Hi,
Data races occur when multiple threads access shared data at the same time, with at least one thread performing a write operation. This can lead to unpredictable behavior. While atomic operations are indivisible and prevent interference during their execution, they don't synchronize access between different threads, so data races can still occur without proper synchronization.
Critical sections are essential for ensuring mutual exclusion, allowing only one thread to execute a block of code at a time. This prevents data races by coordinating access to shared resources, which is crucial when atomic operations alone aren't enough to ensure synchronization.
Polyspace's "Data Race including atomic operations" setting is useful for identifying potential data races involving atomic operations. By enabling this option, you can detect areas where additional synchronization is necessary, highlighting where critical sections should be applied to prevent race conditions.
Following Polyspace's recommendations to use critical sections is advisable, even when operations are atomic. Critical sections protect the entire sequence of operations, preventing race conditions and maintaining data integrity, ensuring that concurrent processes do not interfere with each other.
In your example, `var++` is atomic, but tasks `task1` and `task2` can still cause data races if they run concurrently. `task3` uses critical sections around `increment()`, ensuring safe execution without interference. This practice helps avoid concurrency bugs and ensures robust, error-free programming.
Hope this helps!
