I knew this was an LRU cache question the second they said it, which honestly made me a little overconfident.
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, explaining how the hash map provides fast access to nodes and the linked list maintains access order. Finally, implement the core methods and analyze complexity.
Pro tip: Mention that you would use a sentinel head and tail to simplify edge cases in the linked list, and discuss thread-safety considerations if the cache might be accessed concurrently.
Ask about expected cache size, concurrency needs, and whether eviction policy is strictly LRU. Confirm that average O(1) is required for both get and put.
Propose a hash map for O(1) key lookup and a doubly linked list to track access order. Explain that the hash map stores key to node references, and the list maintains most-recently used at one end.
Describe how get moves the accessed node to the front (most recent), and put inserts or updates, moving the node to the front. On capacity overflow, remove the tail node (least recent) and delete its key from the map.
State that both get and put run in O(1) average time due to hash map and linked list operations. Space complexity is O(capacity) for storing up to capacity items.
Write clean code for the LRU cache class, including helper methods for adding to front and removing nodes. Use sentinel nodes to avoid null checks.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.