diff --git a/.prettierrc b/.prettierrc
deleted file mode 100644
index 5a938ce1..00000000
--- a/.prettierrc
+++ /dev/null
@@ -1,4 +0,0 @@
-{
-  "tabWidth": 4,
-  "useTabs": false
-}
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 00000000..f699e33e
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,16 @@
+FROM python:3.9.0-alpine
+
+RUN pip install -i https://pypi.tuna.tsinghua.edu.cn/simple --upgrade pip
+RUN pip install -i https://pypi.tuna.tsinghua.edu.cn/simple mkdocs-material==9.0.2
+
+WORKDIR /app
+
+COPY codes /app/codes
+COPY docs /app/docs
+COPY mkdocs.yml /app/mkdocs.yml
+
+RUN mkdir ./docs/overrides && mkdocs build
+
+EXPOSE 8000
+
+CMD ["mkdocs", "serve", "-a", "0.0.0.0:8000"]
diff --git a/codes/c/chapter_array_and_linkedlist/array.c b/codes/c/chapter_array_and_linkedlist/array.c
index 11fcb67f..33dc9990 100644
--- a/codes/c/chapter_array_and_linkedlist/array.c
+++ b/codes/c/chapter_array_and_linkedlist/array.c
@@ -74,11 +74,11 @@ int main() {
     int size = 5;
     int arr[5];
     printf("数组 arr = ");
-    PrintArray(arr, size);
+    printArray(arr, size);
 
     int nums[5] = { 1, 3, 2, 5, 4 };
     printf("数组 nums = ");
-    PrintArray(nums, size);
+    printArray(nums, size);
     
     /* 随机访问 */
     int randomNum = randomAccess(nums, size);
@@ -89,17 +89,17 @@ int main() {
     int* res = extend(nums, size, enlarge);
     size += enlarge;
     printf("将数组长度扩展至 8 ，得到 nums = ");
-    PrintArray(res, size);
+    printArray(res, size);
     
     /* 插入元素 */
     insert(res, size, 6, 3);
     printf("在索引 3 处插入数字 6 ，得到 nums = ");
-    PrintArray(res, size);
+    printArray(res, size);
 
     /* 删除元素 */
     removeItem(res, size, 2);
     printf("删除索引 2 处的元素，得到 nums = ");
-    PrintArray(res, size);
+    printArray(res, size);
     
     /* 遍历数组 */
     traverse(res, size);
diff --git a/codes/c/chapter_computational_complexity/worst_best_time_complexity.c b/codes/c/chapter_computational_complexity/worst_best_time_complexity.c
index 531a76e5..e5cee821 100644
--- a/codes/c/chapter_computational_complexity/worst_best_time_complexity.c
+++ b/codes/c/chapter_computational_complexity/worst_best_time_complexity.c
@@ -41,7 +41,7 @@ int main(int argc, char *argv[]) {
         int *nums = randomNumbers(n);
         int index = findOne(nums, n);
         printf("\n数组 [ 1, 2, ..., n ] 被打乱后 = ");
-        PrintArray(nums, n);
+        printArray(nums, n);
         printf("数字 1 的索引为 %d\n", index);
         // 释放堆区内存
         if (nums != NULL) {
diff --git a/codes/c/chapter_sorting/bubble_sort.c b/codes/c/chapter_sorting/bubble_sort.c
index 4a2a24b4..51bab6c6 100644
--- a/codes/c/chapter_sorting/bubble_sort.c
+++ b/codes/c/chapter_sorting/bubble_sort.c
@@ -7,7 +7,7 @@
 #include "../include/include.h"
 
 /* 冒泡排序 */
-void bubble_sort(int nums[], int size) {
+void bubbleSort(int nums[], int size) {
     // 外循环：待排序元素数量为 n-1, n-2, ..., 1
     for (int i = 0; i < size - 1; i++)
     {
@@ -25,7 +25,7 @@ void bubble_sort(int nums[], int size) {
 }
 
 /* 冒泡排序（标志优化）*/
-void bubble_sort_with_flag(int nums[], int size) {
+void bubbleSortWithFlag(int nums[], int size) {
     // 外循环：待排序元素数量为 n-1, n-2, ..., 1
     for (int i = 0; i < size - 1; i++)
     {
@@ -51,14 +51,14 @@ void bubble_sort_with_flag(int nums[], int size) {
 int main() {
     int nums[6] = {4, 1, 3, 1, 5, 2};
     printf("冒泡排序后: ");
-    bubble_sort(nums, 6);
+    bubbleSort(nums, 6);
     for (int i = 0; i < 6; i++)
     {
         printf("%d ", nums[i]);
     }
 
     printf("\n优化版冒泡排序后: ");
-    bubble_sort_with_flag(nums, 6);
+    bubbleSortWithFlag(nums, 6);
     for (int i = 0; i < 6; i++)
     {
         printf("%d ", nums[i]);
diff --git a/codes/c/chapter_tree/binary_tree.c b/codes/c/chapter_tree/binary_tree.c
index 0a2f946a..1eb8e846 100644
--- a/codes/c/chapter_tree/binary_tree.c
+++ b/codes/c/chapter_tree/binary_tree.c
@@ -10,34 +10,33 @@
 int main() {
     /* 初始化二叉树 */
     // 初始化结点
-    TreeNode* n1 = NewTreeNode(1);
-    TreeNode* n2 = NewTreeNode(2);
-    TreeNode* n3 = NewTreeNode(3);
-    TreeNode* n4 = NewTreeNode(4);
-    TreeNode* n5 = NewTreeNode(5);
+    TreeNode* n1 = newTreeNode(1);
+    TreeNode* n2 = newTreeNode(2);
+    TreeNode* n3 = newTreeNode(3);
+    TreeNode* n4 = newTreeNode(4);
+    TreeNode* n5 = newTreeNode(5);
     // 构建引用指向（即指针）
     n1->left = n2;
     n1->right = n3;
     n2->left = n4;
     n2->right = n5;
     printf("初始化二叉树\n");
-    PrintTree(n1);
+    printTree(n1);
 
     /* 插入与删除结点 */
-    TreeNode* P = NewTreeNode(0);
+    TreeNode* P = newTreeNode(0);
     // 在 n1 -> n2 中间插入结点 P
     n1->left = P;
     P->left = n2;
     printf("插入结点 P 后\n");
-    PrintTree(n1);
+    printTree(n1);
 
     // 删除结点 P
     n1->left = n2;
     // 释放内存
     free(P);
     printf("删除结点 P 后\n");
-    PrintTree(n1);
+    printTree(n1);
 
     return 0;
 }
-
diff --git a/codes/c/chapter_tree/binary_tree_bfs.c b/codes/c/chapter_tree/binary_tree_bfs.c
index abad3735..c7b83b91 100644
--- a/codes/c/chapter_tree/binary_tree_bfs.c
+++ b/codes/c/chapter_tree/binary_tree_bfs.c
@@ -52,15 +52,15 @@ int main() {
     // 这里借助了一个从数组直接生成二叉树的函数
     int nums[] = {1, 2, 3, NIL, 5, 6, NIL};
     int size = sizeof(nums) / sizeof(int);
-    TreeNode *root = ArrayToTree(nums, size);
+    TreeNode *root = arrToTree(nums, size);
     printf("初始化二叉树\n");
-    PrintTree(root);
+    printTree(root);
 
     /* 层序遍历 */
     // 需要传入数组的长度
     int *arr = levelOrder(root, &size);
     printf("层序遍历的结点打印序列 = ");
-    PrintArray(arr, size);
+    printArray(arr, size);
 
     return 0;
 }
\ No newline at end of file
diff --git a/codes/c/chapter_tree/binary_tree_dfs.c b/codes/c/chapter_tree/binary_tree_dfs.c
index f72e6687..bafc90fd 100644
--- a/codes/c/chapter_tree/binary_tree_dfs.c
+++ b/codes/c/chapter_tree/binary_tree_dfs.c
@@ -43,10 +43,10 @@ int main() {
     /* 初始化二叉树 */
     // 这里借助了一个从数组直接生成二叉树的函数
     int nums[] = {1, 2, 3, 4, 5, 6, 7};
-    int size = sizeof(nums) / sizt ceof(int);
-    TreeNode *root = ArrayToTree(nums, size);
+    int size = sizeof(nums) / sizeof(int);
+    TreeNode *root = arrToTree(nums, size);
     printf("初始化二叉树\n");
-    PrintTree(root);
+    printTree(root);
 
     /* 前序遍历 */
     // 初始化辅助数组
@@ -54,19 +54,19 @@ int main() {
     size = 0;
     preOrder(root, &size);
     printf("前序遍历的结点打印序列 = ");
-    PrintArray(arr, size);
+    printArray(arr, size);
 
     /* 中序遍历 */
     size = 0;
     inOrder(root, &size);
     printf("中序遍历的结点打印序列 = ");
-    PrintArray(arr, size);
+    printArray(arr, size);
 
     /* 后序遍历 */
     size = 0;
     postOrder(root, &size);
     printf("后序遍历的结点打印序列 = ");
-    PrintArray(arr, size);
+    printArray(arr, size);
 
     return 0;
 }
diff --git a/codes/c/include/include_test.c b/codes/c/include/include_test.c
index baa8e649..602670d6 100644
--- a/codes/c/include/include_test.c
+++ b/codes/c/include/include_test.c
@@ -9,24 +9,24 @@
 void testListNode() {
     int nums[] = {2, 3, 5, 6, 7};
     int size = sizeof(nums) / sizeof(int);
-    ListNode *head = ArrayToLinkedList(nums, size);
-    PrintLinkedList(head);
+    ListNode *head = arrToLinkedList(nums, size);
+    printLinkedList(head);
 
