Optimize compression for in-place
Last updated: January 14, 2026
Quick Overview
Given a large dataset stored in a fixed-size array, implement an algorithm to optimize the compression of the data in-place, minimizing the memory overhead while ensuring that the original data can be reconstructed accurately. Your solution should handle various data types and should not use additional data structures that exceed O(1) space complexity. The output should be the compressed representation of the data within the same array.
Zillow
January 14, 202614
12
111 solved
Given a large dataset stored in a fixed-size array, implement an algorithm to optimize the compression of the data in-place, minimizing the memory overhead while ensuring that the original data can be reconstructed accurately. Your solution should handle various data types and should not use additional data structures that exceed O(1) space complexity. The output should be the compressed representation of the data within the same array.
Zillow uses this problem in the Technical Screen to evaluate your algorithmic thinking. They expect you to discuss multiple approaches, analyze trade-offs between them, and implement the optimal solution with clean, readable code.
What the Interviewer Expects
- Quickly identify the optimal approach and its theoretical basis
- Handle complex algorithm design with multiple interacting components
- Write concise, elegant code under time pressure
- Prove correctness of your approach and discuss alternative solutions
- Optimize beyond the obvious: discuss constant factor improvements
- Address follow-up variations and explain how the solution generalizes
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
- Can you solve this in a single pass?
- What is the worst-case input for your solution?
- What if the input doesn't fit in memory?
- What happens if the input contains duplicates?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Practice DSA ProblemsSample Answer
Problem Analysis
To solve the problem of optimizing compression for a fixed-size array in-place, we can utilize a two-pointer technique. This approach is applicable here because the task involves reading through t...
Approach
- Initialization: Start with a
write_indexinitialized to 0, which will track where we write compressed data. - Iterate: Use a loop to traverse the array with a
read_index. For each uni...
Submit Your Answer
