98. Validate Binary Search Tree
Description
Given the root of a binary tree, determine if it is a valid binary search tree (BST).
A valid BST is defined as follows:
- The left subtree of a node contains only nodes with keys strictly less than the node’s key.
- The right subtree of a node contains only nodes with keys strictly greater than the node’s key.
- Both the left and right subtrees must also be binary search trees.
Example 1:

- Input: root = [2,1,3]
- Output: true
Example 2:

- Input: root = [5,1,4,null,null,3,6]
- Output: false
- Explanation: The root node’s value is 5 but its right child’s value is 4.
Constraints:
- The number of nodes in the tree is in the range [1, 104].
- -231 <= Node.val <= 231 - 1
Submitted Code
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
class Solution:
def isValidBST(self, root: Optional[TreeNode]) -> bool:
def dfs(node, low, high):
if not node:
return True
if not low < node.val < high:
return False
return dfs(node.left, low, node.val) and dfs(node.right, node.val, high)
return dfs(root, -float('inf'), float('inf'))
Runtime: 0 ms | Beats 100.00%
Memory: 20.84 MB | Beats 74.49%
부모 노드뿐만 아니라 조상 노드에서부터 정해진 범위를 만족해야 하기 때문에 허용 범위(min, max) 값을 넘겨주는 방법을 사용했다.
Other Solutions
1st
class Solution:
def isValidBST(self, root: TreeNode) -> bool:
# Use maximal system integer to represent infinity
INF = sys.maxsize
def helper(node, lower, upper):
if not node:
# empty node or empty tree
return True
if lower < node.val < upper:
# check if all tree nodes follow BST rule
return helper(node.left, lower, node.val) and helper(node.right, node.val, upper)
else:
# early reject when we find violation
return False
# ----------------------------------
return helper( node=root, lower=-INF, upper=INF )
time complexity: 𝑂(𝑛)
space complexity: 𝑂(ℎ)