The O(1) constraint is what makes this non-trivial.
Start by clarifying requirements (fixed capacity, O(1) get/put, no built-in ordered map). Then explain the classic hash map + doubly linked list design, emphasizing how it achieves O(1) operations. Finally, walk through the implementation details, edge cases, and trade-offs.
Pro tip: Mention that you would use a sentinel head and tail node to eliminate null checks and simplify edge cases, and discuss how you would handle thread safety if needed.
Confirm the exact operations (get, put), capacity behavior (evict least recently used when full), and that no built-in ordered map or cache utility can be used. Ask about thread safety and expected data types.
Select a hash map for O(1) key lookup and a doubly linked list for O(1) insertion, deletion, and reordering. Explain why a singly linked list or array would not meet the O(1) requirement.
Describe how get moves the accessed node to the front (most recently used) and returns its value. Describe how put inserts or updates a node at the front and evicts the tail (least recently used) if capacity is exceeded.
Write clean code for the Node class, the doubly linked list operations (add to front, remove node, move to front), and the LRU cache class with get and put methods. Use sentinel nodes to simplify edge cases.
State that both get and put are O(1) time and O(capacity) space. Discuss edge cases: empty cache, single item, updating existing key, eviction when full, and handling capacity 0 or 1.
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