Leetcode #1602: Find Nearest Right Node in Binary Tree
In this guide, we solve Leetcode #1602 Find Nearest Right Node in Binary Tree in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given the root of a binary tree and a node u in the tree, return the nearest node on the same level that is to the right of u, or return null if u is the rightmost node in its level. Example 1: Input: root = [1,2,3,null,4,5,6], u = 4 Output: 5 Explanation: The nearest node on the same level to the right of node 4 is node 5.
Quick Facts
- Difficulty: Medium
- Premium: Yes
- Tags: Tree, Breadth-First Search, Binary Tree
Intuition
We need level-by-level exploration or shortest steps, which is ideal for BFS.
A queue naturally models the frontier of the search.
Approach
Push initial nodes into a queue and expand in layers.
Track visited nodes to prevent cycles.
Steps:
- Initialize queue with start nodes.
- Process level by level.
- Track visited nodes.
Example
Input: root = [1,2,3,null,4,5,6], u = 4
Output: 5
Explanation: The nearest node on the same level to the right of node 4 is node 5.
Python Solution
# 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 findNearestRightNode(self, root: TreeNode, u: TreeNode) -> Optional[TreeNode]:
q = deque([root])
while q:
for i in range(len(q) - 1, -1, -1):
root = q.popleft()
if root == u:
return q[0] if i else None
if root.left:
q.append(root.left)
if root.right:
q.append(root.right)
Complexity
The time complexity is , and the space complexity is . The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.