The part that trips people up isn't the cache logic itself, it's the O(1) eviction.
Start by clarifying the requirements: O(1) get and put, capacity limit, and eviction policy (least recently used). Then propose a combination of a hash map for O(1) access and a doubly linked list for O(1) updates to recency order. Walk through the design, implement the core operations, and analyze time and space complexity.
Pro tip: Mention edge cases like updating an existing key, evicting when at capacity, and handling capacity 0 or 1. Also, discuss thread-safety if the cache will be used in a concurrent environment, as Oracle often values robustness in production systems.
Confirm the cache capacity, eviction policy (LRU), and whether operations need to be thread-safe. Ask about expected usage patterns to tailor the design.
Select a hash map for O(1) key lookup and a doubly linked list to maintain recency order. Explain how the map stores nodes of the list for direct access.
Define get: if key exists, move node to front and return value; else return -1. Define put: if key exists, update value and move to front; else add new node to front and evict least recently used (tail) if over capacity.
Write clean code for the LRU cache class, handling edge cases like capacity 0 or 1. Test with scenarios including repeated gets, puts, and evictions.
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 the map and list.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.