Implement LRU Cache with with follow-up

Last updated: May 7, 2026

Quick Overview

Implement a Priority Queue data structure that supports insert, delete, and lookup operations in O(log n) time.

Two Sigma
Coding & Algorithms
Software Engineer
Two Sigma
May 7, 2026
Software Engineer
Take-home Project
Coding & Algorithms
Medium

4

5

3,066 solved


Implement a Priority Queue data structure that supports insert, delete, and lookup operations in O(log n) time.

Coding interviews at Two Sigma 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
  • 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
Data structure selection and trade-offs
Sorting and searching
Graph algorithms and traversal
Dynamic programming and memoization
Tree structures and recursion
How to Approach This
  1. Clarify input constraints and edge cases before writing code.
  2. Walk through your approach verbally and confirm with the interviewer before coding.
  3. Start with a brute force solution, then optimize. Mention time and space complexity.
  4. Test your solution with examples, including edge cases like empty input or duplicates.
  5. Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
  • Can you optimize the space complexity of your solution?
  • Can you solve this iteratively instead of recursively (or vice versa)?
  • How would you modify your solution to handle streaming input?
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