描述
给一棵二叉树, 找到和为最小的子树, 返回其根节点。
注意事项
LintCode会打印根节点为你返回节点的子树。保证只有一棵和最小的子树并且给出的二叉树不是一棵空树。
样例
给一棵二叉树：
1
/ \
-5 2
/ \ / \
0 2 -4 -5
返回节点 1
代码
/**
* Definition of TreeNode:
* public class TreeNode {
* public int val;
* public TreeNode left, right;
* public TreeNode(int val) {
* this.val = val;
* this.left = this.right = null;
* }
* }
*/
方法1
// version 1 : traverse + divide conquer
public class Solution {
private TreeNode subtree = null;
private int subtreeSum = Integer.MAX_VALUE;
/**
* @param root the root of binary tree
* @return the root of the minimum subtree
*/
public TreeNode findSubtree(TreeNode root) {
helper(root);
return subtree;
}
// 计算子树和用分治算法，同时用全局变量纪录全局最小子树和（遍历）
private int helper(TreeNode root) {
if (root == null) {
return 0;
}
int sum = helper(root.left) + helper(root.right) + root.val;
if (sum <= subtreeSum) {
subtreeSum = sum;
subtree = root;
}
return sum;
}
}
方法2
用分治需要注意，ResultType 实际上定义的是3个变量，很容易把 sum 和
minSum 混为一谈， minSum 是记录以当前结点为根结点的二叉树的所有子树的二叉树和的最小值， 而 sum 代表当前结点为根结点的二叉树和，sum 是比较交换 minSum 的基础，sum 只有在递归到叶子结点时才起到作用，用于计算叶子结点的 minSum
// version 2: Pure divide conquer
class ResultType {
public TreeNode minSubtree;
public int sum, minSum;
public ResultType(TreeNode minSubtree, int minSum, int sum) {
this.minSubtree = minSubtree;
this.minSum = minSum;
this.sum = sum;
}
}
public class Solution {
/**
* @param root the root of binary tree
* @return the root of the minimum subtree
*/
public TreeNode findSubtree(TreeNode root) {
ResultType result = helper(root);
return result.minSubtree;
}
public ResultType helper(TreeNode node) {
if (node == null) {
return new ResultType(null, Integer.MAX_VALUE, 0);
}
ResultType leftResult = helper(node.left);
ResultType rightResult = helper(node.right);
ResultType result = new ResultType(
node,
leftResult.sum + rightResult.sum + node.val,
// 当前结点最小子树和先写成当前结点的和，然后再和左右子树的最小子树比较，判断是否需要重新赋值
leftResult.sum + rightResult.sum + node.val
);
if (leftResult.minSum <= result.minSum) {
result.minSum = leftResult.minSum;
result.minSubtree = leftResult.minSubtree;
}
if (rightResult.minSum <= result.minSum) {
result.minSum = rightResult.minSum;
result.minSubtree = rightResult.minSubtree;
}
return result;
}
}