-    ListNode *node = GetListNode(head, 5);
+    ListNode *node = getListNode(head, 5);
     printf("find node: %d\n", node->val);
 }
 
 void testTreeNode() {
     int nums[] = {1, 2, 3, NIL, 5, 6, NIL};
     int size = sizeof(nums) / sizeof(int);
-    TreeNode *root = ArrayToTree(nums, size);
+    TreeNode *root = arrToTree(nums, size);
 
     // print tree
-    PrintTree(root);
+    printTree(root);
 
     // tree to arr
-    int *arr = TreeToArray(root);
-    PrintArray(arr, size);
+    int *arr = treeToArr(root);
+    printArray(arr, size);
 }
 
 int main(int argc, char *argv[]) {
diff --git a/codes/c/include/list_node.h b/codes/c/include/list_node.h
index 5597d210..1845ffaf 100644
--- a/codes/c/include/list_node.h
+++ b/codes/c/include/list_node.h
@@ -22,7 +22,7 @@ struct ListNode {
 // typedef 为 C 语言的关键字，作用是为一种数据类型定义一个新名字
 typedef struct ListNode ListNode;
 
-ListNode *NewListNode(int val) {
+ListNode *newListNode(int val) {
     ListNode *node, *next;
     node = (ListNode *) malloc(sizeof(ListNode));
     node->val = val;
@@ -37,15 +37,15 @@ ListNode *NewListNode(int val) {
  * @return ListNode*
  */
 
-ListNode *ArrayToLinkedList(const int *arr, size_t size) {
+ListNode *arrToLinkedList(const int *arr, size_t size) {
     if (size <= 0) {
         return NULL;
     }
 
-    ListNode *dummy = NewListNode(0);
+    ListNode *dummy = newListNode(0);
     ListNode *node = dummy;
     for (int i = 0; i < size; i++) {
-        node->next = NewListNode(arr[i]);
+        node->next = newListNode(arr[i]);
         node = node->next;
     }
     return dummy->next;
@@ -58,7 +58,7 @@ ListNode *ArrayToLinkedList(const int *arr, size_t size) {
  * @param val
  * @return ListNode*
  */
-ListNode *GetListNode(ListNode *head, int val) {
+ListNode *getListNode(ListNode *head, int val) {
     while (head != NULL && head->val != val) {
         head = head->next;
     }
diff --git a/codes/c/include/print_util.h b/codes/c/include/print_util.h
index fcb0a4ca..a0c3a150 100644
--- a/codes/c/include/print_util.h
+++ b/codes/c/include/print_util.h
@@ -25,7 +25,7 @@ extern "C" {
  * @param arr
  * @param size
  */
-static void PrintArray(int *arr, int size) {
+static void printArray(int *arr, int size) {
     printf("[");
     for (int i = 0; i < size - 1; i++) {
         if (arr[i] != NIL) {
@@ -46,7 +46,7 @@ static void PrintArray(int *arr, int size) {
  *
  * @param head
  */
-static void PrintLinkedList(ListNode *node) {
+static void printLinkedList(ListNode *node) {
     if (node == NULL) {
         return;
     }
@@ -123,7 +123,7 @@ static void printTreeHelper(TreeNode *node, Trunk *prev, bool isLeft) {
  *
  * @param head
  */
-static void PrintTree(TreeNode *root) {
+static void printTree(TreeNode *root) {
     printTreeHelper(root, NULL, false);
 }
 
diff --git a/codes/c/include/tree_node.h b/codes/c/include/tree_node.h
index 4b0e7018..c0438c43 100644
--- a/codes/c/include/tree_node.h
+++ b/codes/c/include/tree_node.h
@@ -25,7 +25,7 @@ struct TreeNode {
 typedef struct TreeNode TreeNode;
 
 
-TreeNode *NewTreeNode(int val) {
+TreeNode *newTreeNode(int val) {
     TreeNode *node;
 
     node = (TreeNode *) malloc(sizeof(TreeNode));
@@ -43,7 +43,7 @@ TreeNode *NewTreeNode(int val) {
  * @param size
  * @return TreeNode *
  */
-TreeNode *ArrayToTree(const int *arr, size_t size) {
+TreeNode *arrToTree(const int *arr, size_t size) {
     if (size <= 0) {
         return NULL;
     }
@@ -53,7 +53,7 @@ TreeNode *ArrayToTree(const int *arr, size_t size) {
     TreeNode **queue;
 
     /* 根结点 */
-    root = NewTreeNode(arr[0]);
+    root = newTreeNode(arr[0]);
     /* 辅助队列 */
     queue = (TreeNode **) malloc(sizeof(TreeNode) * MAX_NODE_SIZE);
     // 队列指针
@@ -68,14 +68,14 @@ TreeNode *ArrayToTree(const int *arr, size_t size) {
         index++;
         if (index < size) {
             if (arr[index] != NIL) {
-                node->left = NewTreeNode(arr[index]);
+                node->left = newTreeNode(arr[index]);
                 queue[rear++] = node->left;
             }
         }
         index++;
         if (index < size) {
             if (arr[index] != NIL) {
-                node->right = NewTreeNode(arr[index]);
+                node->right = newTreeNode(arr[index]);
                 queue[rear++] = node->right;
             }
         }
@@ -91,7 +91,7 @@ TreeNode *ArrayToTree(const int *arr, size_t size) {
  * @param size
  * @return TreeNode *
  */
-int *TreeToArray(TreeNode *root) {
+int *treeToArr(TreeNode *root) {
     if (root == NULL) {
         return NULL;
     }
diff --git a/codes/cpp/include/include.hpp b/codes/cpp/include/include.hpp
index 8e4a8070..03bf9b50 100644
--- a/codes/cpp/include/include.hpp
+++ b/codes/cpp/include/include.hpp
@@ -17,6 +17,8 @@
 #include <unordered_set>
 #include <set>
 #include <random>
+#include <chrono>
+#include <algorithm>
 
 #include "ListNode.hpp"
 #include "TreeNode.hpp"
diff --git a/codes/java/chapter_hashing/array_hash_map.java b/codes/java/chapter_hashing/array_hash_map.java
index 68df1f3b..980a00ab 100644
--- a/codes/java/chapter_hashing/array_hash_map.java
+++ b/codes/java/chapter_hashing/array_hash_map.java
@@ -5,6 +5,7 @@
  */
 
 package chapter_hashing;
+
 import java.util.*;
 
 /* 键值对 int->String */
diff --git a/codes/java/chapter_hashing/hash_map.java b/codes/java/chapter_hashing/hash_map.java
index fe3f822f..47f4823b 100644
--- a/codes/java/chapter_hashing/hash_map.java
+++ b/codes/java/chapter_hashing/hash_map.java
@@ -5,6 +5,7 @@
  */
 
 package chapter_hashing;
+
 import java.util.*;
 import include.*;
 
