Merge 5ec15c4a3e 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_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/chapter_searching/searching_algorithm_revisited.md

@@ -1,28 +1,28 @@
 # Search algorithms revisited
 
-<u>Searching algorithms (searching algorithm)</u> are used to search for one or several elements that meet specific criteria in data structures such as arrays, linked lists, trees, or graphs.
+<u>Searching algorithms (search algorithms)</u> are used to retrieve one or more elements that meet specific criteria within data structures such as arrays, linked lists, trees, or graphs.
 
-Searching algorithms can be divided into the following two categories based on their implementation approaches.
+Searching algorithms can be divided into the following two categories based on their approach.
 
 - **Locating the target element by traversing the data structure**, such as traversals of arrays, linked lists, trees, and graphs, etc.
-- **Using the organizational structure of the data or the prior information contained in the data to achieve efficient element search**, such as binary search, hash search, and binary search tree search, etc.
+- **Using the organizational structure of the data or existing data to achieve efficient element searches**, such as binary search, hash search, binary search tree search, etc.
 
-It is not difficult to notice that these topics have been introduced in previous chapters, so searching algorithms are not unfamiliar to us. In this section, we will revisit searching algorithms from a more systematic perspective.
+These topics were introduced in previous chapters, so they are not unfamiliar to us. In this section, we will revisit searching algorithms from a more systematic perspective.
 
 ## Brute-force search
 
-Brute-force search locates the target element by traversing every element of the data structure.
+A Brute-force search locates the target element by traversing every element of the data structure.
 
-- "Linear search" is suitable for linear data structures such as arrays and linked lists. It starts from one end of the data structure, accesses each element one by one, until the target element is found or the other end is reached without finding the target element.
-- "Breadth-first search" and "Depth-first search" are two traversal strategies for graphs and trees. Breadth-first search starts from the initial node and searches layer by layer, accessing nodes from near to far. Depth-first search starts from the initial node, follows a path until the end, then backtracks and tries other paths until the entire data structure is traversed.
+- "Linear search" is suitable for linear data structures such as arrays and linked lists. It starts from one end of the data structure and accesses each element one by one until the target element is found or the other end is reached without finding the target element.
+- "Breadth-first search" and "Depth-first search" are two traversal strategies for graphs and trees. Breadth-first search starts from the initial node and searches layer by layer (left to right), accessing nodes from near to far. Depth-first search starts from the initial node, follows a path until the end (top to bottom), then backtracks and tries other paths until the entire data structure is traversed.
 
-The advantage of brute-force search is its simplicity and versatility, **no need for data preprocessing and the help of additional data structures**.
+The advantage of brute-force search is its simplicity and versatility, **no need for data preprocessing or the help of additional data structures**.
 
-However, **the time complexity of this type of algorithm is $O(n)$**, where $n$ is the number of elements, so the performance is poor in cases of large data volumes.
+However, **the time complexity of this type of algorithm is $O(n)$**, where $n$ is the number of elements, so the performance is poor with large data sets.
 
 ## Adaptive search
 
-Adaptive search uses the unique properties of data (such as order) to optimize the search process, thereby locating the target element more efficiently.
+An Adaptive search uses the unique properties of data (such as order) to optimize the search process, thereby locating the target element more efficiently.
 
 - "Binary search" uses the orderliness of data to achieve efficient searching, only suitable for arrays.
 - "Hash search" uses a hash table to establish a key-value mapping between search data and target data, thus implementing the query operation.
@@ -30,7 +30,7 @@ Adaptive search uses the unique properties of data (such as order) to optimize t
 
 The advantage of these algorithms is high efficiency, **with time complexities reaching $O(\log n)$ or even $O(1)$**.
 
-However, **using these algorithms often requires data preprocessing**. For example, binary search requires sorting the array in advance, and hash search and tree search both require the help of additional data structures, maintaining these structures also requires extra time and space overhead.
+However, **using these algorithms often requires data preprocessing**. For example, binary search requires sorting the array in advance, and hash search and tree search both require the help of additional data structures. Maintaining these structures also requires more overhead in terms of time and space.
 
