False positives are our enemies, but may still be your friends

A false positive is a result of static analysis that indicates an issue with the code, but it is not actually a real problem. The type and origin of the false positive vary, including semantic false positives related to Rice's theorem, specification false positives from rules like Code Smell, and bugs causing false positives due to implementation issues. Avoiding false positives is important as excessive reporting can lead to decreased tool effectiveness over time. However, it is challenging to eliminate them completely due to the limitations of static analysis techniques. To help minimize false positives, users can report them to improve the product, take a closer look at the code as a hint that there might be an issue, and engage with the community for discussion and feedback.

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