diff --git a/codes/java/chapter_heap/heap.java b/codes/java/chapter_heap/heap.java
new file mode 100644
index 00000000..1a0c53b9
--- /dev/null
+++ b/codes/java/chapter_heap/heap.java
@@ -0,0 +1,67 @@
+/**
+ * File: my_heap.java
+ * Created Time: 2023-01-07
+ * Author: Krahets (krahets@163.com)
+ */
+
+package chapter_heap;
+
+import include.*;
+import java.util.*;
+
+
+public class heap {
+    public static void testPush(Queue<Integer> heap, int val) {
+        heap.add(val); // 元素入堆
+        System.out.format("\n元素 %d 入堆后\n", val);
+        PrintUtil.printHeap(heap);
+    }
+
+    public static void testPoll(Queue<Integer> heap) {
+        int val = heap.poll(); // 堆顶元素出堆
+        System.out.format("\n堆顶元素 %d 出堆后\n", val);
+        PrintUtil.printHeap(heap);
+    }
+
+    public static void main(String[] args) {
+        /* 初始化堆 */
+        // 初始化小顶堆
+        Queue<Integer> minHeap = new PriorityQueue<>();
+        // 初始化大顶堆（使用 lambda 表达式修改 Comparator 即可）
+        Queue<Integer> maxHeap = new PriorityQueue<>((a, b) -> { return b - a; });
+
+        System.out.println("\n以下测试样例为大顶堆");
+
+        /* 元素入堆 */
+        testPush(maxHeap, 1);
+        testPush(maxHeap, 3);
+        testPush(maxHeap, 2);
+        testPush(maxHeap, 5);
+        testPush(maxHeap, 4);
+
+        /* 获取堆顶元素 */
+        int peek = maxHeap.peek();
+        System.out.format("\n堆顶元素为 %d\n", peek);
+
+        /* 堆顶元素出堆 */
+        testPoll(maxHeap);
+        testPoll(maxHeap);
+        testPoll(maxHeap);
+        testPoll(maxHeap);
+        testPoll(maxHeap);
+
+        /* 获取堆大小 */
+        int size = maxHeap.size();
+        System.out.format("\n堆元素数量为 %d\n", size);
+
+        /* 判断堆是否为空 */
+        boolean isEmpty = maxHeap.isEmpty();
+        System.out.format("\n堆是否为空 %b\n", isEmpty);
+
+        /* 输入列表并建堆 */
+        // 时间复杂度为 O(n) ，而非 O(nlogn)
+        minHeap = new PriorityQueue<>(Arrays.asList(1, 3, 2, 5, 4));
+        System.out.println("\n输入列表并建立小顶堆后");
+        PrintUtil.printHeap(minHeap);
+    }
+}
diff --git a/codes/java/chapter_heap/my_heap.java b/codes/java/chapter_heap/my_heap.java
new file mode 100644
index 00000000..b80ce6d0
--- /dev/null
+++ b/codes/java/chapter_heap/my_heap.java
@@ -0,0 +1,177 @@
+/**
+ * File: my_heap.java
+ * Created Time: 2023-01-07
+ * Author: Krahets (krahets@163.com)
+ */
+
+package chapter_heap;
+
+import include.*;
+import java.util.*;
+
+class MaxHeap {
+    // 使用列表而非数组，这样无需考虑扩容问题
+    private List<Integer> maxHeap;
+
+    /* 构造函数，建立空堆 */
+    public MaxHeap() {
+        maxHeap = new ArrayList<>();
+    }
+
+    /* 构造函数，根据输入列表建堆 */
+    public MaxHeap(List<Integer> nums) {
+        // 所有元素入堆
+        maxHeap = new ArrayList<>(nums);
+        // 堆化除叶结点以外的其他所有结点
+        for (int i = parent(size() - 1); i >= 0; i--) {
+            siftDown(i);
+        }
+    }
+
+    /* 获取左子结点索引 */
+    private int left(int i) {
+        return 2 * i + 1;
+    }
+
+    /* 获取右子结点索引 */
+    private int right(int i) {
+        return 2 * i + 2;
+    }
+
+    /* 获取父结点索引 */
+    private int parent(int i) {
+        return (i - 1) / 2; // 向下整除
+    }
+
+    /* 交换元素 */
+    private void swap(int i, int j) {
+        int a = maxHeap.get(i), 
+            b = maxHeap.get(j),
+            tmp = a;
+        maxHeap.set(i, b);
+        maxHeap.set(j, tmp);
+    }
+
+    /* 获取堆大小 */
+    public int size() {
+        return maxHeap.size();
+    }
+
+    /* 判断堆是否为空 */
+    public boolean isEmpty() {
+        return size() == 0;
+    }
+
+    /* 访问堆顶元素 */
+    public int peek() {
+        return maxHeap.get(0);
+    }
+
+    /* 元素入堆 */
+    public void push(int val) {
+        // 添加结点
+        maxHeap.add(val);
+        // 从底至顶堆化
+        siftUp(size() - 1);
+    }
+
+    /* 从结点 i 开始，从底至顶堆化 */
+    private void siftUp(int i) {
+        while (true) {
+            // 获取结点 i 的父结点
+            int p = parent(i);
+            // 当“越过根结点”或“结点无需修复”时，结束堆化
+            if (p < 0 || maxHeap.get(i) <= maxHeap.get(p))
+                break;
+            // 交换两结点
+            swap(i, p);
+            // 循环向上堆化
+            i = p;
+        }
+    }
+
+    /* 元素出堆 */
+    public int poll() {
+        // 判空处理
+        if (isEmpty())
+            throw new EmptyStackException();
+        // 交换根结点与最右叶结点（即交换首元素与尾元素）
+        swap(0, size() - 1);
+        // 删除结点
+        int val = maxHeap.remove(size() - 1);
+        // 从顶至底堆化
+        siftDown(0);
+        // 返回堆顶元素
+        return val;
+    }
+
+    /* 从结点 i 开始，从顶至底堆化 */
+    private void siftDown(int i) {
+        while (true) {
+            // 判断结点 i, l, r 中值最大的结点，记为 ma
+            int l = left(i), r = right(i), ma = i;
+            if (l < size() && maxHeap.get(l) > maxHeap.get(ma))
+                ma = l;
+            if (r < size() && maxHeap.get(r) > maxHeap.get(ma))
+                ma = r;
+            // 若结点 i 最大或索引 l, r 越界，则无需继续堆化，跳出
+            if (ma == i) break;
+            // 交换两结点
+            swap(i, ma);
+            // 循环向下堆化
+            i = ma;
+        }
+    }
+
+    /* 打印堆（二叉树） */
+    public void print() {
+        Queue<Integer> queue = new PriorityQueue<>((a, b) -> { return b - a; });
+        queue.addAll(maxHeap);
+        PrintUtil.printHeap(queue);
+    }
+}
+
+
+public class my_heap {
+    public static void testPush(MaxHeap maxHeap, int val) {
+        maxHeap.push(val);  // 元素入堆
+        System.out.format("\n添加元素 %d 后\n", val);
+        maxHeap.print();
+    }
+
+    public static void testPoll(MaxHeap maxHeap) {
+        int val = maxHeap.poll(); // 堆顶元素出堆
+        System.out.format("\n出堆元素为 %d\n", val);
+        maxHeap.print();
+    }
+
+    public static void main(String[] args) {
+        /* 初始化大顶堆 */
+        MaxHeap maxHeap = new MaxHeap(Arrays.asList(9, 8, 6, 6, 7, 5, 2, 1, 4, 3, 6, 2));
+        System.out.println("\n输入列表并建堆后");
+        maxHeap.print();
+
+        /* 获取堆顶元素 */
+        int peek = maxHeap.peek();
+        System.out.format("\n堆顶元素为 %d\n", peek);
+
+        /* 元素入堆 */
+        int val = 7;
+        maxHeap.push(val);
+        System.out.format("\n元素 %d 入堆后\n", val);
+        maxHeap.print();
+
+        /* 堆顶元素出堆 */
+        peek = maxHeap.poll();
+        System.out.format("\n堆顶元素 %d 出堆后\n", peek);
+        maxHeap.print();
+
+        /* 获取堆大小 */
+        int size = maxHeap.size();
+        System.out.format("\n堆元素数量为 %d\n", size);
+
+        /* 判断堆是否为空 */
+        boolean isEmpty = maxHeap.isEmpty();
+        System.out.format("\n堆是否为空 %b\n", isEmpty);
+    }
+}
diff --git a/codes/java/chapter_tree/binary_tree_bfs.java b/codes/java/chapter_tree/binary_tree_bfs.java
index 450311d0..ffeb352e 100644
--- a/codes/java/chapter_tree/binary_tree_bfs.java
+++ b/codes/java/chapter_tree/binary_tree_bfs.java
@@ -30,7 +30,7 @@ public class binary_tree_bfs {
     public static void main(String[] args) {
         /* 初始化二叉树 */
         // 这里借助了一个从数组直接生成二叉树的函数
-        TreeNode root = TreeNode.arrToTree(new Integer[] { 1, 2, 3, 4, 5, 6, 7 });
+        TreeNode root = TreeNode.listToTree(Arrays.asList(1, 2, 3, 4, 5, 6, 7));
         System.out.println("\n初始化二叉树\n");
         PrintUtil.printTree(root);
 
diff --git a/codes/java/chapter_tree/binary_tree_dfs.java b/codes/java/chapter_tree/binary_tree_dfs.java
index ad5337f2..9f2d0507 100644
--- a/codes/java/chapter_tree/binary_tree_dfs.java
+++ b/codes/java/chapter_tree/binary_tree_dfs.java
@@ -43,7 +43,7 @@ public class binary_tree_dfs {
     public static void main(String[] args) {
         /* 初始化二叉树 */
         // 这里借助了一个从数组直接生成二叉树的函数
-        TreeNode root = TreeNode.arrToTree(new Integer[] { 1, 2, 3, 4, 5, 6, 7 });
+        TreeNode root = TreeNode.listToTree(Arrays.asList(1, 2, 3, 4, 5, 6, 7));
         System.out.println("\n初始化二叉树\n");
         PrintUtil.printTree(root);
 
diff --git a/codes/java/include/PrintUtil.java b/codes/java/include/PrintUtil.java
index b2593ac1..1ebc45ba 100755
--- a/codes/java/include/PrintUtil.java
+++ b/codes/java/include/PrintUtil.java
@@ -105,10 +105,16 @@ public class PrintUtil {
         }
     }
 
-    public static void printHeap(PriorityQueue<Integer> queue) {
-        Integer[] nums = (Integer[])queue.toArray();
-        TreeNode root = TreeNode.arrToTree(nums);
-        
+    /**
+     * Print a heap (PriorityQueue)
+     * @param queue
+     */
+    public static void printHeap(Queue<Integer> queue) {
+        List<Integer> list = new ArrayList<>(queue);
+        System.out.print("堆的数组表示：");
+        System.out.println(list);
+        System.out.println("堆的树状表示：");
+        TreeNode root = TreeNode.listToTree(list);
         printTree(root);
     }
 }
diff --git a/codes/java/include/TreeNode.java b/codes/java/include/TreeNode.java
index 11d457a1..22a34974 100644
--- a/codes/java/include/TreeNode.java
+++ b/codes/java/include/TreeNode.java
@@ -23,26 +23,27 @@ public class TreeNode {
 
     /**
      * Generate a binary tree given an array
-     * @param arr
+     * @param list
      * @return
      */
-    public static TreeNode arrToTree(Integer[] arr) {
-        if (arr.length == 0)
+    public static TreeNode listToTree(List<Integer> list) {
+        int size = list.size();
+        if (size == 0)
             return null;
         
