What are data races and how can we prevent them?

What are data races and how can we prevent them?

Data races occur when two or more threads access shared data simultaneously, and at least one thread modifies it. To prevent them, you can use synchronization techniques like mutexes, semaphores, or locks.

Can you explain how mutexes work?

Sure! A mutex, or mutual exclusion, is a synchronization primitive that allows only one thread to access a resource at a time. When a thread locks a mutex, other threads trying to lock it will be blocked until the mutex is unlocked.

What are some common pitfalls when using mutexes?

Common pitfalls include deadlocks, where two or more threads are waiting on each other to release locks, and priority inversion, where a lower-priority thread holds a lock needed by a higher-priority thread.

Are there alternatives to mutexes for synchronization?

Yes, alternatives include read-write locks, condition variables, and atomic operations, which can be more efficient depending on the use case.