二叉树的前序遍历、中序遍历、后序遍历的非递归实现方式

2019年4月13日17:20:51   今天上午华为面试的手撕代码题目！感触良多！

// 前序遍历 ，递归写法
    public void frontTraversal(treeNode node) {
        if (node != null) {
            System.out.print(node.data+" ");
            frontTraversal(node.left);
            frontTraversal(node.right);
        }
    }

    //中序遍历 midTraversal，递归写法
    public void midTraversal(treeNode node) {
        if (node != null) {
           midTraversal(node.left);
           System.out.print(node.data+" ");
           midTraversal(node.right);
        }
    }

    
    //后序遍历，递归写法
    public void afterTraversal(treeNode node) {
        if (node != null) {
            afterTraversal(node.left);
            afterTraversal(node.right);
            System.out.print(node.data+" ");
        }
    }



// 前序遍历，非递归写法，利用stack
    public void frontTraversalNew(treeNode node) {
        Stack stack =new Stack<>();
        while(node != null || !stack.isEmpty()) {
            while(node != null) {
                System.out.print(node.data+" ");
                stack.push(node);
                node = node.left;
            }
            if (! stack.isEmpty()) {
                node = stack.pop();
                node = node.right;
            }
        }
    }

    //中序遍历，非递归写法，利用stack
    public void midTraversalNew(treeNode node) {
        Stack stack = new Stack<>();
        while(node != null || !stack.isEmpty()) {
            while(node != null) {
                stack.push(node);
                node = node.left;
            }
            if (!stack.isEmpty()) {
                node = stack.pop();
                System.out.print(node.data+" ");
                node = node.right;
            }
        }
        
    }

    //后序遍历，非递归写法，利用stack两个
    public void afterTraversalNew(treeNode node) {
        Stack stackForNode = new  Stack<>();
        Stack< Integer> stackForState =new Stack<>();
        int state =1;
        while(node != null || !stackForNode.isEmpty()) {
            while(node != null) {
                stackForNode.push(node);
                stackForState.push(0);
                node  = node.left;
            }           
            while(!stackForNode.isEmpty() && stackForState.peek()==state) {
                stackForState.pop();
                //node = stackForNode.pop();
                System.out.print(stackForNode.pop().data+" ");
            }
            if( !stackForNode.isEmpty()) {
                stackForState.pop();
                stackForState.push(1);
                node = stackForNode.peek();
                node = node.right;
            }
        }
        
    }

补充一个小代码：图的深度优先遍历（DFS）

package dataStructure;

import java.util.Arrays;
import java.util.Stack;

public class GraphTest {
    public static void main(String[] args) {
        Vertex v1 =new Vertex('A');
        Vertex v2 =new Vertex('B');
        Vertex v3 =new Vertex('C');
        Vertex v4 =new Vertex('D');
        Vertex v5 =new Vertex('E');
        
        Graph graph =new Graph(5);
        graph.addVertex(v1);
        graph.addVertex(v2);
        graph.addVertex(v3);
        graph.addVertex(v4);
        graph.addVertex(v5);

       graph.addEdge('A', 'B');
       graph.addEdge('A', 'C');
       graph.addEdge('A', 'D');
       graph.addEdge('B', 'E');
       graph.addEdge('C', 'E');    
       
       for(int [] a: graph.adjMat) {
           System.out.println(Arrays.toString(a));
       }
       System.out.println("深度优先搜索的结果：");
       graph.DFS();
    }
}

class Vertex{
    public char Value;
    public boolean wasVisited = false;
    
    public Vertex(char value) {
        // TODO Auto-generated constructor stub
        this.Value =  value;
    }
    public char getValue() {
        return Value;
    }
}


class Graph{
    private int GraphSize;
    public Stack stack = new Stack<>();
    
    public int getGraphSize() {
        return GraphSize;
    }
    public int currentSize;
    public Vertex []  vertexs ;
    public int[][] adjMat;
    
    public Graph(int size) {
        // TODO Auto-generated constructor stub
        this.GraphSize = size;
        vertexs = new Vertex[size];
        adjMat = new int[size][size];
    }
    //向当前图中添加节点
    public void addVertex(Vertex v) {
        adjMat[currentSize][currentSize] = 1; //每次加入一个节点就将对角线  置为1
        vertexs[currentSize++] = v;
    }
    
    public void addEdge(char a,char b) {
        int index1 = 0;
        for (int i=0;i < vertexs.length; i++) {
            if (vertexs[i].Value == a) {
                index1 = i;
                break;
            }
        }
        int index2 = 0;
        for (int i=0;i < vertexs.length; i++) {
            if (vertexs[i].Value == b) {
                index2 = i;
                break;
            }
        }
        adjMat[index1][index2] = 1;
        adjMat[index2][index1] = 1;
    }
    
    public void DFS() {
        int maxDeep=1;
        vertexs[0].wasVisited = true;
        stack.push(0);
        System.out.println(vertexs[0].Value);
        
        while(! stack.isEmpty()) {
            for(int i= stack.peek()+1;i

单链表的逆序输出 + 单链表的逆向（都使用递归来做）

		//使用递归，倒序输出链表
		public void reversePrint(Node node) {
			if (node.next == null ) {
				System.out.print(node.getValue()+" ");
				return;
			}
			reversePrint(node.next);
			System.out.print(node.getValue()+" ");
		}
		
		//使用递归，实现链表的反转	
		/** https://blog.csdn.net/guyuealian/article/details/51119499
		 * @param head  当前链表的头结点
		 * @return
		 */
		public Node reverseLink(Node head) {
		    if (head == null || head.next == null) {
		        return head;
		    }
		    Node newHead = reverseLink(head.next);
		    head.next.next = head;
		    head.next=null;
		    return newHead;
		}