Implement LRU Cache with O(1) space

Last updated: March 8, 2026

Quick Overview

Implement a Segment Tree data structure that supports get and put operations in O(1) time.

Adobe
Coding & Algorithms
Software Engineer
Adobe
March 8, 2026
Software Engineer
Technical Screen
Coding & Algorithms
Medium

34

13

1,647 solved


Implement a Segment Tree data structure that supports get and put operations in O(1) time.

Adobe 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
  • 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
Time and space complexity analysis
Tree structures and recursion
Hash maps and frequency counting
Common algorithm patterns (sliding window, two pointers, BFS/DFS)
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
  • How would you test this solution thoroughly?
  • Can you solve this iteratively instead of recursively (or vice versa)?
  • Can you optimize the space complexity of your solution?
  • How would you parallelize this solution?
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Sample Answer
Problem Analysis

The problem requires us to implement an LRU (Least Recently Used) Cache, which inherently means we need to keep track of the order in which items are accessed. The optimal solution for this problem is...

Approach
  1. Data Structures: Use a hash map to store the key-value pairs and a doubly linked list to keep track of the usage order.
  2. Put Operation:
    • If the key already exists in the cache, updat...

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