-        TreeNode root = new TreeNode(arr[0]);
+        TreeNode root = new TreeNode(list.get(0));
         Queue<TreeNode> queue = new LinkedList<>() {{ add(root); }};
         int i = 0;
         while(!queue.isEmpty()) {
             TreeNode node = queue.poll();
-            if (++i >= arr.length) break;
-            if(arr[i] != null) {
-                node.left = new TreeNode(arr[i]);
+            if (++i >= size) break;
+            if (list.get(i) != null) {
+                node.left = new TreeNode(list.get(i));
                 queue.add(node.left);
             }
-            if (++i >= arr.length) break;
-            if(arr[i] != null) {
-                node.right = new TreeNode(arr[i]);
+            if (++i >= size) break;
+            if (list.get(i) != null) {
+                node.right = new TreeNode(list.get(i));
                 queue.add(node.right);
             }
         }
diff --git a/codes/zig/build.zig b/codes/zig/build.zig
index 1a9fb0fb..b9bbddce 100644
--- a/codes/zig/build.zig
+++ b/codes/zig/build.zig
@@ -64,4 +64,59 @@ pub fn build(b: *std.build.Builder) void {
         if (b.args) |args| run_cmd_leetcode_two_sum.addArgs(args);
         const run_step_leetcode_two_sum = b.step("run_leetcode_two_sum", "Run leetcode_two_sum");
         run_step_leetcode_two_sum.dependOn(&run_cmd_leetcode_two_sum.step);
+
+    // Section: "Array"
+        // Source File: "chapter_array_and_linkedlist/array.zig"
+        // Run Command: zig build run_array
+        const exe_array = b.addExecutable("array", "chapter_array_and_linkedlist/array.zig");
+        exe_array.addPackagePath("include", "include/include.zig");
+        exe_array.setTarget(target);
+        exe_array.setBuildMode(mode);
+        exe_array.install();
+        const run_cmd_array = exe_array.run();
+        run_cmd_array.step.dependOn(b.getInstallStep());
+        if (b.args) |args| run_cmd_array.addArgs(args);
+        const run_step_array = b.step("run_array", "Run array");
+        run_step_array.dependOn(&run_cmd_array.step);
+
+    // Section: "LinkedList"
+        // Source File: "chapter_array_and_linkedlist/linked_list.zig"
+        // Run Command: zig build run_linked_list
+        const exe_linked_list = b.addExecutable("linked_list", "chapter_array_and_linkedlist/linked_list.zig");
+        exe_linked_list.addPackagePath("include", "include/include.zig");
+        exe_linked_list.setTarget(target);
+        exe_linked_list.setBuildMode(mode);
+        exe_linked_list.install();
+        const run_cmd_linked_list = exe_linked_list.run();
+        run_cmd_linked_list.step.dependOn(b.getInstallStep());
+        if (b.args) |args| run_cmd_linked_list.addArgs(args);
+        const run_step_linked_list = b.step("run_linked_list", "Run linked_list");
+        run_step_linked_list.dependOn(&run_cmd_linked_list.step);
+
+    // Section: "List"
+        // Source File: "chapter_array_and_linkedlist/list.zig"
+        // Run Command: zig build run_list
+        const exe_list = b.addExecutable("list", "chapter_array_and_linkedlist/list.zig");
+        exe_list.addPackagePath("include", "include/include.zig");
+        exe_list.setTarget(target);
+        exe_list.setBuildMode(mode);
+        exe_list.install();
+        const run_cmd_list = exe_list.run();
+        run_cmd_list.step.dependOn(b.getInstallStep());
+        if (b.args) |args| run_cmd_list.addArgs(args);
+        const run_step_list = b.step("run_list", "Run list");
+        run_step_list.dependOn(&run_cmd_list.step);
+
+        // Source File: "chapter_array_and_linkedlist/my_list.zig"
+        // Run Command: zig build run_my_list
+        const exe_my_list = b.addExecutable("my_list", "chapter_array_and_linkedlist/my_list.zig");
+        exe_my_list.addPackagePath("include", "include/include.zig");
+        exe_my_list.setTarget(target);
+        exe_my_list.setBuildMode(mode);
+        exe_my_list.install();
+        const run_cmd_my_list = exe_my_list.run();
+        run_cmd_my_list.step.dependOn(b.getInstallStep());
+        if (b.args) |args| run_cmd_my_list.addArgs(args);
+        const run_step_my_list = b.step("run_my_list", "Run my_list");
+        run_step_my_list.dependOn(&run_cmd_my_list.step);
 }
diff --git a/codes/zig/chapter_array_and_linkedlist/array.zig b/codes/zig/chapter_array_and_linkedlist/array.zig
new file mode 100644
index 00000000..8c830cf4
--- /dev/null
+++ b/codes/zig/chapter_array_and_linkedlist/array.zig
@@ -0,0 +1,117 @@
+// File: array.zig
+// Created Time: 2023-01-07
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+const inc = @import("include");
+
+// 随机返回一个数组元素
+pub fn randomAccess(nums: []i32) i32 {
+    // 在区间 [0, nums.len) 中随机抽取一个整数
+    var randomIndex = std.crypto.random.intRangeLessThan(usize, 0, nums.len);
+    // 获取并返回随机元素
+    var randomNum = nums[randomIndex];
+    return randomNum;
+}
+
+// 扩展数组长度
+pub fn extend(mem_allocator: std.mem.Allocator, nums: []i32, enlarge: usize) ![]i32 {
+    // 初始化一个扩展长度后的数组
+    var res = try mem_allocator.alloc(i32, nums.len + enlarge);
+    std.mem.set(i32, res, 0);
+    // 将原数组中的所有元素复制到新数组
+    std.mem.copy(i32, res, nums);
+    // 返回扩展后的新数组
+    return res;
+}
+
+// 在数组的索引 index 处插入元素 num
+pub fn insert(nums: []i32, num: i32, index: usize) void {
+    // 把索引 index 以及之后的所有元素向后移动一位
+    var i = nums.len - 1;
+    while (i > index) : (i -= 1) {
+        nums[i] = nums[i - 1];
+    }
+    // 将 num 赋给 index 处元素
+    nums[index] = num;
+}
+
+// 删除索引 index 处元素
+pub fn remove(nums: []i32, index: usize) void {
+    // 把索引 index 之后的所有元素向前移动一位
+    var i = index;
+    while (i < nums.len - 1) : (i += 1) {
+        nums[i] = nums[i + 1];
+    }
+}
+
+// 遍历数组
+pub fn traverse(nums: []i32) void {
+    var count: i32 = 0;
+    // 通过索引遍历数组
+    var i: i32 = 0;
+    while (i < nums.len) : (i += 1) {
+        count += 1;
+    }
+    count = 0;
+    // 直接遍历数组
+    for (nums) |_| {
+        count += 1;
+    }
+}
+
+// 在数组中查找指定元素
+pub fn find(nums: []i32, target: i32) i32 {
+    for (nums) |num, i| {
+        if (num == target) return @intCast(i32, i);
+    }
+    return -1;
+}
+
+// Driver Code
+pub fn main() !void {
+    // 初始化数组
+    const size: i32 = 5;
+    var arr = [_]i32{0} ** size;
+    std.debug.print("数组 arr = ", .{});
+    inc.PrintUtil.printArray(i32, &arr);
+
+    var array = [_]i32{ 1, 3, 2, 5, 4 };
+    std.debug.print("\n数组 nums = ", .{});
+    inc.PrintUtil.printArray(i32, &array);
+
+    // 随机访问
+    var randomNum = randomAccess(&array);
+    std.debug.print("\n在 nums 中获取随机元素 {}", .{randomNum});
+
+    // 长度扩展
+    var known_at_runtime_zero: usize = 0;
+    var nums: []i32 = array[known_at_runtime_zero..array.len];
+    var mem_arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
+    defer mem_arena.deinit();
+    const mem_allocator = mem_arena.allocator();
+    nums = try extend(mem_allocator, nums, 3);
+    std.debug.print("\n将数组长度扩展至 8 ，得到 nums = ", .{});
+    inc.PrintUtil.printArray(i32, nums);
+
+    // 插入元素
+    insert(nums, 6, 3);
+    std.debug.print("\n在索引 3 处插入数字 6 ，得到 nums = ", .{});
+    inc.PrintUtil.printArray(i32, nums);
+
+    // 删除元素
+    remove(nums, 2);
+    std.debug.print("\n删除索引 2 处的元素，得到 nums = ", .{});
+    inc.PrintUtil.printArray(i32, nums);
+
+    // 遍历数组
+    traverse(nums);
+
+    // 查找元素
+    var index = find(nums, 3);
+    std.debug.print("\n在 nums 中查找元素 3 ，得到索引 = {}\n", .{index});
+
+    const getchar = try std.io.getStdIn().reader().readByte();
+    _ = getchar;
+}
+
diff --git a/codes/zig/chapter_array_and_linkedlist/linked_list.zig b/codes/zig/chapter_array_and_linkedlist/linked_list.zig
new file mode 100644
index 00000000..fbaa3f8d
--- /dev/null
+++ b/codes/zig/chapter_array_and_linkedlist/linked_list.zig
@@ -0,0 +1,85 @@
+// File: linked_list.zig
+// Created Time: 2023-01-07
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+const inc = @import("include");
+
+// 在链表的结点 n0 之后插入结点 P
+pub fn insert(n0: ?*inc.ListNode(i32), P: ?*inc.ListNode(i32)) void {
+    var n1 = n0.?.next;
+    n0.?.next = P;
+    P.?.next = n1;
+}
+
+// 删除链表的结点 n0 之后的首个结点
+pub fn remove(n0: ?*inc.ListNode(i32)) void {
+    if (n0.?.next == null) return;
+    // n0 -> P -> n1
+    var P = n0.?.next;
+    var n1 = P.?.next;
+    n0.?.next = n1;
+}
+
+// 访问链表中索引为 index 的结点
+pub fn access(node: ?*inc.ListNode(i32), index: i32) ?*inc.ListNode(i32) {
+    var head = node;
+    var i: i32 = 0;
+    while (i < index) : (i += 1) {
+        head = head.?.next;
+        if (head == null) return null;
+    }
+    return head;
+}
+
+// 在链表中查找值为 target 的首个结点
+pub fn find(node: ?*inc.ListNode(i32), target: i32) i32 {
+    var head = node;
+    var index: i32 = 0;
+    while (head != null) {
+        if (head.?.val == target) return index;
+        head = head.?.next;
+        index += 1;
+    }
+    return -1;
+}
+
+// Driver Code
+pub fn main() !void {
+    // 初始化链表
+    // 初始化各个结点 
+    var n0 = inc.ListNode(i32){.val = 1};
+    var n1 = inc.ListNode(i32){.val = 3};
+    var n2 = inc.ListNode(i32){.val = 2};
+    var n3 = inc.ListNode(i32){.val = 5};
+    var n4 = inc.ListNode(i32){.val = 4};
+    // 构建引用指向
+    n0.next = &n1;
+    n1.next = &n2;
+    n2.next = &n3;
+    n3.next = &n4;
+    std.debug.print("初始化的链表为", .{});
+    try inc.PrintUtil.printLinkedList(i32, &n0);
+
+    // 插入结点
+    var tmp = inc.ListNode(i32){.val = 0};
+    insert(&n0, &tmp);
+    std.debug.print("插入结点后的链表为", .{});
+    try inc.PrintUtil.printLinkedList(i32, &n0);
+
+    // 删除结点
+    remove(&n0);
+    std.debug.print("删除结点后的链表为", .{});
+    try inc.PrintUtil.printLinkedList(i32, &n0);
+
+    // 访问结点
+    var node = access(&n0, 3);
+    std.debug.print("链表中索引 3 处的结点的值 = {}\n", .{node.?.val});
+
+    // 查找结点
+    var index = find(&n0, 2);
+    std.debug.print("链表中值为 2 的结点的索引 = {}\n", .{index});
+
+    const getchar = try std.io.getStdIn().reader().readByte();
+    _ = getchar;
+}
\ No newline at end of file
diff --git a/codes/zig/chapter_array_and_linkedlist/list.zig b/codes/zig/chapter_array_and_linkedlist/list.zig
new file mode 100644
index 00000000..608bce96
--- /dev/null
+++ b/codes/zig/chapter_array_and_linkedlist/list.zig
@@ -0,0 +1,81 @@
+// File: list.zig
+// Created Time: 2023-01-07
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+const inc = @import("include");
+
+// Driver Code
+pub fn main() !void {
+    // 初始化列表
+    var list = std.ArrayList(i32).init(std.heap.page_allocator);
+    // 延迟释放内存
+    defer list.deinit();
+    try list.appendSlice(&[_]i32{ 1, 3, 2, 5, 4 });
+    std.debug.print("列表 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 访问元素
+    var num = list.items[1];
+    std.debug.print("\n访问索引 1 处的元素，得到 num = {}", .{num});
+
+    // 更新元素
+    list.items[1] = 0;
+    std.debug.print("\n将索引 1 处的元素更新为 0 ，得到 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 清空列表
+    list.clearRetainingCapacity();
+    std.debug.print("\n清空列表后 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 尾部添加元素
+    try list.append(1);
+    try list.append(3);
+    try list.append(2);
+    try list.append(5);
+    try list.append(4);
+    std.debug.print("\n添加元素后 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 中间插入元素
+    try list.insert(3, 6);
+    std.debug.print("\n在索引 3 处插入数字 6 ，得到 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 删除元素
+    var value = list.orderedRemove(3);
+    _ = value;
+    std.debug.print("\n删除索引 3 处的元素，得到 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 通过索引遍历列表
+    var count: i32 = 0;
+    var i: i32 = 0;
+    while (i < list.items.len) : (i += 1) {
+        count += 1;
+    }
+
+    // 直接遍历列表元素
+    count = 0;
+    for (list.items) |_| {
+        count += 1;
+    }
+
+    // 拼接两个列表
+    var list1 = std.ArrayList(i32).init(std.heap.page_allocator);
+    defer list1.deinit();
+    try list1.appendSlice(&[_]i32{ 6, 8, 7, 10, 9 });
+    try list.insertSlice(list.items.len, list1.items);
+    std.debug.print("\n将列表 list1 拼接到 list 之后，得到 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    // 排序列表
+    std.sort.sort(i32, list.items, {}, comptime std.sort.asc(i32));
+    std.debug.print("\n排序列表后 list = ", .{});
+    inc.PrintUtil.printList(i32, list);
+
+    const getchar = try std.io.getStdIn().reader().readByte();
+    _ = getchar;
+}
+
diff --git a/codes/zig/chapter_array_and_linkedlist/my_list.zig b/codes/zig/chapter_array_and_linkedlist/my_list.zig
new file mode 100644
index 00000000..f018e61c
--- /dev/null
+++ b/codes/zig/chapter_array_and_linkedlist/my_list.zig
@@ -0,0 +1,177 @@
+// File: my_list.zig
+// Created Time: 2023-01-08
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+const inc = @import("include");
+
+// 列表类简易实现
+// 编译期泛型
+pub fn MyList(comptime T: type) type {
+    return struct {
+        const Self = @This();
+        
+        nums: []T = undefined,                          // 数组（存储列表元素）
+        numsCapacity: usize = 10,                       // 列表容量
+        numSize: usize = 0,                             // 列表长度（即当前元素数量）
+        extendRatio: usize = 2,                         // 每次列表扩容的倍数
+        mem_arena: ?std.heap.ArenaAllocator = null,
+        mem_allocator: std.mem.Allocator = undefined,   // 内存分配器
+
+        // 构造函数（分配内存+初始化列表）
+        pub fn init(self: *Self, allocator: std.mem.Allocator) !void {
+            if (self.mem_arena == null) {
+                self.mem_arena = std.heap.ArenaAllocator.init(allocator);
+                self.mem_allocator = self.mem_arena.?.allocator();
+            }
+            self.nums = try self.mem_allocator.alloc(T, self.numsCapacity);
+            std.mem.set(T, self.nums, @as(T, 0));
+        }
+
+        // 析构函数（释放内存）
+        pub fn deinit(self: *Self) void {
+            if (self.mem_arena == null) return;
+            self.mem_arena.?.deinit();
+        }
+
+        // 获取列表长度（即当前元素数量）
+        pub fn size(self: *Self) usize {
+            return self.numSize;
+        }
+
+        // 获取列表容量
+        pub fn capacity(self: *Self) usize {
+            return self.numsCapacity;
+        }
+
+        // 访问元素
+        pub fn get(self: *Self, index: usize) T {
+            // 索引如果越界则抛出异常，下同
+            if (index >= self.size()) @panic("索引越界");
+            return self.nums[index];
+        }  
+
+        // 更新元素
+        pub fn set(self: *Self, index: usize, num: T) void {
+            // 索引如果越界则抛出异常，下同
+            if (index >= self.size()) @panic("索引越界");
+            self.nums[index] = num;
+        }  
+
+        // 尾部添加元素
+        pub fn add(self: *Self, num: T) !void {
+            // 元素数量超出容量时，触发扩容机制
+            if (self.size() == self.capacity()) try self.extendCapacity();
+            self.nums[self.size()] = num;
+            // 更新元素数量
+            self.numSize += 1;
+        }  
+
+        // 中间插入元素
+        pub fn insert(self: *Self, index: usize, num: T) !void {
+            if (index >= self.size()) @panic("索引越界");
+            // 元素数量超出容量时，触发扩容机制
+            if (self.size() == self.capacity()) try self.extendCapacity();
+            // 索引 i 以及之后的元素都向后移动一位
+            var j = self.size() - 1;
+            while (j >= index) : (j -= 1) {
+                self.nums[j + 1] = self.nums[j];
+            }
+            self.nums[index] = num;
+            // 更新元素数量
+            self.numSize += 1;
+        }
+
+        // 删除元素
+        pub fn remove(self: *Self, index: usize) T {
+            if (index >= self.size()) @panic("索引越界");
+            var num = self.nums[index];
+            // 索引 i 之后的元素都向前移动一位
+            var j = index;
+            while (j < self.size() - 1) : (j += 1) {
+                self.nums[j] = self.nums[j + 1];
+            }
+            // 更新元素数量
+            self.numSize -= 1;
+            // 返回被删除元素
+            return num;
+        }
+
+        // 列表扩容
+        pub fn extendCapacity(self: *Self) !void {
+            // 新建一个长度为 size * extendRatio 的数组，并将原数组拷贝到新数组
+            var newCapacity = self.capacity() * self.extendRatio;
+            var extend = try self.mem_allocator.alloc(T, newCapacity);
+            std.mem.set(T, extend, @as(T, 0));
+            // 将原数组中的所有元素复制到新数组
+            std.mem.copy(T, extend, self.nums);
+            self.nums = extend;
+            // 更新列表容量
+            self.numsCapacity = newCapacity;
+        }
+
+        // 将列表转换为数组
+        pub fn toArray(self: *Self) ![]T {
+            // 仅转换有效长度范围内的列表元素
+            var nums = try self.mem_allocator.alloc(T, self.size());
+            std.mem.set(T, nums, @as(T, 0));
+            for (nums) |*num, i| {
+                num.* = self.get(i);
+            }
+            return nums;
+        }
+    };
+}
+
+// Driver Code
+pub fn main() !void {
+    // 初始化列表
+    var list = MyList(i32){};
+    try list.init(std.heap.page_allocator);
+    // 延迟释放内存
+    defer list.deinit();
+
+    // 尾部添加元素
+    try list.add(1);
+    try list.add(3);
+    try list.add(2);
+    try list.add(5);
+    try list.add(4);
+    std.debug.print("列表 list = ", .{});
+    inc.PrintUtil.printArray(i32, try list.toArray());
+    std.debug.print(" ，容量 = {} ，长度 = {}", .{list.capacity(), list.size()});
+
+    // 中间插入元素
+    try list.insert(3, 6);
+    std.debug.print("\n在索引 3 处插入数字 6 ，得到 list = ", .{});
+    inc.PrintUtil.printArray(i32, try list.toArray());
+
+    // 删除元素
+    _ = list.remove(3);
+    std.debug.print("\n删除索引 3 处的元素，得到 list = ", .{});
+    inc.PrintUtil.printArray(i32, try list.toArray());
+
+    // 访问元素
+    var num = list.get(1);
+    std.debug.print("\n访问索引 1 处的元素，得到 num = {}", .{num});
+
+    // 更新元素
+    list.set(1, 0);
+    std.debug.print("\n将索引 1 处的元素更新为 0 ，得到 list = ", .{});
+    inc.PrintUtil.printArray(i32, try list.toArray());
+
+    // 测试扩容机制
+    list.set(1, 0);
+    var i: i32 = 0;
+    while (i < 10) : (i += 1) {
+        // 在 i = 5 时，列表长度将超出列表容量，此时触发扩容机制
+        try list.add(i);
+    }
+    std.debug.print("\n扩容后的列表 list = ", .{});
+    inc.PrintUtil.printArray(i32, try list.toArray());
+    std.debug.print(" ，容量 = {} ，长度 = {}\n", .{list.capacity(), list.size()});
+
+    const getchar = try std.io.getStdIn().reader().readByte();
+    _ = getchar;
+}
+
diff --git a/codes/zig/include/PrintUtil.zig b/codes/zig/include/PrintUtil.zig
index 9e6b18b0..4d2d2089 100644
--- a/codes/zig/include/PrintUtil.zig
+++ b/codes/zig/include/PrintUtil.zig
@@ -7,16 +7,42 @@ const ListNode = @import("ListNode.zig").ListNode;
 const TreeNode = @import("TreeNode.zig").TreeNode;
 
