数据结构(C#)_查找(动态查找)

我们接着上次的静态查找表，今天主要介绍动态查找表的二叉排序树。动态查找表的的特点是表结构本身是在查找过程中动态生成的，查找指定的关键码，若表中存在则返回成功，若不存在则插入关键码。下面我们介绍动态查找表的二叉树实现。首先介绍二叉排序树的基本概念和性质。

具有如下性质：

1 若它的左子树不为空，则左子树上所有节点的值均小于根结点的值；

2 若它的右子树不为空，则右子树上所有节点的值均大于他的根结点的值；

3 他的左，右边子树分别为二叉排序树；

二叉排序树又叫二叉查找树，他最适合用于存储在结构中的数据随机存储，可以喝容易的做到查找一个特定值，查找最小和最大值。下面的代码演示了如何插入树结点，同时对树进行中序遍历，先序遍历以及后序遍历，查找最大，最小，指定值。

public class Node { public int Data { get; set; } public Node left; public Node right; public void DisplayNode() { Console.WriteLine(this.Data); } } public class BinarySearchTree { public Node root { get; set; } public BinarySearchTree() { root = new Node(); } /// <summary> /// Insert tree node /// </summary> /// <param name="data"></param> public void Insert(int data) { Node node = new Node(); node.Data = data; if (this.root == null) { root = node; } else { Node current = root; Node parent; while (true) { parent = current; if (data < current.Data) { // Point to left child tree current = current.left; if (current == null) { parent.left = node; return; } } else { // Point to right child tree current = current.right; if (current == null) { parent.right = node; return; } } } } } public void InOrder(Node root) { if (root != null) { InOrder(root.left); root.DisplayNode(); InOrder(root.right); } } public void PreOrder(Node root) { if (root != null) { root.DisplayNode(); PreOrder(root.left); PreOrder(root.right); } } public void PostOrder(Node root) { if (root != null) { PostOrder(root.left); PostOrder(root.right); root.DisplayNode(); } } /// <summary> /// Find min value /// </summary> /// <returns></returns> public int FindMinValue() { Node current = this.root; while (current.left != null) { current = current.left; } return current.Data; } /// <summary> /// Find max value /// </summary> /// <returns></returns> public int FinMaxValue() { Node current = this.root; while (current.right != null) { current = current.right; } return current.Data; } /// <summary> /// Find node by key /// </summary> /// <param name="key"></param> /// <returns></returns> public Node Find(int key) { Node current = this.root; while (current.Data != key) { if (current == null) { return null; } if (key < current.Data) { current = current.left; } else { current = current.right; } } return current; } /// <summary> /// Remove leaf node /// </summary> /// <param name="key"></param> /// <returns></returns> public bool RemoveLeaf(int key) { Node current = this.root; Node parent = this.root; bool isLeftChild = false; while (current.Data != key) { parent = current; if (current == null) { return false; } if (key < current.Data) { current = current.left; isLeftChild = true; } else { current = current.right; isLeftChild = false; } } if (current.left == null && current.right == null) { if (current == root) { root = null; } else if (isLeftChild) { parent.left = null; } else { parent.right = null; } } return true; } }

演示代码：

static void Main(string[] args) { // SequeceSearch(); // BinarySearch(); BinarySearchTree searchTree = new BinarySearchTree(); searchTree.Insert(23); searchTree.Insert(45); searchTree.Insert(16); searchTree.Insert(37); searchTree.Insert(3); searchTree.Insert(99); searchTree.Insert(22); searchTree.InOrder(searchTree.root); searchTree.PreOrder(searchTree.root); searchTree.PostOrder(searchTree.root); Console.ReadLine(); }