagod、zhouLion、yishangzhang、yi427、yabo083、weibk、wangwang105、th1nk3r-ing、tao363、4yDX3906、syd168、siqyka、selear、sdshaoda、noobcodemaker、chadyi、lyl625760、lucaswangdev、liuxjerry、0130w、shanghai-Jerry、JackYang-hellobobo、Javesun99、lipusheng、ShiMaRing、FreddieLi、FloranceYeh、Transmigration-zhou、fanchenggang、gltianwen、Dr-XYZ、curly210102、CuB3y0nd、youshaoXG、bubble9um、fanenr、52coder、foursevenlove、KorsChen、ZongYangL、hezhizhen、linzeyan、ZJKung、GaochaoZhu、yang-le、Evilrabbit520、Turing-1024-Lee、Suremotoo、Allen-Scai、Richard-Zhang1019、qingpeng9802、primexiao、nidhoggfgg、1ch0、MwumLi、ZnYang2018、hugtyftg、logan-qiu、psychelzh 和 Keynman 。
+本書在開源社群眾多貢獻者的共同努力下不斷完善。感謝每一位投入時間與精力的撰稿人，他們是（按照 GitHub 自動生成的順序）：krahets、coderonion、Gonglja、nuomi1、Reanon、justin-tse、hpstory、danielsss、curtishd、night-cruise、S-N-O-R-L-A-X、msk397、gvenusleo、khoaxuantu、RiverTwilight、rongyi、gyt95、zhuoqinyue、K3v123、Zuoxun、mingXta、hello-ikun、FangYuan33、GN-Yu、yuelinxin、longsizhuo、Cathay-Chen、guowei-gong、xBLACKICEx、IsChristina、JoseHung、qualifier1024、QiLOL、pengchzn、Guanngxu、L-Super、WSL0809、Slone123c、lhxsm、yuan0221、what-is-me、theNefelibatas、longranger2、cy-by-side、xiongsp、JeffersonHuang、Transmigration-zhou、magentaqin、Wonderdch、malone6、xiaomiusa87、gaofer、bluebean-cloud、a16su、Shyam-Chen、nanlei、hongyun-robot、Phoenix0415、MolDuM、Nigh、he-weilai、junminhong、mgisr、iron-irax、yd-j、XiaChuerwu、XC-Zero、seven1240、SamJin98、wodray、reeswell、NI-SW、Horbin-Magician、Enlightenus、xjr7670、YangXuanyi、DullSword、boloboloda、iStig、qq909244296、jiaxianhua、wenjianmin、keshida、kilikilikid、lclc6、lwbaptx、liuxjerry、lucaswangdev、lyl625760、hts0000、gledfish、fbigm、echo1937、szu17dmy、dshlstarr、Yucao-cy、coderlef、czruby、bongbongbakudan、beintentional、ZongYangL、ZhongYuuu、luluxia、xb534、bitsmi、ElaBosak233、baagod、zhouLion、yishangzhang、yi427、yabo083、weibk、wangwang105、th1nk3r-ing、tao363、4yDX3906、syd168、steventimes、sslmj2020、smilelsb、siqyka、selear、sdshaoda、Xi-Row、popozhu、nuquist19、noobcodemaker、XiaoK29、chadyi、ZhongGuanbin、shanghai-Jerry、JackYang-hellobobo、Javesun99、lipusheng、BlindTerran、ShiMaRing、FreddieLi、FloranceYeh、iFleey、fanchenggang、gltianwen、goerll、Dr-XYZ、nedchu、curly210102、CuB3y0nd、KraHsu、CarrotDLaw、youshaoXG、bubble9um、fanenr、eagleanurag、LifeGoesOnionOnionOnion、52coder、foursevenlove、KorsChen、hezhizhen、linzeyan、ZJKung、GaochaoZhu、hopkings2008、yang-le、Evilrabbit520、Turing-1024-Lee、thomasq0、Suremotoo、Allen-Scai、Risuntsy、Richard-Zhang1019、qingpeng9802、primexiao、nidhoggfgg、1ch0、MwumLi、martinx、ZnYang2018、hugtyftg、logan-qiu、psychelzh、Keynman、KeiichiKasai 和 0130w。
 
-本書的程式碼審閱工作由 codingonion、curtishd、Gonglja、gvenusleo、hpstory、justin-tse、khoaxuantu、krahets、night-cruise、nuomi1 和 Reanon 完成（按照首字母順序排列）。感謝他們付出的時間與精力，正是他們確保了各語言程式碼的規範與統一。
+本書的程式碼審閱工作由 coderonion、curtishd、Gonglja、gvenusleo、hpstory、justin-tse、khoaxuantu、krahets、night-cruise、nuomi1、Reanon 和 rongyi 完成（按照首字母順序排列）。感謝他們付出的時間與精力，正是他們確保了各語言程式碼的規範與統一。
 
 在本書的創作過程中，我得到了許多人的幫助。
 

zh-hant/docs/index.html

@@ -258,9 +258,9 @@
             <h3>程式碼審閱者</h3>
             <div class="profile-div">
                 <div class="profile-cell">
-                    <a href="https://github.com/codingonion">
-                        <img class="profile-img" src="../assets/avatar/avatar_codingonion.jpg" alt="Reviewer: codingonion" />
-                        <br><b>codingonion</b>
+                    <a href="https://github.com/coderonion">
+                        <img class="profile-img" src="../assets/avatar/avatar_coderonion.jpg" alt="Reviewer: coderonion" />
+                        <br><b>coderonion</b>
                         <br><sub>Zig, Rust</sub>
                     </a>
                 </div>

zh-hant/mkdocs.yml

@@ -9,7 +9,7 @@ docs_dir: ../build/zh-hant/docs
 site_dir: ../site/zh-hant
 # Repository
 edit_uri: tree/main/zh-hant/docs
-version: 1.1.0
+version: 1.2.0
 
 # Configuration
 theme: