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---
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comments: true
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---
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# 7.2. 二叉树遍历
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从物理结构的角度来看,树是一种基于链表的数据结构,因此其遍历方式是通过指针逐个访问节点。然而,树是一种非线性数据结构,这使得遍历树比遍历链表更加复杂,需要借助搜索算法来实现。
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二叉树常见的遍历方式包括层序遍历、前序遍历、中序遍历和后序遍历等。
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## 7.2.1. 层序遍历
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「层序遍历 Level-Order Traversal」从顶部到底部逐层遍历二叉树,并在每一层按照从左到右的顺序访问节点。
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层序遍历本质上属于「广度优先搜索 Breadth-First Traversal」,它体现了一种“一圈一圈向外扩展”的逐层搜索方式。
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![二叉树的层序遍历](binary_tree_traversal.assets/binary_tree_bfs.png)
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<p align="center"> Fig. 二叉树的层序遍历 </p>
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### 算法实现
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广度优先遍历通常借助「队列」来实现。队列遵循“先进先出”的规则,而广度优先遍历则遵循“逐层推进”的规则,两者背后的思想是一致的。
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=== "Java"
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```java title="binary_tree_bfs.java"
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/* 层序遍历 */
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List<Integer> levelOrder(TreeNode root) {
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// 初始化队列,加入根节点
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Queue<TreeNode> queue = new LinkedList<>() {{ add(root); }};
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// 初始化一个列表,用于保存遍历序列
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List<Integer> list = new ArrayList<>();
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while (!queue.isEmpty()) {
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TreeNode node = queue.poll(); // 队列出队
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list.add(node.val); // 保存节点值
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if (node.left != null)
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queue.offer(node.left); // 左子节点入队
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if (node.right != null)
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queue.offer(node.right); // 右子节点入队
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}
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return list;
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}
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```
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=== "C++"
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```cpp title="binary_tree_bfs.cpp"
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/* 层序遍历 */
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vector<int> levelOrder(TreeNode *root) {
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// 初始化队列,加入根节点
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queue<TreeNode *> queue;
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queue.push(root);
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// 初始化一个列表,用于保存遍历序列
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vector<int> vec;
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while (!queue.empty()) {
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TreeNode *node = queue.front();
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queue.pop(); // 队列出队
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vec.push_back(node->val); // 保存节点值
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if (node->left != nullptr)
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queue.push(node->left); // 左子节点入队
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if (node->right != nullptr)
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queue.push(node->right); // 右子节点入队
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}
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return vec;
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}
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```
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=== "Python"
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```python title="binary_tree_bfs.py"
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def level_order(root: TreeNode | None) -> list[int]:
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"""层序遍历"""
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# 初始化队列,加入根节点
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queue: deque[TreeNode] = deque()
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queue.append(root)
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# 初始化一个列表,用于保存遍历序列
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res: list[int] = []
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while queue:
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node: TreeNode = queue.popleft() # 队列出队
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res.append(node.val) # 保存节点值
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if node.left is not None:
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queue.append(node.left) # 左子节点入队
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if node.right is not None:
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queue.append(node.right) # 右子节点入队
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return res
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```
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=== "Go"
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```go title="binary_tree_bfs.go"
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/* 层序遍历 */
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func levelOrder(root *TreeNode) []int {
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// 初始化队列,加入根节点
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queue := list.New()
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queue.PushBack(root)
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// 初始化一个切片,用于保存遍历序列
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nums := make([]int, 0)
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for queue.Len() > 0 {
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// 队列出队
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node := queue.Remove(queue.Front()).(*TreeNode)
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// 保存节点值
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nums = append(nums, node.Val)
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if node.Left != nil {
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// 左子节点入队
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queue.PushBack(node.Left)
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}
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if node.Right != nil {
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// 右子节点入队
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queue.PushBack(node.Right)
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}
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}
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return nums
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}
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```
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=== "JavaScript"
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```javascript title="binary_tree_bfs.js"
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/* 层序遍历 */
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function levelOrder(root) {
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// 初始化队列,加入根节点
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const queue = [root];
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// 初始化一个列表,用于保存遍历序列
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const list = [];
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while (queue.length) {
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let node = queue.shift(); // 队列出队
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list.push(node.val); // 保存节点值
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if (node.left) queue.push(node.left); // 左子节点入队
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if (node.right) queue.push(node.right); // 右子节点入队
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}
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return list;
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}
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```
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=== "TypeScript"
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```typescript title="binary_tree_bfs.ts"
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/* 层序遍历 */
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function levelOrder(root: TreeNode | null): number[] {
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// 初始化队列,加入根节点
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const queue = [root];
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// 初始化一个列表,用于保存遍历序列
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const list: number[] = [];
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while (queue.length) {
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let node = queue.shift() as TreeNode; // 队列出队
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list.push(node.val); // 保存节点值
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if (node.left) {
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queue.push(node.left); // 左子节点入队
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}
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if (node.right) {
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queue.push(node.right); // 右子节点入队
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}
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}
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return list;
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}
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```
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=== "C"
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```c title="binary_tree_bfs.c"
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/* 层序遍历 */
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int *levelOrder(TreeNode *root, int *size) {
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/* 辅助队列 */
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int front, rear;
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int index, *arr;
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TreeNode *node;
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TreeNode **queue;
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/* 辅助队列 */
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queue = (TreeNode **)malloc(sizeof(TreeNode *) * MAX_NODE_SIZE);
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// 队列指针
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front = 0, rear = 0;
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// 加入根节点
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queue[rear++] = root;
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// 初始化一个列表,用于保存遍历序列
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/* 辅助数组 */
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arr = (int *)malloc(sizeof(int) * MAX_NODE_SIZE);
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// 数组指针
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index = 0;
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while (front < rear) {
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// 队列出队
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node = queue[front++];
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// 保存节点值
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arr[index++] = node->val;
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if (node->left != NULL) {
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// 左子节点入队
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queue[rear++] = node->left;
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}
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if (node->right != NULL) {
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// 右子节点入队
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queue[rear++] = node->right;
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}
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}
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// 更新数组长度的值
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*size = index;
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arr = realloc(arr, sizeof(int) * (*size));
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// 释放辅助数组空间
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free(queue);
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return arr;
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}
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```
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=== "C#"
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```csharp title="binary_tree_bfs.cs"
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/* 层序遍历 */
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List<int> levelOrder(TreeNode root) {
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// 初始化队列,加入根节点
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Queue<TreeNode> queue = new();
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queue.Enqueue(root);
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// 初始化一个列表,用于保存遍历序列
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List<int> list = new();
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while (queue.Count != 0) {
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TreeNode node = queue.Dequeue(); // 队列出队
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list.Add(node.val); // 保存节点值
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if (node.left != null)
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queue.Enqueue(node.left); // 左子节点入队
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if (node.right != null)
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queue.Enqueue(node.right); // 右子节点入队
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}
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return list;
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}
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```
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=== "Swift"
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```swift title="binary_tree_bfs.swift"
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/* 层序遍历 */
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func levelOrder(root: TreeNode) -> [Int] {
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// 初始化队列,加入根节点
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var queue: [TreeNode] = [root]
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// 初始化一个列表,用于保存遍历序列
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var list: [Int] = []
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while !queue.isEmpty {
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let node = queue.removeFirst() // 队列出队
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list.append(node.val) // 保存节点值
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if let left = node.left {
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queue.append(left) // 左子节点入队
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}
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if let right = node.right {
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queue.append(right) // 右子节点入队
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}
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}
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return list
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}
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```
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=== "Zig"
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```zig title="binary_tree_bfs.zig"
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// 层序遍历
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fn levelOrder(comptime T: type, mem_allocator: std.mem.Allocator, root: *inc.TreeNode(T)) !std.ArrayList(T) {
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// 初始化队列,加入根节点
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const L = std.TailQueue(*inc.TreeNode(T));
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var queue = L{};
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var root_node = try mem_allocator.create(L.Node);
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root_node.data = root;
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queue.append(root_node);
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// 初始化一个列表,用于保存遍历序列
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var list = std.ArrayList(T).init(std.heap.page_allocator);
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while (queue.len > 0) {
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var queue_node = queue.popFirst().?; // 队列出队
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var node = queue_node.data;
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try list.append(node.val); // 保存节点值
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if (node.left != null) {
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var tmp_node = try mem_allocator.create(L.Node);
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tmp_node.data = node.left.?;
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queue.append(tmp_node); // 左子节点入队
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}
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if (node.right != null) {
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var tmp_node = try mem_allocator.create(L.Node);
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tmp_node.data = node.right.?;
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queue.append(tmp_node); // 右子节点入队
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}
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}
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return list;
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}
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```
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### 复杂度分析
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**时间复杂度**:所有节点被访问一次,使用 $O(n)$ 时间,其中 $n$ 为节点数量。
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**空间复杂度**:在最差情况下,即满二叉树时,遍历到最底层之前,队列中最多同时存在 $\frac{n + 1}{2}$ 个节点,占用 $O(n)$ 空间。
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## 7.2.2. 前序、中序、后序遍历
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相应地,前序、中序和后序遍历都属于「深度优先遍历 Depth-First Traversal」,它体现了一种“先走到尽头,再回溯继续”的遍历方式。
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如下图所示,左侧是深度优先遍历的示意图,右上方是对应的递归实现代码。深度优先遍历就像是绕着整个二叉树的外围“走”一圈,在这个过程中,在每个节点都会遇到三个位置,分别对应前序遍历、中序遍历和后序遍历。
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![二叉搜索树的前、中、后序遍历](binary_tree_traversal.assets/binary_tree_dfs.png)
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<p align="center"> Fig. 二叉搜索树的前、中、后序遍历 </p>
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<div class="center-table" markdown>
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| 位置 | 含义 | 此处访问节点时对应 |
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| ---------- | ------------------------------------ | ----------------------------- |
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| 橙色圆圈处 | 刚进入此节点,即将访问该节点的左子树 | 前序遍历 Pre-Order Traversal |
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| 蓝色圆圈处 | 已访问完左子树,即将访问右子树 | 中序遍历 In-Order Traversal |
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| 紫色圆圈处 | 已访问完左子树和右子树,即将返回 | 后序遍历 Post-Order Traversal |
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</div>
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### 算法实现
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=== "Java"
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```java title="binary_tree_dfs.java"
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/* 前序遍历 */
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void preOrder(TreeNode root) {
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if (root == null)
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return;
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// 访问优先级:根节点 -> 左子树 -> 右子树
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list.add(root.val);
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preOrder(root.left);
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preOrder(root.right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode root) {
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if (root == null)
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return;
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// 访问优先级:左子树 -> 根节点 -> 右子树
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inOrder(root.left);
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list.add(root.val);
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inOrder(root.right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode root) {
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if (root == null)
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return;
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// 访问优先级:左子树 -> 右子树 -> 根节点
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postOrder(root.left);
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postOrder(root.right);
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list.add(root.val);
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}
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```
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=== "C++"
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```cpp title="binary_tree_dfs.cpp"
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/* 前序遍历 */
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void preOrder(TreeNode *root) {
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if (root == nullptr)
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return;
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// 访问优先级:根节点 -> 左子树 -> 右子树
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vec.push_back(root->val);
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preOrder(root->left);
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preOrder(root->right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode *root) {
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if (root == nullptr)
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return;
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// 访问优先级:左子树 -> 根节点 -> 右子树
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inOrder(root->left);
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vec.push_back(root->val);
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inOrder(root->right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode *root) {
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if (root == nullptr)
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return;
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// 访问优先级:左子树 -> 右子树 -> 根节点
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postOrder(root->left);
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postOrder(root->right);
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vec.push_back(root->val);
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}
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```
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=== "Python"
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```python title="binary_tree_dfs.py"
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def pre_order(root: TreeNode | None) -> None:
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"""前序遍历"""
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if root is None:
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return
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# 访问优先级:根节点 -> 左子树 -> 右子树
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res.append(root.val)
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pre_order(root=root.left)
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pre_order(root=root.right)
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|
|
def in_order(root: TreeNode | None) -> None:
|
|
|
"""中序遍历"""
|
|
|
if root is None:
|
|
|
return
|
|
|
# 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
in_order(root=root.left)
|
|
|
res.append(root.val)
|
|
|
in_order(root=root.right)
|
|
|
|
|
|
def post_order(root: TreeNode | None) -> None:
|
|
|
"""后序遍历"""
|
|
|
if root is None:
|
|
|
return
|
|
|
# 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
post_order(root=root.left)
|
|
|
post_order(root=root.right)
|
|
|
res.append(root.val)
|
|
|
```
|
|
|
|
|
|
=== "Go"
|
|
|
|
|
|
```go title="binary_tree_dfs.go"
|
|
|
/* 前序遍历 */
|
|
|
func preOrder(node *TreeNode) {
|
|
|
if node == nil {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
nums = append(nums, node.Val)
|
|
|
preOrder(node.Left)
|
|
|
preOrder(node.Right)
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
func inOrder(node *TreeNode) {
|
|
|
if node == nil {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(node.Left)
|
|
|
nums = append(nums, node.Val)
|
|
|
inOrder(node.Right)
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
func postOrder(node *TreeNode) {
|
|
|
