race-conditions

Prevent race conditions in concurrent database transactions by replacing read-then-write patterns with atomic updates and enforcing transactional boundaries. This guarantees consistency when multiple actors access shared mutable state simultaneously.

Optimistic locking uses versioning to detect conflicts at commit time, while pessimistic locking restricts access immediately. Both locking strategies coordinate concurrent updates to prevent race conditions in multi-threaded and distributed environments.

Implement idempotency checks for duplicate API requests by assigning unique idempotency keys to each operation. This prevents duplicate or conflicting work when the same request is received multiple times in asynchronous systems.

You need distributed locks for multi-resource operations when complex updates span multiple microservices or databases. They coordinate access across distributed environments where local transaction boundaries are insufficient to prevent race conditions.

Test for race conditions and timing bugs by designing tests that simulate concurrent executions. Identify shared mutable state accessed by multiple actors and verify that atomic operations and synchronization mechanisms maintain correctness under concurrency.

Fix intermittent bugs caused by concurrent access by identifying shared mutable state and replacing read-then-write patterns with atomic updates. Introduce versioning, optimistic locking, and idempotency checks to ensure correctness under concurrency.