Implement Segment Tree with with follow-up
Last updated: May 18, 2026
Quick Overview
Implement a LRU Cache data structure that supports get and put operations in O(log n) time.
Rippling
May 18, 20268
9
250 solved
Implement a LRU Cache data structure that supports get and put operations in O(log n) time.
This coding problem is frequently asked during Onsite at Rippling. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. Rippling expects candidates to write production-quality code, not just solve the puzzle.
What the Interviewer Expects
- Recognize the underlying problem pattern (sliding window, two pointers, BFS/DFS, etc.)
- Discuss multiple approaches and trade-offs before coding
- Implement an optimal solution with clean, production-quality code
- Handle all edge cases including boundary conditions and invalid input
- Optimize both time and space complexity with clear justification
- Test your solution systematically with well-chosen examples
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 test this solution thoroughly?
- Can you solve this iteratively instead of recursively (or vice versa)?
- What is the worst-case input for your solution?
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