算法概述

递归算法简洁明了、可读性好，但与非递归算法相比要消耗更多的时间和存储空间。为提高效率，我们可采用一种非递归的二叉树遍历算法。非递归的实现要借助栈来实现，因为堆栈的先进后出的结构和递归很相似。

对于中序遍历来说，非递归的算法比递归算法的效率要高的多。其中序遍历算法的实现的过程如下：

(1).初始化栈，根结点进栈；

(2).若栈非空，则栈顶结点的左孩子结点相继进栈，直到null(到叶子结点时)退栈；访问栈顶结点(执行visit操作)并使栈顶结点的右孩子结点进栈成为栈顶结点。

(3).重复执行(2)，直至栈为空。

算法实现

package datastructure.tree;

import datastructure.stack.ArrayStack;

import datastructure.stack.Stack;

public class UnrecOrderBTree implements Visit{

private Stack stack = new ArrayStack();

private BTree bt;

@Override

public void visit(BTree btree) {

System.out.print("\t" + btree.getRootData());

}

public void inOrder(BTree boot) {

stack.clear();

stack.push(boot);

while(!stack.isEmpty()) {

//左孩子结点进栈

while((bt = ((BTree)(stack.peek())).getLeftChild()) != null) {

stack.push(bt);

}

//如果该结点没有右孩子，则逐级往上出栈

while(!stack.isEmpty() &&!( (BTree)stack.peek() ).hasRightTree()) {

bt = (BTree)stack.pop();

visit(bt);

}

//如果该结点有右孩子，则右孩子进栈

if(!stack.isEmpty() && ( (BTree)stack.peek() ).hasRightTree()){

bt = (BTree)stack.pop();

visit(bt);

stack.push(bt.getRightChild());

}

}

}

}

测试：

package datastructure.tree;

/**

* 测试二叉树

* @author Administrator

*

*/

public class BTreeTest {

public static void main(String args[]) {

BTree btree = new LinkBTree('A');

BTree bt1, bt2, bt3, bt4;

bt1 = new LinkBTree('B');

btree.addLeftTree(bt1);

bt2 = new LinkBTree('D');

bt1.addLeftTree(bt2);

bt3 =  new LinkBTree('C');

btree.addRightTree(bt3);

bt4 =  new LinkBTree('E');

bt3.addLeftTree(bt4);

bt4 =  new LinkBTree('F');

bt3.addRightTree(bt4);

RecursionOrderBTree order = new RecursionOrderBTree();

System.out.println("\n中序遍历：");

order.inOrder(btree);

}

}

结果如下：

中序遍历：

D B  A E

C   F

转载至：http://blog.csdn.net/luoweifu/article/details/9079799