compression on Binary Tree
Last updated: November 25, 2025
Quick Overview
Given a binary tree, compress it into a more space-efficient representation by eliminating unnecessary nodes while maintaining the structure of the tree. The output should be a new binary tree that reflects this compressed version. Your function should take the root of the original binary tree as input and return the root of the compressed binary tree.
TikTok
November 25, 20253
9
1,021 solved
Given a binary tree, compress it into a more space-efficient representation by eliminating unnecessary nodes while maintaining the structure of the tree. The output should be a new binary tree that reflects this compressed version. Your function should take the root of the original binary tree as input and return the root of the compressed binary tree.
Coding interviews at TikTok focus on problem-solving approach as much as the final solution. The interviewer wants to see you break down the problem, consider edge cases, and optimize iteratively. Communication throughout the process is key.
What the Interviewer Expects
- Identify the correct data structure and algorithm for the problem
- Write clean, bug-free code with proper variable naming
- Analyze time and space complexity correctly
- Handle basic edge cases (empty input, single element)
- Communicate your thought process while coding
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- How would you parallelize this solution?
- How would you test this solution thoroughly?
- What happens if the input contains duplicates?
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Practice DSA ProblemsSample Answer
Problem Analysis
To compress the binary tree, we need to eliminate unnecessary nodes while maintaining the structure. The key pattern here is Depth-First Search (DFS). This is appropriate because we need to traver...
Approach
We will use a recursive DFS approach to traverse the tree. The steps are as follows:
- Start at the root node and check if it is null. If so, return null.
- Recursively call the function on the left...
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