Leetcode #1379: Find a Corresponding Node of a Binary Tree in a Clone of That Tree
In this guide, we solve Leetcode #1379 Find a Corresponding Node of a Binary Tree in a Clone of That 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 two binary trees original and cloned and given a reference to a node target in the original tree. The cloned tree is a copy of the original tree.
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Tree, Depth-First Search, Breadth-First Search, Binary Tree
Intuition
We need to explore a structure deeply before backing up, which suits DFS.
DFS keeps local context on the call stack and is easy to implement recursively.
Approach
Define a recursive DFS that carries the necessary state.
Combine child results as the recursion unwinds.
Steps:
- Define a recursive DFS with state.
- Visit children and combine results.
- Return the final aggregation.
Example
Input: tree = [7,4,3,null,null,6,19], target = 3
Output: 3
Explanation: In all examples the original and cloned trees are shown. The target node is a green node from the original tree. The answer is the yellow node from the cloned tree.
Python Solution
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def getTargetCopy(
self, original: TreeNode, cloned: TreeNode, target: TreeNode
) -> TreeNode:
def dfs(root1: TreeNode, root2: TreeNode) -> TreeNode:
if root1 is None:
return None
if root1 == target:
return root2
return dfs(root1.left, root2.left) or dfs(root1.right, root2.right)
return dfs(original, cloned)
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.