You'd think this is easy until you're staring at a blank editor.
Start by clarifying the requirements: O(1) for both get and put, and the eviction policy when capacity is exceeded. Then propose a combination of a hash map for O(1) access and a doubly linked list for O(1) updates to maintain recency order. Walk through the implementation details, including edge cases like updating existing keys and handling capacity limits.
Pro tip: Mention that you would use a doubly linked list with sentinel head and tail nodes to simplify edge cases and avoid null checks. Also, discuss how you would handle thread safety if needed, showing awareness of concurrency in real-world systems.
Confirm that get and put must be O(1), and that the cache evicts the least recently used item when full. Ask about constraints like capacity size, thread safety, and whether null values are allowed.
Explain that a hash map provides O(1) access to cache nodes, and a doubly linked list maintains the order of usage. The hash map maps keys to nodes in the linked list.
For get: if key exists, move the node to the front (most recently used) and return its value; else return -1. For put: if key exists, update value and move to front; else create a new node, add to front, and if capacity exceeded, remove the node at the tail (least recently used) and delete its key from the map.
Consider capacity 0 or 1, updating an existing key, and ensuring the linked list and hash map stay in sync. Use sentinel nodes to simplify adding/removing nodes.
Confirm that both get and put are O(1) time because hash map operations are O(1) and linked list insertions/deletions are O(1) with direct node references. Space complexity is O(capacity).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.