 // Print an array
-// 编译期泛型
 pub fn printArray(comptime T: type, nums: []T) void {
     std.debug.print("[", .{});
     if (nums.len > 0) {
         for (nums) |num, j| {
-            std.debug.print("{}{s}", .{num, if (j == nums.len-1) "]\n" else ", " });
+            std.debug.print("{}{s}", .{num, if (j == nums.len-1) "]" else ", " });
         }
     } else {
         std.debug.print("]", .{});
-        std.debug.print("\n", .{});
+    }
+}
+
+// Print a list
+pub fn printList(comptime T: type, list: std.ArrayList(T)) void {
+    std.debug.print("[", .{});
+    if (list.items.len > 0) {
+        for (list.items) |value, i| {
+            std.debug.print("{}{s}", .{value, if (i == list.items.len-1) "]" else ", " });
+        }
+    } else {
+        std.debug.print("]", .{});
+    }
+    
+}
+
+// Print a linked list
+pub fn printLinkedList(comptime T: type, node: ?*ListNode(T)) !void {
+    if (node == null) return;
+    var list = std.ArrayList(i32).init(std.heap.page_allocator);
+    defer list.deinit();
+    var head = node;
+    while (head != null) {
+        try list.append(head.?.val);
+        head = head.?.next;
+    }
+    for (list.items) |value, i| {
+        std.debug.print("{}{s}", .{value, if (i == list.items.len-1) "\n" else "->" });
     }
 }
 
