标签:
Given a binary tree, return the inorder traversal of its nodes‘ values.
Example
Given binary tree {1,#,2,3},
   1
         2
    /
   3
return [1,3,2].
SOLUTION 1:
递归方法,具体代码可以参照preorder traversal,这里就不赘述了。
SOLUTION 2:
分治法,Divide & conquer,其实这个代码也可以参照preorder traversal,只贴个代码吧:
public class Solution {
    /**
     * @param root: The root of binary tree.
     * @return: Inorder in ArrayList which contains node values.
     */
    public ArrayList<Integer> inorderTraversal(TreeNode root) {
        ArrayList<Integer> result = new ArrayList<Integer>();
        if (root == null){
            return result;
        }
        ArrayList<Integer> left = inorderTraversal(root.left);
        ArrayList<Integer> right = inorderTraversal(root.right);
        // 差别就是result里面先加入了left,再root,再right
        result.addAll(left);
        result.add(root.val);
        result.addAll(right);
        return result;
    }
}
SOLUTION 3:
非递归,non-recursion,首先我们模拟一下这个中序遍历过程,就是用一个cur指针从root 一路走到最左下角叶节点(DFS),然后逐层回退,访问回退节点的右节点,当走到右节点的叶节点时再继续回退找下一个右节点。
由于stack.pop()之后就找不到这个树上的点的位置了,所以要用一个点纪录一下,这个根节点,然后继续访问以这个记录点为根的右节点。代码如下:
public class Solution {
    /**
     * @param root: The root of binary tree.
     * @return: Inorder in ArrayList which contains node values.
     */
    public ArrayList<Integer> inorderTraversal(TreeNode root) {
        ArrayList<Integer> result = new ArrayList<Integer>();
        if (root == null){
            return result;
        }
        Stack<TreeNode> stack = new Stack<TreeNode>();
        TreeNode cur = root;
        while (cur != null || !stack.empty()){
            while (cur != null){
                stack.push(cur);
                cur = cur.left;
            }
            cur = stack.peek();
            stack.pop();
            result.add(cur.val);
            cur = cur.right;
        }
        return result;
    }
}
[lintcode] Binary Tree Inorder Traversal
标签:
原文地址:http://www.cnblogs.com/tritritri/p/4856872.html