← Verkada Inc. Interview Insights
Classic problem, so I'd seen it before, but the O(1) constraint is where people trip up if they haven't thought through the data structure combo.
Start by clarifying requirements and edge cases, then explain that a hash map combined with a doubly linked list achieves O(1) get and put. Walk through the design, implement the class with careful pointer updates, and analyze time/space complexity.
Pro tip: Use dummy head and tail nodes to eliminate null checks and simplify edge cases in the doubly linked list. Also, mention thread-safety considerations if the cache might be accessed concurrently.
Ask about capacity bounds, key/value types, expected concurrency, and whether get should update recency. Confirm that both operations must be O(1) average time.
Explain that a hash map provides O(1) access to nodes, and a doubly linked list maintains recency order with O(1) insertion and deletion. Together they meet the complexity requirement.
Define a Node class with key, value, prev, and next pointers. Use dummy head and tail nodes. For get, move the accessed node to the front; for put, insert or update and move to front, then evict the tail if over capacity.
Write clean code with helper methods for addToFront and removeNode. Handle edge cases like updating an existing key and evicting when capacity is reached.
State that both operations are O(1) average time and O(capacity) space. Walk through a few test cases to verify correctness, including eviction and updating existing keys.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.