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Apple·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Apple SWE interview with a classic LRU cache design question. Pretty standard stuff for this level but the implementation details are where it gets tricky.

Questions Asked (1)

Q1

Design and implement an LRU cache that supports get and put operations in O(1) average time, with eviction of the least recently used entry when capacity is exceeded.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

You need a hash map plus a doubly linked list working together.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a hash map combined with a doubly linked list to achieve O(1) get and put. Walk through the design, implement key methods, and discuss trade-offs and edge cases.

Pro tip: Mention that you would use a doubly linked list with sentinel head and tail nodes to simplify edge cases, and discuss how this design can be extended for thread safety or persistence if needed.

1. Clarify Requirements

Ask about expected capacity, concurrency needs, and whether the cache should be thread-safe. Confirm that get and put must be O(1) average time.

2. Propose Data Structures

Explain that a hash map provides O(1) access to nodes, and a doubly linked list maintains recency order. The hash map maps keys to nodes in the list.

3. Detail Operations

Describe how get moves the accessed node to the front (most recently used), and put inserts or updates a node, moving it to the front, and evicts the tail (least recently used) if capacity is exceeded.

4. Implement Key Methods

Write pseudocode or actual code for get and put, using helper methods like addToFront, removeNode, and moveToFront. Handle edge cases like updating an existing key.

5. Discuss Trade-offs and Extensions

Talk about time and space complexity, potential improvements like using a circular doubly linked list, and how to make it thread-safe with locks or concurrent data structures.

Key Points to Mention

  • Hash map for O(1) key lookup, mapping to nodes in a doubly linked list.
  • Doubly linked list to maintain recency order, with O(1) insertion and deletion.
  • Use of sentinel head and tail nodes to simplify boundary conditions.
  • Eviction policy: remove the least recently used node (tail) when capacity is exceeded.
  • Time complexity: O(1) average for both get and put; space complexity: O(capacity).
  • Thread safety considerations: use locks or concurrent data structures if needed.

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