Classic question and I knew it, which almost made it worse because I rushed into the hashmap plus doubly linked list setup without explaining why.
Start by clarifying the requirements and constraints, then propose a hash map combined with a doubly linked list to achieve O(1) operations. Explain the design, walk through an example, and discuss edge cases and potential optimizations.
Pro tip: Mention that you would use a doubly linked list with sentinel head and tail nodes to simplify edge cases, and discuss thread-safety if the cache might be accessed concurrently.
Ask about cache capacity, expected operations, and whether thread-safety is needed. Confirm that get and put must be O(1) average time.
Propose a hash map for O(1) key lookup and a doubly linked list to maintain access order. Explain how they work together.
Describe how get moves a node to the front (most recently used) and how put inserts or updates, evicting the least recently used (tail) when at capacity.
Discuss updating existing keys, evicting when full, and using sentinel nodes to avoid null checks. Mention thread-safety if relevant.
Confirm O(1) time for both operations and O(capacity) space. Suggest possible optimizations like using a custom linked list or considering concurrency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where the interview actually got interesting.
Start by clarifying the requirements and constraints, then systematically compare locking strategies from coarse-grained to fine-grained, discussing tradeoffs in performance, complexity, and correctness. Conclude with a recommendation based on the expected workload and mention advanced techniques like lock-free or optimistic approaches if relevant.
Pro tip: Emphasize that the best strategy depends on the read/write ratio and contention level; mentioning that you'd measure and adapt rather than dogmatically choosing one approach shows engineering maturity.
Ask about expected read/write ratio, thread count, latency requirements, and whether the cache must be strictly LRU or can be approximate. This sets the stage for evaluating tradeoffs.
Explain that LRU cache operations (get, put) involve both a hash map and a doubly linked list, so concurrent access can cause race conditions, inconsistent ordering, and corruption. Highlight the need for synchronization.
Walk through coarse-grained locking (single mutex), fine-grained locking (per-bucket or per-node locks), and read-write locks. For each, discuss pros (simplicity, correctness) and cons (contention, deadlock risk, overhead).
Mention lock-free or optimistic concurrency techniques (e.g., using atomic operations, versioning, or concurrent data structures like ConcurrentHashMap with a separate eviction policy). Discuss their complexity and suitability.
Based on the clarified requirements, recommend a strategy (e.g., coarse-grained for low contention, fine-grained for high concurrency) and explain why it balances performance, correctness, and maintainability.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.