java 实现的二叉查找树

好像一个多星期没写代码了，感觉手生很，脑袋不转啊。还是复习一下算法，今天早上把二叉查找树重写了一遍，而且还把节点的删除完全看明白了，

package com.kinglong.binarytree;/** * @author kinglong * @version 2011-6-26 上午09:29:40 */public class SearchTree {private Node root;public SearchTree() {root = null;}public SearchTree(Node root) {this.root = root;}// 插入节点public void insert(Node node) {if (root == null) {root = node;} else {Node temp = root;Node privous = temp;while (temp != null) {privous = temp;if (temp.getData() < node.getData()) {temp = temp.getRight();} else {temp = temp.getLeft();}}if (privous.getData() < node.getData()) {privous.setRight(node);} else {privous.setLeft(node);}node.setParent(privous);}}// 返回最小值的节点(默认值为)public Node Minimum() {return Minimum(root);}public Node Minimum(Node node) {Node temp = node;while (temp.getLeft() != null) {temp = temp.getLeft();}return temp;}// 返回最大值的节点 public Node Maximum() {Node temp = root;while (temp.getRight() != null) {temp = temp.getRight();}return temp;}// 查询包含关键字K的节点(非递归)public Node search(int k) {Node x = root;while (x != null) {if (x == null || k == x.getData()) {return x;} else if (k < x.getData()) {x = x.getLeft();} else {x = x.getRight();}}return x;}//查找包含关键字k的节点(递归)public Node searchRecursive(Node node, int k) {if (node == null || k == node.getData()) {return node;}if (k < node.getData()) {return searchRecursive(node.getLeft(), k);} else {return searchRecursive(node.getRight(), k);}}//返回后继节点public Node successor(int k) {Node node = search(k);return successor(node);}public Node successor(Node node) {if (node.getRight() != null) {return Minimum(node.getRight());}Node temp = node;Node parent = node.getParent();while (parent != null && parent.getRight() == temp) {temp = parent;parent = parent.getParent();}return parent;}//返回前驱节点public Node predecessor(int k) {Node node = search(k);return predecessor(node);} public Node predecessor(Node node) {if (node.getLeft() != null) {return node.getLeft();}Node temp = node;Node parent = node.getParent();while (parent != null && parent.getLeft() == temp) {temp = parent;parent = parent.getParent();}return parent;}//删除关键字为k的节点public Node delete(int k) {Node node = search(k);Node temp = null;Node tempChild = null;if (node.getLeft() == null || node.getRight() == null) {temp = node;} else {temp = successor(node);}if (temp.getLeft() != null) {tempChild = temp.getLeft();} else {tempChild = temp.getRight();}if (tempChild != null) {tempChild.setParent(temp.getParent());}if (temp.getParent() == null) {root = tempChild;} else if (temp.getParent().getRight() == temp) {temp.getParent().setRight(tempChild);} else if (temp.getParent().getLeft() == temp) {temp.getParent().setLeft(tempChild);}if (temp != node) {node.setData(temp.getData());}return temp;}//中序遍历public void printTree() {printTree(root);System.out.println(" ");}public void printTree(Node node) {if (node != null) {printTree(node.getLeft());System.out.print(node.getData() + " ");printTree(node.getRight());}}}class Node {private Node left;private Node right;private Node parent;private int data;public Node() {}public Node(int data) {this(data, null, null, null);}private Node(int data, Node parent, Node left, Node right) {this.data = data;this.left = left;this.parent = parent;this.right = right;}public Node getLeft() {return left;}public void setLeft(Node left) {this.left = left;}public Node getRight() {return right;}public void setRight(Node right) {this.right = right;}public Node getParent() {return parent;}public void setParent(Node parent) {this.parent = parent;}public int getData() {return data;}public void setData(int data) {this.data = data;}} 

测试代码：

package com.kinglong.binarytree;/** *@author kinglong *@version 2011-6-26 上午10:41:38 */public class SearchTest {public static void main(String[] args) {SearchTree tree = new SearchTree();tree.insert(new Node(5));tree.insert(new Node(2));tree.insert(new Node(10));tree.insert(new Node(17));tree.insert(new Node(3));tree.printTree();System.out.println("最大值："+tree.Maximum().getData());System.out.println("最小值："+tree.Minimum().getData());tree.delete(5);//删除5tree.printTree();System.out.println("节点3 的前驱为：" + tree.predecessor(3).getData());tree.insert(new Node(12));System.out.println("节点12的后继为：" + tree.successor(12).getData());}} 

 

算法的重点在于找节点的后继，节点的前驱，和删除。