diff --git a/deploy.sh b/deploy.sh
index 96a633cb..975d7b2f 100644
--- a/deploy.sh
+++ b/deploy.sh
@@ -3,6 +3,6 @@ mkdocs build --clean
 cd site
 git init
 git add -A
-git commit -m 'deploy'
+git commit -m "deploy"
 git push -f git@github.com:krahets/hello-algo.git master:gh-pages
 cd -
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 00000000..6a472b17
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,7 @@
+version: '3'
+services:
+  hello-algo:
+    build: .
+    ports:
+      - "8000:8000"
+      
\ No newline at end of file
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diff --git a/docs/chapter_heap/heap.assets/min_heap_and_max_heap.png b/docs/chapter_heap/heap.assets/min_heap_and_max_heap.png
new file mode 100644
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diff --git a/docs/chapter_heap/heap.md b/docs/chapter_heap/heap.md
new file mode 100644
index 00000000..73f425ff
--- /dev/null
+++ b/docs/chapter_heap/heap.md
@@ -0,0 +1,627 @@
+---
+comments: true
+---
+
+# 堆
+
+「堆 Heap」是一颗限定条件下的「完全二叉树」。根据成立条件，堆主要分为两种类型：
+
+- 「大顶堆 Max Heap」，任意结点的值 $\geq$ 其子结点的值；
+- 「小顶堆 Min Heap」，任意结点的值 $\leq$ 其子结点的值；
+
+![min_heap_and_max_heap](heap.assets/min_heap_and_max_heap.png)
+
+## 堆术语与性质
+
+- 由于堆是完全二叉树，因此最底层结点靠左填充，其它层结点皆被填满。
+- 二叉树中的根结点对应「堆顶」，底层最靠右结点对应「堆底」。
+- 对于大顶堆 / 小顶堆，其堆顶元素（即根结点）的值最大 / 最小。
+
+## 堆常用操作
+
+值得说明的是，多数编程语言提供的是「优先队列 Priority Queue」，其是一种抽象数据结构，**定义为具有出队优先级的队列**。
+
+而恰好，**堆的定义与优先队列的操作逻辑完全吻合**，大顶堆就是一个元素从大到小出队的优先队列。从使用角度看，我们可以将「优先队列」和「堆」理解为等价的数据结构。因此，本文与代码对两者不做特别区分，统一使用「堆」来命名。
+
+堆的常用操作见下表（方法命名以 Java 为例）。
+
+<p align="center"> Table. 堆的常用操作 </p>
+
+<div class="center-table" markdown>
+
+| 方法      | 描述                                         | 时间复杂度  |
+| --------- | -------------------------------------------- | ----------- |
+| add()     | 元素入堆                                     | $O(\log n)$ |
+| poll()    | 堆顶元素出堆                                 | $O(\log n)$ |
+| peek()    | 访问堆顶元素（大 / 小顶堆分别为最大 / 小值） | $O(1)$      |
+| size()    | 获取堆的元素数量                             | $O(1)$      |
+| isEmpty() | 判断堆是否为空                               | $O(1)$      |
+
+</div>
+
+我们可以直接使用编程语言提供的堆类（或优先队列类）。
+
+!!! tip
+
+    类似于排序中“从小到大排列”和“从大到小排列”，“大顶堆”和“小顶堆”可仅通过修改 Comparator 来互相转换。
+
+=== "Java"
+
+    ```java title="heap.java"
+    /* 初始化堆 */
+    // 初始化小顶堆
+    Queue<Integer> minHeap = new PriorityQueue<>();
+    // 初始化大顶堆（使用 lambda 表达式修改 Comparator 即可）
+    Queue<Integer> maxHeap = new PriorityQueue<>((a, b) -> { return b - a; });
+    
+    /* 元素入堆 */
+    maxHeap.add(1);
+    maxHeap.add(3);
+    maxHeap.add(2);
+    maxHeap.add(5);
+    maxHeap.add(4);
+    
+    /* 获取堆顶元素 */
+    int peek = maxHeap.peek(); // 5
+    
+    /* 堆顶元素出堆 */
+    // 出堆元素会形成一个从大到小的序列
+    peek = heap.poll();  // 5
+    peek = heap.poll();  // 4
+    peek = heap.poll();  // 3
+    peek = heap.poll();  // 2
+    peek = heap.poll();  // 1
+    
+    /* 获取堆大小 */
+    int size = maxHeap.size();
+    
+    /* 判断堆是否为空 */
+    boolean isEmpty = maxHeap.isEmpty();
+    
+    /* 输入列表并建堆 */
+    minHeap = new PriorityQueue<>(Arrays.asList(1, 3, 2, 5, 4));
+    ```
+
+=== "C++"
+
+    ```cpp title="heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="heap.swift"
+
+    ```
+
+## 堆的实现
+
+下文实现的是「大顶堆」，若想转换为「小顶堆」，将所有大小逻辑判断取逆（例如将 $\geq$ 替换为 $\leq$ ）即可，有兴趣的同学可自行实现。
+
+### 堆的存储与表示
+
+在二叉树章节我们学过，「完全二叉树」非常适合使用「数组」来表示，而堆恰好是一颗完全二叉树，**因而我们采用「数组」来存储「堆」**。
+
+**二叉树指针**。使用数组表示二叉树时，元素代表结点值，索引代表结点在二叉树中的位置，**而结点指针通过索引映射公式来实现**。
+
+具体地，给定索引 $i$ ，那么其左子结点索引为 $2i + 1$ 、右子结点索引为 $2i + 2$ 、父结点索引为 $(i - 1) / 2$ （向下整除）。当索引越界时，代表空结点或结点不存在。
+
+![representation_of_heap](heap.assets/representation_of_heap.png)
+
+我们将索引映射公式封装成函数，以便后续使用。
+
+=== "Java"
+
+    ```java title="my_heap.java"
+    // 使用列表而非数组，这样无需考虑扩容问题
+    List<Integer> maxHeap;
+    
+    /* 构造函数，建立空堆 */
+    public MaxHeap() {
+        maxHeap = new ArrayList<>();
+    }
+    
+    /* 获取左子结点索引 */
+    int left(int i) {
+        return 2 * i + 1;
+    }
+    
+    /* 获取右子结点索引 */
+    int right(int i) {
+        return 2 * i + 2;
+    }
+    
+    /* 获取父结点索引 */
+    int parent(int i) {
+        return (i - 1) / 2; // 向下整除
+    }
+    ```
+
+=== "C++"
+
+    ```cpp title="my_heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="my_heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="my_heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="my_heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="my_heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="my_heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="my_heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="my_heap.swift"
+
+    ```
+
+### 访问堆顶元素
+
+堆顶元素是二叉树的根结点，即列表首元素。
+
+=== "Java"
+
+    ```java title="my_heap.java"
+    /* 访问堆顶元素 */
+    public int peek() {
+        return maxHeap.get(0);
+    }
+    ```
+
+=== "C++"
+
+    ```cpp title="my_heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="my_heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="my_heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="my_heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="my_heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="my_heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="my_heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="my_heap.swift"
+
+    ```
+
+### 元素入堆
+
+给定元素 `val` ，我们先将其添加到堆底。添加后，由于 `val` 可能大于堆中其它元素，此时堆的成立条件可能已经被破坏，**因此需要修复从插入结点到根结点这条路径上的各个结点**，该操作被称为「堆化 Heapify」。
+
+考虑从入堆结点开始，**从底至顶执行堆化**。具体地，比较插入结点与其父结点的值，若插入结点更大则将它们交换；并循环以上操作，从底至顶地修复堆中的各个结点；直至越过根结点时结束，或当遇到无需交换的结点时提前结束。
+
+=== "Step 1"
+    ![heap_push_step1](heap.assets/heap_push_step1.png)
+
+=== "Step 2"
+    ![heap_push_step2](heap.assets/heap_push_step2.png)
+
+=== "Step 3"
+    ![heap_push_step3](heap.assets/heap_push_step3.png)
+
+=== "Step 4"
+    ![heap_push_step4](heap.assets/heap_push_step4.png)
+
+=== "Step 5"
+    ![heap_push_step5](heap.assets/heap_push_step5.png)
+
+=== "Step 6"
+    ![heap_push_step6](heap.assets/heap_push_step6.png)
+
+设结点总数为 $n$ ，则树的高度为 $O(\log n)$ ，易得堆化操作的循环轮数最多为 $O(\log n)$ ，**因而元素入堆操作的时间复杂度为 $O(\log n)$** 。
+
+=== "Java"
+
+    ```java title="my_heap.java"
+    /* 元素入堆 */
+    void push(int val) {
+        // 添加结点
+        maxHeap.add(val);
+        // 从底至顶堆化
+        siftUp(size() - 1);
+    }
+    
+    /* 从结点 i 开始，从底至顶堆化 */
+    void siftUp(int i) {
+        while (true) {
+            // 获取结点 i 的父结点
+            int p = parent(i);
+            // 若“越过根结点”或“结点无需修复”，则结束堆化
+            if (p < 0 || maxHeap.get(i) <= maxHeap.get(p))
+                break;
+            // 交换两结点
+            swap(i, p);
+            // 循环向上堆化
+            i = p;
+        }
+    }
+    ```
+
+=== "C++"
+
+    ```cpp title="my_heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="my_heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="my_heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="my_heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="my_heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="my_heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="my_heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="my_heap.swift"
+
+    ```
+
+### 堆顶元素出堆
+
+堆顶元素是二叉树根结点，即列表首元素，如果我们直接将首元素从列表中删除，则二叉树中所有结点都会随之发生移位（索引发生变化），这样后续使用堆化修复就很麻烦了。为了尽量减少元素索引变动，采取以下操作步骤：
+
+1. 交换堆顶元素与堆底元素（即交换根结点与最右叶结点）；
+2. 交换完成后，将堆底从列表中删除（注意，因为已经交换，实际上删除的是原来的堆顶元素）；
+3. 从根结点开始，**从顶至底执行堆化**；
+
+顾名思义，**从顶至底堆化的操作方向与从底至顶堆化相反**，我们比较根结点的值与其两个子结点的值，将最大的子结点与根结点执行交换，并循环以上操作，直到越过叶结点时结束，或当遇到无需交换的结点时提前结束。
+
+=== "Step 1"
+    ![heap_poll_step1](heap.assets/heap_poll_step1.png)
+
+=== "Step 2"
+    ![heap_poll_step2](heap.assets/heap_poll_step2.png)
+
+=== "Step 3"
+    ![heap_poll_step3](heap.assets/heap_poll_step3.png)
+
+=== "Step 4"
+    ![heap_poll_step4](heap.assets/heap_poll_step4.png)
+
+=== "Step 5"
+    ![heap_poll_step5](heap.assets/heap_poll_step5.png)
+
+=== "Step 6"
+    ![heap_poll_step6](heap.assets/heap_poll_step6.png)
+
+=== "Step 7"
+    ![heap_poll_step7](heap.assets/heap_poll_step7.png)
+
+=== "Step 8"
+    ![heap_poll_step8](heap.assets/heap_poll_step8.png)
+
+=== "Step 9"
+    ![heap_poll_step9](heap.assets/heap_poll_step9.png)
+
+=== "Step 10"
+    ![heap_poll_step10](heap.assets/heap_poll_step10.png)
+
+与元素入堆操作类似，**堆顶元素出堆操作的时间复杂度为 $O(\log n)$** 。
+
+=== "Java"
+
+    ```java title="my_heap.java"
+    /* 元素出堆 */
+    int poll() {
+        // 判空处理
+        if (isEmpty())
+            throw new EmptyStackException();
+        // 交换根结点与最右叶结点（即交换首元素与尾元素）
+        swap(0, size() - 1);
+        // 删除结点
+        int val = maxHeap.remove(size() - 1);
+        // 从顶至底堆化
+        siftDown(0);
+        // 返回堆顶元素
+        return val;
+    }
+    
+    /* 从结点 i 开始，从顶至底堆化 */
+    void siftDown(int i) {
+        while (true) {
+            // 判断结点 i, l, r 中值最大的结点，记为 ma
+            int l = left(i), r = right(i), ma = i;
+            if (l < size() && maxHeap.get(l) > maxHeap.get(ma))
+                ma = l;
+            if (r < size() && maxHeap.get(r) > maxHeap.get(ma))
+                ma = r;
+            // 若“结点 i 最大”或“越过叶结点”，则结束堆化
+            if (ma == i) break;
+            // 交换两结点
+            swap(i, ma);
+            // 循环向下堆化
+            i = ma;
+        }
+    }
+    ```
+
+=== "C++"
+
+    ```cpp title="my_heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="my_heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="my_heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="my_heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="my_heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="my_heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="my_heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="my_heap.swift"
+
+    ```
+
+### 输入数据并建堆 *
+
+如果我们想要直接输入一个列表并将其建堆，那么该怎么做呢？最直接地，考虑使用「元素入堆」方法，将列表元素依次入堆。元素入堆的时间复杂度为 $O(n)$ ，而平均长度为 $\frac{n}{2}$ ，因此该方法的总体时间复杂度为 $O(n \log n)$ 。
+
+然而，存在一种更加优雅的建堆方法。设结点数量为 $n$ ，我们先将列表所有元素原封不动添加进堆，**然后迭代地对各个结点执行「从顶至底堆化」**。当然，**无需对叶结点执行堆化**，因为其没有子结点。
+
+=== "Java"
+
+    ```java title="my_heap.java"
+    /* 构造函数，根据输入列表建堆 */
+    public MaxHeap(List<Integer> nums) {
+        // 将列表元素原封不动添加进堆
+        maxHeap = new ArrayList<>(nums);
+        // 堆化除叶结点以外的其他所有结点
+        for (int i = parent(size() - 1); i >= 0; i--) {
+            siftDown(i);
+        }
+    }
+    ```
+
+=== "C++"
+
+    ```cpp title="my_heap.cpp"
+
+    ```
+
+=== "Python"
+
+    ```python title="my_heap.py"
+
+    ```
+
+=== "Go"
+
+    ```go title="my_heap.go"
+
+    ```
+
+=== "JavaScript"
+
+    ```js title="my_heap.js"
+
+    ```
+
+=== "TypeScript"
+
+    ```typescript title="my_heap.ts"
+
+    ```
+
+=== "C"
+
+    ```c title="my_heap.c"
+
+    ```
+
+=== "C#"
+
+    ```csharp title="my_heap.cs"
+
+    ```
+
+=== "Swift"
+
+    ```swift title="my_heap.swift"
+
+    ```
+
+那么，第二种建堆方法的时间复杂度时多少呢？我们来做一下简单推算。
+
+- 完全二叉树中，设结点总数为 $n$ ，则叶结点数量为 $(n + 1) / 2$ ，其中 $/$ 为向下整除。因此在排除叶结点后，需要堆化结点数量为 $(n - 1)/2$ ，即为 $O(n)$ ；
+- 从顶至底堆化中，每个结点最多堆化至叶结点，因此最大迭代次数为二叉树高度 $O(\log n)$ ；
+
+将上述两者相乘，可得时间复杂度为 $O(n \log n)$ 。然而，该估算结果仍不够准确，因为我们没有考虑到 **二叉树底层结点远多于顶层结点** 的性质。
+
+下面我们来尝试展开计算。为了减小计算难度，我们假设树是一个「完美二叉树」，该假设不会影响计算结果的正确性。设二叉树（即堆）结点数量为 $n$ ，树高度为 $h$ 。上文提到，**结点堆化最大迭代次数等于该结点到叶结点的距离，而这正是“结点高度”**。因此，我们将各层的“结点数量 $\times$ 结点高度”求和，即可得到所有结点的堆化的迭代次数总和。
+
+$$
+T(h) = 2^0h + 2^1(h-1) + 2^2(h-2) + \cdots + 2^{(h-1)}\times1
+$$
+
+![heapify_count](heap.assets/heapify_count.png)
+
+化简上式需要借助中学的数列知识，先对 $T(h)$ 乘以 $2$ ，易得
+
+$$
+\begin{aligned}
+T(h) & = 2^0h + 2^1(h-1) + 2^2(h-2) + \cdots + 2^{h-1}\times1 \newline
+2 T(h) & = 2^1h + 2^2(h-1) + 2^3(h-2) + \cdots + 2^{h}\times1 \newline
+\end{aligned}
+$$
+
+**使用错位相减法**，令下式 $2 T(h)$ 减去上式 $T(h)$ ，可得
+
+$$
+2T(h) - T(h) = T(h) = -2^0h + 2^1 + 2^2 + \cdots + 2^{h-1} + 2^h
+$$
+
+观察上式，$T(h)$ 是一个等比数列，可直接使用求和公式，得到时间复杂度为
+
+$$
+\begin{aligned}
+T(h) & = 2 \frac{1 - 2^h}{1 - 2} - h \newline
+& = 2^{h+1} - h \newline
+& = O(2^h)
+\end{aligned}
+$$
+
+进一步地，高度为 $h$ 的完美二叉树的结点数量为 $n = 2^{h+1} - 1$ ，易得复杂度为 $O(2^h) = O(n)$。以上推算表明，**输入列表并建堆的时间复杂度为 $O(n)$ ，非常高效**。
+
+## 堆常见应用
+
+- **优先队列**。堆常作为实现优先队列的首选数据结构，入队和出队操作时间复杂度为 $O(\log n)$ ，建队操作为 $O(n)$ ，皆非常高效。
+- **堆排序**。给定一组数据，我们使用其建堆，并依次全部弹出，则可以得到有序的序列。当然，堆排序一般无需弹出元素，仅需每轮将堆顶元素交换至数组尾部并减小堆的长度即可。
+- **获取最大的 $k$ 个元素**。这既是一道经典算法题目，也是一种常见应用，例如选取热度前 10 的新闻作为微博热搜，选取前 10 销量的商品等。
diff --git a/docs/chapter_preface/contribution.md b/docs/chapter_preface/contribution.md
index c710e6de..4e5f3dc8 100644
--- a/docs/chapter_preface/contribution.md
+++ b/docs/chapter_preface/contribution.md
@@ -41,4 +41,26 @@ comments: true
 
