Data race

A data race happens when multiple threads in a program access shared memory concurrently, and at least one thread modifies the memory, without proper synchronization mechanisms in place. Due to the timing unpredictability inherent in multithreading, these unsynchronized operations can yield inconsistent results, corrupt data, or cause runtime errors. Data races undermine thread safety and program reliability. They're common pitfalls in concurrent programming, where threads must interact safely and predictably when working with shared resources.

To fix data race conditions, ensure proper synchronization when accessing shared memory. Utilize synchronization mechanisms like mutexes (locks), semaphores, or synchronized blocks to ensure only one thread can modify shared data at a time. Implement thread-safe data structures and methods specifically designed for concurrent use. In programming languages that support concurrency (such as Java, C++, or Go), clearly define and enforce the rules of thread safety within your codebase. Additionally, use specialized tools and analyzers designed to detect data races early, and consistently apply best practices like minimizing shared state or using immutable data structures.