The problem itself isn't hard to understand but I fumbled for a minute on the data structure choice.
Start by clarifying the requirements and constraints, then propose a hash map combined with a doubly linked list to achieve O(1) operations. Walk through the design, implement the core methods, and analyze time and space complexity.
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.
Ask about cache size, eviction policy, concurrency needs, and expected operation frequency to ensure alignment with the interviewer.
Explain that a hash map provides O(1) access to nodes, and a doubly linked list maintains recency order for O(1) updates and evictions.
Describe how get moves a node to the front (most recently used) and put inserts or updates, evicting the tail (least recently used) when capacity is exceeded.
Write clean code for the LRU cache class, using sentinel nodes to avoid null checks, and test with edge cases like capacity 1 and repeated updates.
State that both get and put run in O(1) time and O(capacity) space, and discuss potential trade-offs or extensions.
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