 !!! tip
 
@@ -38,11 +38,11 @@ However, **using these algorithms often requires data preprocessing**. For examp
 
 ## Choosing a search method
 
-Given a set of data of size $n$, we can use linear search, binary search, tree search, hash search, and other methods to search for the target element from it. The working principles of these methods are shown in the figure below.
+Given a set of data of size $n$, we can use a linear search, binary search, tree search, hash search, or other methods to retrieve the target element. The working principles of these methods are shown in the figure below.
 
 ![Various search strategies](searching_algorithm_revisited.assets/searching_algorithms.png)
 
-The operation efficiency and characteristics of the aforementioned methods are shown in the following table.
+The characteristics and operational efficiency of the aforementioned methods are shown in the following table.
 
 <p align="center"> Table <id> &nbsp; Comparison of search algorithm efficiency </p>
 
@@ -55,23 +55,23 @@ The operation efficiency and characteristics of the aforementioned methods are s
 | Data preprocessing | /             | Sorting $O(n \log n)$ | Building tree $O(n \log n)$ | Building hash table $O(n)$ |
 | Data orderliness   | Unordered     | Ordered               | Ordered                     | Unordered                  |
 
-The choice of search algorithm also depends on the volume of data, search performance requirements, data query and update frequency, etc.
+The choice of search algorithm also depends on the volume of data, search performance requirements, frequency of data queries and updates, etc.
 
 **Linear search**
 
-- Good versatility, no need for any data preprocessing operations. If we only need to query the data once, then the time for data preprocessing in the other three methods would be longer than the time for linear search.
+- Good versatility, no need for any data preprocessing operations. If we only need to query the data once, then the time for data preprocessing in the other three methods would be longer than the time for a linear search.
 - Suitable for small volumes of data, where time complexity has a smaller impact on efficiency.
-- Suitable for scenarios with high data update frequency, because this method does not require any additional maintenance of the data.
+- Suitable for scenarios with very frequent data updates, because this method does not require any additional maintenance of the data.
 
 **Binary search**
 
-- Suitable for large data volumes, with stable efficiency performance, the worst time complexity being $O(\log n)$.
-- The data volume cannot be too large, because storing arrays requires contiguous memory space.
-- Not suitable for scenarios with frequent additions and deletions, because maintaining an ordered array incurs high overhead.
+- Suitable for larger data volumes, with stable performance and a worst-case time complexity of $O(\log n)$.
+- However, the data volume cannot be too large, because storing arrays requires contiguous memory space.
+- Not suitable for scenarios with frequent additions and deletions, because maintaining an ordered array incurs a lot of overhead.
 
 **Hash search**
 
-- Suitable for scenarios with high query performance requirements, with an average time complexity of $O(1)$.
+- Suitable for scenarios where fast query performance is essential, with an average time complexity of $O(1)$.
 - Not suitable for scenarios needing ordered data or range searches, because hash tables cannot maintain data orderliness.
 - High dependency on hash functions and hash collision handling strategies, with significant performance degradation risks.
 - Not suitable for overly large data volumes, because hash tables need extra space to minimize collisions and provide good query performance.
@@ -80,5 +80,5 @@ The choice of search algorithm also depends on the volume of data, search perfor
 
 - Suitable for massive data, because tree nodes are stored scattered in memory.
 - Suitable for maintaining ordered data or range searches.
-- In the continuous addition and deletion of nodes, the binary search tree may become skewed, degrading the time complexity to $O(n)$.
+- With the continuous addition and deletion of nodes, the binary search tree may become skewed, degrading the time complexity to $O(n)$.
 - If using AVL trees or red-black trees, operations can run stably at $O(\log n)$ efficiency, but the operation to maintain tree balance adds extra overhead.

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);
@@ -156,4 +169,4 @@ int main() {
     delArrayDeque(deque);
 
     return 0;
-}
+}

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);
@@ -111,11 +124,11 @@ 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
     delArrayQueue(queue);
 
     return 0;
-}
+}

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: