Meta·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Apr 2026

Summary

Meta system design round, just one question about building an LRU cache. Felt pretty short but they go deep fast.

Questions Asked (1)

Design an LRU cache.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

Started with a hashmap plus doubly linked list, which is the obvious path, and they pushed pretty quickly on eviction edge cases and thread safety.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (capacity, operations, thread-safety) and then propose a design using a hash map and a doubly linked list to achieve O(1) time for both get and put. Walk through the implementation details, discuss trade-offs, and consider edge cases and potential optimizations.

Pro tip: Mention that you would use a doubly linked list with sentinel nodes to simplify edge cases, and discuss how you would handle concurrency if needed (e.g., using locks or a concurrent data structure). This shows attention to detail and production readiness.

1. Clarify Requirements

Ask about expected capacity, operations (get, put), thread-safety, and performance requirements. Confirm that O(1) time complexity is desired.

2. Choose Data Structures

Propose a hash map for O(1) access to cache entries and a doubly linked list to maintain usage order. Explain how they work together.

3. Detail Operations

Describe how get and put work: on get, move the accessed item to the front (most recently used); on put, add new item to front and evict the least recently used (tail) if capacity exceeded.

4. Handle Edge Cases and Optimizations

Discuss edge cases like updating existing keys, capacity of 1, and thread-safety. Mention possible optimizations like using sentinel nodes or a custom linked list.

5. Analyze Complexity and Trade-offs

State that both operations are O(1) time and O(capacity) space. Discuss trade-offs between different implementations (e.g., using OrderedDict in Python vs. manual implementation).

Key Points to Mention

Hash map provides O(1) lookup, doubly linked list maintains recency order.
Eviction policy: least recently used item is at the tail of the list.
Get operation moves the accessed node to the head (most recently used).
Put operation inserts at head and evicts tail if over capacity.
Thread-safety considerations: use locks or concurrent data structures if needed.
Time complexity: O(1) for both get and put; space complexity: O(capacity).

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.