Search⌘ K
AI Features

Solution: Height of Binary Tree After Subtree Removal Queries

Understand how to efficiently calculate the height of a binary tree after removing specified subtrees. Learn to use depth-first search to track node depths and heights, and how to handle multiple queries to update the tree's height without rebuilding it from scratch. This lesson helps you apply key tree traversal techniques to solve complex removal queries.

Statement

We are given the root of a binary tree with nn nodes and an array, queries, of size mm. Each query represents the root of a subtree that should be removed from the tree. The task here is to determine the height of the binary tree after each query, i.e., once a subtree is removed. We'll store the updated heights against each query in an array and return it.

Note: A tree’s height is the number of edges in the longest path from the root to any leaf node in the tree.

A few points to be considered:

  • All the values in the tree are unique.

  • It is guaranteed that queries[i] will not be equal to the value of the root.

  • The queries are independent, so the tree returns to its initial state after each query.

Constraints:

  • 22 \leq nn 500\leq 500 ...