Start by identifying the shared mutable state and the specific race conditions (e.g., check-then-act, read-modify-write) that cause the cache to break. Then propose a fix using appropriate synchronization primitives, and analyze the trade-offs of different locking strategies (coarse-grained, fine-grained, lock-free) in terms of scalability and contention. Finally, discuss how the fix scales under high concurrency and potential optimizations like sharding or read-write locks.
Pro tip: Demonstrate awareness of real-world constraints: mention that while a global lock is simplest, it serializes all operations and kills scalability; instead, consider lock striping or read-write locks to balance correctness and performance. Also, note that even with locks, cache stampede (thundering herd) can occur, and suggest techniques like request coalescing or probabilistic early expiration.
Analyze the cache operations (get, put, evict) to find race conditions such as check-then-act (e.g., checking if a key exists before inserting), non-atomic updates to LRU order, and unsynchronized access to shared data structures.
Choose a synchronization strategy (e.g., mutex, read-write lock, atomic operations) to make critical sections atomic. Ensure that the fix addresses all identified races without introducing deadlocks or excessive contention.
Compare coarse-grained locking (single lock), fine-grained locking (per-bucket or per-entry), and lock-free approaches (e.g., using atomic CAS). Discuss trade-offs in terms of complexity, scalability, and contention.
Explain how each strategy performs under high concurrency: coarse-grained locks serialize access and limit throughput; fine-grained locks reduce contention but add overhead; lock-free can scale well but is complex. Mention metrics like throughput, latency, and contention.
Propose enhancements like lock striping (e.g., sharding by key hash), read-write locks for read-heavy workloads, and handling cache stampede via request coalescing. Also consider memory consistency and false sharing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.