Introduction

In this blog post, we will explore how to solve the LeetCode problem "1379" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

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. Return a reference to the same node in the cloned tree. Note that you are not allowed to change any of the two trees or the target node and the answer must be a reference to a node in the cloned tree. Example 1: 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. Example 2: Input: tree = [7], target = 7 Output: 7 Example 3: Input: tree = [8,null,6,null,5,null,4,null,3,null,2,null,1], target = 4 Output: 4 Constraints: The number of nodes in the tree is in the range [1, 104]. The values of the nodes of the tree are unique. target node is a node from the original tree and is not null. Follow up: Could you solve the problem if repeated values on the tree are allowed?

Explanation

Here's a breakdown of the approach, complexities, and the Python code:

• Key Approach:

  • Perform a simultaneous traversal of both the original and cloned trees.
  • Compare nodes in the original tree with the target node.
  • When the target node is found in the original tree, return the corresponding node in the cloned tree.

• Complexity:

  • Runtime Complexity: O(N), where N is the number of nodes in the tree (worst-case, we might have to traverse the entire tree). Storage Complexity: O(H), where H is the height of the tree (due to the call stack during recursion; worst-case O(N) for a skewed tree, best/average case O(log N) for a balanced tree).

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

def getTargetCopy(original: TreeNode, cloned: TreeNode, target: TreeNode) -> TreeNode:
    """
    Finds the corresponding node in the cloned tree that matches the target node in the original tree.

    Args:
        original: The original binary tree.
        cloned: The cloned binary tree (a copy of the original).
        target: The target node to find in the original tree.

    Returns:
        The corresponding node in the cloned tree.
    """

    def inorder_traversal(orig_node, cloned_node):
        if not orig_node:
            return None

        if orig_node is target:
            return cloned_node

        left_result = inorder_traversal(orig_node.left, cloned_node.left)
        if left_result:
            return left_result

        return inorder_traversal(orig_node.right, cloned_node.right)

    return inorder_traversal(original, cloned)