I knew the answer involved a hash map and a doubly linked list but actually coding it up cleanly under pressure is a different story.
Start by clarifying the requirements and constraints, then propose a design using a hash map and a doubly linked list to achieve O(1) operations. Walk through the implementation details, including edge cases, and discuss potential optimizations and concurrency considerations.
Pro tip: Mention that you would use a doubly linked list to track usage order and a hash map for O(1) access, and explicitly discuss how you handle eviction and updates. Also, proactively bring up thread-safety if the cache might be accessed concurrently, as Amazon values scalable and robust solutions.
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.
Explain that a hash map provides O(1) access to cache entries, while a doubly linked list maintains the order of usage, allowing O(1) removal and insertion.
Describe how get moves the accessed node to the front (most recently used), and put inserts or updates a node, evicting the least recently used (tail) if capacity is exceeded.
Discuss scenarios like updating an existing key, evicting when capacity is 1, and handling null keys/values if applicable.
Mention potential improvements like using a sentinel head/tail to simplify list operations, and if needed, how to make the cache thread-safe using locks or concurrent data structures.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.