The implement of Binary Search Tree (JAVA)

An implement of Binary Search Tree in JAVA

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/** *  * Binary search tree (BST) is a node-based binary tree data structure which has * the following properties: *  * The left subtree of a node contains only nodes with keys less than the node's * key. The right subtree of a node contains only nodes with keys greater than * the node's key. Both the left and right subtrees must also be binary search * trees. From the above properties, it naturally follows that each node (item * in the tree) has a distinct key. Generally, the information represented by * each node is an Object element. However, for sequencing purposes, nodes are * compared according to their keys rather than any part of their associated * records. *  * The major advantage of binary search trees over other data structures is that * the related sorting algorithms and search algorithms such as in-order * traversal can be very efficient. * *//** * 创建（插入）, 查找, 遍历 删除 *  * 最大最小节点 *  * */public class BinSearchTree {private class Node {int value;Node left;Node right;Node(int value) {this.value = value;left = null;right = null;}}public BinSearchTree() {}/** * 由一个数组构造BST * */public BinSearchTree(int[] array) {for (int value : array) {insert(value);}}private Node root;/** * 全部由根部开始插入 * */public void insert(int value) {root = insert(root, value);}/** * 插入，根据节点值，判断插入到左边还是右边 * */public Node insert(Node node, int value) {if (node == null) {node = new Node(value);} else {if (value < node.value) {node.left = insert(node.left, value);} else {node.right = insert(node.right, value);}}return node;}/** * 打印结果 * */public void visit(Node node) {if (node == null) {return;} else {System.out.println(node.value);}}/** * 中序遍历 * */public void in_order_traves(Node node) {if (node == null) {return;} else {in_order_traves(node.left);visit(node);in_order_traves(node.right);}}/** * 查找，其实就是二分查找 * */public Node bst_search(Node root, int key) {Node found = null;if (root == null) {found = null;} else {if (root.value == key) {found = root;}if (root.value < key) {found = bst_search(root.right, key);}if (root.value > key) {found = bst_search(root.left, key);}}return found;}/** * 最大 * */public Node getMax(Node node) {Node cur = node;while (cur.right != null) {cur = cur.right;}return cur;}/** * 最小 * */public Node getMin(Node node) {Node cur = node;while (cur.left != null) {cur = cur.left;}return cur;}/** * 删除 * */public void delectNode(Node root, int key) {if (root == null)return;Node found = root;Node parent = null;boolean isLeft = false; // 用于判断该节点是左还是右子节点// 先找到该节点及其父节点while (found.value != key) {if (found.value < key) {parent = found;found = found.right;isLeft = false;} else {parent = found;found = found.left;isLeft = true;}}if (parent == found && found.left == null && found.right == null) {this.root = null;}// 1.该节点为叶子节点，直接删除if (found.left == null && found.right == null) {found = null;if (isLeft) {parent.left = null;} else {parent.right = null;}} else {if (found.left != null && found.right != null) {// 2.该节点同时存在左右子树, 将found 中左子树的最大值 付给原节点,然后 删除左子树中的最大节点Node now = getMax(found.left);delectNode(root, now.value);found.value = now.value;} else {// 3.该节点只有一个子树，则将其自树接到原父节点if (parent != null) {if (isLeft) {if (found.left != null)parent.left = found.left;elseparent.left = found.right;} else {if (found.left != null)parent.right = found.left;elseparent.right = found.right;}} else {this.root = found.left != null ? found.left : found.right;}}}}/** * 获取树的深度 * */public int getDepth(Node btree) {int rtnleft = 1;int rtnright = 1;if (btree == null) {return 0;}rtnleft = getDepth(btree.left);rtnright = getDepth(btree.right);return rtnleft > rtnright ? rtnleft + 1 : rtnright + 1;}// need to be improvedpublic void show(Node root) {Queue<Node> a = new Queue<Node>();Queue<Node> b = new Queue<Node>();a.enqueue(root);int blank = getDepth(root);while (!a.isEmpty()) {for (int i = 0; i < blank; i++)System.out.print(" ");Node node = a.dequeue(null);System.out.print(node.value);if (node.left != null)b.enqueue(node.left);if (node.right != null)b.enqueue(node.right);System.out.print(" ");if (a.isEmpty())System.out.println();while (!b.isEmpty()) {for (int i = 0; i < blank; i++)System.out.print(" ");Node node2 = b.dequeue(null);System.out.print(node2.value);if (node2.left != null)a.enqueue(node2.left);if (node2.right != null)a.enqueue(node2.right);System.out.print(" ");if (b.isEmpty())System.out.println();}}}public static void main(String[] args) {int arr[] = { 1, 2, 4, 3, 6, 9, 5 };BinSearchTree bst = new BinSearchTree(arr);bst.show(bst.root);}}

/**
 * 
 * Binary search tree (BST) is a node-based binary tree data structure which has
 * the following properties:
 * 
 * The left subtree of a node contains only nodes with keys less than the node's
 * key. The right subtree of a node contains only nodes with keys greater than
 * the node's key. Both the left and right subtrees must also be binary search
 * trees. From the above properties, it naturally follows that each node (item
 * in the tree) has a distinct key. Generally, the information represented by
 * each node is an Object element. However, for sequencing purposes, nodes are
 * compared according to their keys rather than any part of their associated
 * records.
 * 
 * The major advantage of binary search trees over other data structures is that
 * the related sorting algorithms and search algorithms such as in-order
 * traversal can be very efficient.

 * */

Functions:

Create

Insert

Search

Travel

Delete

Find Min and Max

Display