Classic question but I still fumbled the eviction logic for a second.
Start by clarifying the requirements: capacity, operations (get, put), and eviction policy. Then, describe the optimal data structure combination: a hash map for O(1) access and a doubly linked list for O(1) updates and evictions. Walk through the implementation details, including edge cases like updating existing keys and handling capacity limits.
Pro tip: Mention thread-safety considerations upfront, as production caches often need concurrent access. Also, discuss potential optimizations like using a sentinel head/tail to simplify edge cases.
Ask about expected capacity, operations (get, put), and eviction policy (LRU). Confirm that get and put should be O(1) time complexity.
Explain that a hash map alone is insufficient because it doesn't track order. Propose a combination: hash map for key-to-node mapping and a doubly linked list for recency order.
Detail how get and put work: on get, move the accessed node to the front (most recent); on put, add new node to front, and if capacity exceeded, remove the least recent node (tail).
Discuss updating an existing key (update value and move to front), and handling capacity of 0 or 1. Also, consider thread-safety if needed.
Conclude that both get and put are O(1) time and O(capacity) space. Mention that this is optimal for LRU cache.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.