 非常欢迎您和我一同来创作本书！
 
+## 离线部署
+
+### Docker
+
+使用本教程前，请确保 Docker 已经安装并启动。
+
+根据如下命令离线部署。
+
+```bash
+git clone https://github.com/krahets/hello-algo.git
+cd hello-algo
+docker-compose up -d
+```
+
+稍等片刻，即可通过浏览器打开 `http://localhost:8000` 访问本教程。
+
+使用如下命令删除部署。
+
+```bash
+docker-compose down
+```
+
 （TODO：教学视频）
diff --git a/docs/chapter_sorting/bubble_sort.md b/docs/chapter_sorting/bubble_sort.md
index e3e394b2..3bb0bc99 100644
--- a/docs/chapter_sorting/bubble_sort.md
+++ b/docs/chapter_sorting/bubble_sort.md
@@ -170,7 +170,7 @@ comments: true
 
     ```c title="bubble_sort.c"
     /* 冒泡排序 */
-    void bubble_sort(int nums[], int size) {
+    void bubbleSort(int nums[], int size) {
         // 外循环：待排序元素数量为 n-1, n-2, ..., 1
         for (int i = 0; i < size - 1; i++)
         {
@@ -373,7 +373,7 @@ comments: true
 
     ```c title="bubble_sort.c"
     /* 冒泡排序 */
-    void bubble_sort(int nums[], int size) {
+    void bubbleSortWithFlag(int nums[], int size) {
         // 外循环：待排序元素数量为 n-1, n-2, ..., 1
         for (int i = 0; i < size - 1; i++)
         {
diff --git a/docs/chapter_stack_and_queue/deque.md b/docs/chapter_stack_and_queue/deque.md
index 52b0540d..4671d5c9 100644
--- a/docs/chapter_stack_and_queue/deque.md
+++ b/docs/chapter_stack_and_queue/deque.md
@@ -18,16 +18,16 @@ comments: true
 
 <div class="center-table" markdown>
 
-| 方法         | 描述             |
-| ------------ | ---------------- |
-| offerFirst() | 将元素添加至队首 |
-| offerLast()  | 将元素添加至队尾 |
-| pollFirst()  | 删除队首元素     |
-| pollLast()   | 删除队尾元素     |
-| peekFirst()  | 访问队首元素     |
-| peekLast()   | 访问队尾元素     |
-| size()       | 获取队列的长度   |
-| isEmpty()    | 判断队列是否为空 |
+| 方法         | 描述             | 时间复杂度 |
+| ------------ | ---------------- | ---------- |
+| offerFirst() | 将元素添加至队首 | $O(1)$     |
+| offerLast()  | 将元素添加至队尾 | $O(1)$     |
+| pollFirst()  | 删除队首元素     | $O(1)$     |
+| pollLast()   | 删除队尾元素     | $O(1)$     |
+| peekFirst()  | 访问队首元素     | $O(1)$     |
+| peekLast()   | 访问队尾元素     | $O(1)$     |
+| size()       | 获取队列的长度   | $O(1)$     |
+| isEmpty()    | 判断队列是否为空 | $O(1)$     |
 
 </div>
 
@@ -196,5 +196,5 @@ comments: true
 === "Swift"
 
     ```swift title="deque.swift"
-
+    
     ```
diff --git a/docs/chapter_stack_and_queue/queue.md b/docs/chapter_stack_and_queue/queue.md
index 08cf76d7..d70b3e52 100644
--- a/docs/chapter_stack_and_queue/queue.md
+++ b/docs/chapter_stack_and_queue/queue.md
@@ -20,13 +20,13 @@ comments: true
 
 <div class="center-table" markdown>
 
-| 方法      | 描述                         |
-| --------- | ---------------------------- |
-| offer()   | 元素入队，即将元素添加至队尾 |
-| poll()    | 队首元素出队                 |
-| front()   | 访问队首元素                 |
-| size()    | 获取队列的长度               |
-| isEmpty() | 判断队列是否为空             |
+| 方法      | 描述                         | 时间复杂度 |
+| --------- | ---------------------------- | ---------- |
+| offer()   | 元素入队，即将元素添加至队尾 | $O(1)$     |
+| poll()    | 队首元素出队                 | $O(1)$     |
+| front()   | 访问队首元素                 | $O(1)$     |
+| size()    | 获取队列的长度               | $O(1)$     |
+| isEmpty() | 判断队列是否为空             | $O(1)$     |
 
 </div>
 
diff --git a/docs/chapter_stack_and_queue/stack.md b/docs/chapter_stack_and_queue/stack.md
index 7ff3f15b..c47f7cc8 100644
--- a/docs/chapter_stack_and_queue/stack.md
+++ b/docs/chapter_stack_and_queue/stack.md
@@ -22,13 +22,13 @@ comments: true
 
 <div class="center-table" markdown>
 
-| 方法      | 描述                   |
-| --------- | ---------------------- |
-| push()    | 元素入栈（添加至栈顶） |
-| pop()     | 栈顶元素出栈           |
-| peek()    | 访问栈顶元素           |
-| size()    | 获取栈的长度           |
-| isEmpty() | 判断栈是否为空         |
+| 方法      | 描述                   | 时间复杂度 |
+| --------- | ---------------------- | ---------- |
+| push()    | 元素入栈（添加至栈顶） | $O(1)$     |
+| pop()     | 栈顶元素出栈           | $O(1)$     |
+| peek()    | 访问栈顶元素           | $O(1)$     |
+| size()    | 获取栈的长度           | $O(1)$     |
+| isEmpty() | 判断栈是否为空         | $O(1)$     |
 
 </div>
 
diff --git a/docs/chapter_tree/binary_tree.md b/docs/chapter_tree/binary_tree.md
index 1061e019..0201f6a2 100644
--- a/docs/chapter_tree/binary_tree.md
+++ b/docs/chapter_tree/binary_tree.md
@@ -114,7 +114,7 @@ comments: true
 
 结点的两个指针分别指向「左子结点 Left Child Node」和「右子结点 Right Child Node」，并且称该结点为两个子结点的「父结点 Parent Node」。给定二叉树某结点，将左子结点以下的树称为该结点的「左子树 Left Subtree」，右子树同理。
 
-除了叶结点外，每个结点都有子结点和子树。例如，若将上图的「结点 2」看作父结点，那么其左子结点和右子结点分别为「结点 4」和「结点 5」，左子树和右子树分别为「结点 4 及其以下结点形成的树」和「结点 5 及其以下结点形成的树」。
+除了叶结点外，每个结点都有子结点和子树。例如，若将下图的「结点 2」看作父结点，那么其左子结点和右子结点分别为「结点 4」和「结点 5」，左子树和右子树分别为「结点 4 及其以下结点形成的树」和「结点 5 及其以下结点形成的树」。
 
 ![binary_tree_definition](binary_tree.assets/binary_tree_definition.png)
 
diff --git a/docs/chapter_tree/summary.md b/docs/chapter_tree/summary.md
index a46a253f..15dc2f6d 100644
--- a/docs/chapter_tree/summary.md
+++ b/docs/chapter_tree/summary.md
@@ -15,4 +15,4 @@ comments: true
 - 前序、中序、后序遍历是深度优先搜索，体现着“走到头、再回头继续”的回溯遍历方式，通常使用递归实现。
 - 二叉搜索树是一种高效的元素查找数据结构，查找、插入、删除操作的时间复杂度皆为 $O(\log n)$ 。二叉搜索树退化为链表后，各项时间复杂度劣化至 $O(n)$ ，因此如何避免退化是非常重要的课题。
 - AVL 树又称平衡二叉搜索树，其通过旋转操作，使得在不断插入与删除结点后，仍然可以保持二叉树的平衡（不退化）。
-- AVL 树的旋转操作分为右旋、左旋、先右旋后左旋、先左旋后右旋。在插入或删除结点后，AVL 树会从底置顶地执行旋转操作，使树恢复平衡。
+- AVL 树的旋转操作分为右旋、左旋、先右旋后左旋、先左旋后右旋。在插入或删除结点后，AVL 树会从底至顶地执行旋转操作，使树恢复平衡。
diff --git a/mkdocs.yml b/mkdocs.yml
index 9ddae9f3..ad836ae9 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -161,6 +161,8 @@ nav:
     - 二叉搜索树: chapter_tree/binary_search_tree.md
     - AVL 树 *: chapter_tree/avl_tree.md
     - 小结: chapter_tree/summary.md
+  - 堆:
+    - 堆（Heap）: chapter_heap/heap.md
   - 查找算法:
     - 线性查找: chapter_searching/linear_search.md
     - 二分查找: chapter_searching/binary_search.md