if node == nil {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(node.Left)
|
|
|
postOrder(node.Right)
|
|
|
nums = append(nums, node.Val)
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "JavaScript"
|
|
|
|
|
|
```javascript title="binary_tree_dfs.js"
|
|
|
/* 前序遍历 */
|
|
|
function preOrder(root) {
|
|
|
if (root === null) return;
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
list.push(root.val);
|
|
|
preOrder(root.left);
|
|
|
preOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
function inOrder(root) {
|
|
|
if (root === null) return;
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(root.left);
|
|
|
list.push(root.val);
|
|
|
inOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
function postOrder(root) {
|
|
|
if (root === null) return;
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(root.left);
|
|
|
postOrder(root.right);
|
|
|
list.push(root.val);
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "TypeScript"
|
|
|
|
|
|
```typescript title="binary_tree_dfs.ts"
|
|
|
/* 前序遍历 */
|
|
|
function preOrder(root: TreeNode | null): void {
|
|
|
if (root === null) {
|
|
|
return;
|
|
|
}
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
list.push(root.val);
|
|
|
preOrder(root.left);
|
|
|
preOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
function inOrder(root: TreeNode | null): void {
|
|
|
if (root === null) {
|
|
|
return;
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(root.left);
|
|
|
list.push(root.val);
|
|
|
inOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
function postOrder(root: TreeNode | null): void {
|
|
|
if (root === null) {
|
|
|
return;
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(root.left);
|
|
|
postOrder(root.right);
|
|
|
list.push(root.val);
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "C"
|
|
|
|
|
|
```c title="binary_tree_dfs.c"
|
|
|
/* 前序遍历 */
|
|
|
void preOrder(TreeNode *root, int *size) {
|
|
|
if (root == NULL)
|
|
|
return;
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
arr[(*size)++] = root->val;
|
|
|
preOrder(root->left, size);
|
|
|
preOrder(root->right, size);
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
void inOrder(TreeNode *root, int *size) {
|
|
|
if (root == NULL)
|
|
|
return;
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(root->left, size);
|
|
|
arr[(*size)++] = root->val;
|
|
|
inOrder(root->right, size);
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
void postOrder(TreeNode *root, int *size) {
|
|
|
if (root == NULL)
|
|
|
return;
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(root->left, size);
|
|
|
postOrder(root->right, size);
|
|
|
arr[(*size)++] = root->val;
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "C#"
|
|
|
|
|
|
```csharp title="binary_tree_dfs.cs"
|
|
|
/* 前序遍历 */
|
|
|
void preOrder(TreeNode? root) {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
list.Add(root.val);
|
|
|
preOrder(root.left);
|
|
|
preOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
void inOrder(TreeNode? root) {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(root.left);
|
|
|
list.Add(root.val);
|
|
|
inOrder(root.right);
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
void postOrder(TreeNode? root) {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(root.left);
|
|
|
postOrder(root.right);
|
|
|
list.Add(root.val);
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "Swift"
|
|
|
|
|
|
```swift title="binary_tree_dfs.swift"
|
|
|
/* 前序遍历 */
|
|
|
func preOrder(root: TreeNode?) {
|
|
|
guard let root = root else {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
list.append(root.val)
|
|
|
preOrder(root: root.left)
|
|
|
preOrder(root: root.right)
|
|
|
}
|
|
|
|
|
|
/* 中序遍历 */
|
|
|
func inOrder(root: TreeNode?) {
|
|
|
guard let root = root else {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
inOrder(root: root.left)
|
|
|
list.append(root.val)
|
|
|
inOrder(root: root.right)
|
|
|
}
|
|
|
|
|
|
/* 后序遍历 */
|
|
|
func postOrder(root: TreeNode?) {
|
|
|
guard let root = root else {
|
|
|
return
|
|
|
}
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
postOrder(root: root.left)
|
|
|
postOrder(root: root.right)
|
|
|
list.append(root.val)
|
|
|
}
|
|
|
```
|
|
|
|
|
|
=== "Zig"
|
|
|
|
|
|
```zig title="binary_tree_dfs.zig"
|
|
|
// 前序遍历
|
|
|
fn preOrder(comptime T: type, root: ?*inc.TreeNode(T)) !void {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:根节点 -> 左子树 -> 右子树
|
|
|
try list.append(root.?.val);
|
|
|
try preOrder(T, root.?.left);
|
|
|
try preOrder(T, root.?.right);
|
|
|
}
|
|
|
|
|
|
// 中序遍历
|
|
|
fn inOrder(comptime T: type, root: ?*inc.TreeNode(T)) !void {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:左子树 -> 根节点 -> 右子树
|
|
|
try inOrder(T, root.?.left);
|
|
|
try list.append(root.?.val);
|
|
|
try inOrder(T, root.?.right);
|
|
|
}
|
|
|
|
|
|
// 后序遍历
|
|
|
fn postOrder(comptime T: type, root: ?*inc.TreeNode(T)) !void {
|
|
|
if (root == null) return;
|
|
|
// 访问优先级:左子树 -> 右子树 -> 根节点
|
|
|
try postOrder(T, root.?.left);
|
|
|
try postOrder(T, root.?.right);
|
|
|
try list.append(root.?.val);
|
|
|
}
|
|
|
```
|
|
|
|
|
|
!!! note
|
|
|
|
|
|
我们也可以仅基于循环实现前、中、后序遍历,有兴趣的同学可以自行实现。
|
|
|
|
|
|
递归过程可分为“递”和“归”两个相反的部分。“递”表示开启新方法,程序在此过程中访问下一个节点;“归”表示函数返回,代表该节点已经访问完毕。如下图所示,为前序遍历二叉树的递归过程。
|
|
|
|
|
|
=== "<1>"
|
|
|
![前序遍历的递归过程](binary_tree_traversal.assets/preorder_step1.png)
|
|
|
|
|
|
=== "<2>"
|
|
|
![preorder_step2](binary_tree_traversal.assets/preorder_step2.png)
|
|
|
|
|
|
=== "<3>"
|
|
|
![preorder_step3](binary_tree_traversal.assets/preorder_step3.png)
|
|
|
|
|
|
=== "<4>"
|
|
|
![preorder_step4](binary_tree_traversal.assets/preorder_step4.png)
|
|
|
|
|
|
=== "<5>"
|
|
|
![preorder_step5](binary_tree_traversal.assets/preorder_step5.png)
|
|
|
|
|
|
=== "<6>"
|
|
|
![preorder_step6](binary_tree_traversal.assets/preorder_step6.png)
|
|
|
|
|
|
=== "<7>"
|
|
|
![preorder_step7](binary_tree_traversal.assets/preorder_step7.png)
|
|
|
|
|
|
=== "<8>"
|
|
|
![preorder_step8](binary_tree_traversal.assets/preorder_step8.png)
|
|
|
|
|
|
=== "<9>"
|
|
|
![preorder_step9](binary_tree_traversal.assets/preorder_step9.png)
|
|
|
|
|
|
=== "<10>"
|
|
|
![preorder_step10](binary_tree_traversal.assets/preorder_step10.png)
|
|
|
|
|
|
=== "<11>"
|
|
|
![preorder_step11](binary_tree_traversal.assets/preorder_step11.png)
|
|
|
|
|
|
### 复杂度分析
|
|
|
|
|
|
**时间复杂度**:所有节点被访问一次,使用 $O(n)$ 时间,其中 $n$ 为节点数量。
|
|
|
|
|
|
**空间复杂度**:在最差情况下,即树退化为链表时,递归深度达到 $n$ ,系统占用 $O(n)$ 栈帧空间。
|