FP Remover can understand code and identify false positives like a developer: it recognizes potential secrets that aren't actually secrets based on code-specific syntax or context understanding.

Today’s fast-paced online world is underlined by systems that allow it to move that fast. Whether it’s the latest advancements to transport systems, faster internet connections, or more real-time ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

False positives have long been one of the biggest challenges in trade surveillance, overwhelming compliance teams with alerts that don’t reflect genuine threats, but still need to be investigated as ...

A new machine learning breakthrough outperforms traditional methods by reducing false positives and minimizing cases needing further inspection, crucial for sectors like Medicare and credit card fraud ...

David Schiffer is the CEO of RevBits and formerly of Safe Banking Systems (SBS). RevBits develops cybersecurity software for organizations. Let’s be honest—alert fatigue is real, and it’s relentless.

Community driven content discussing all aspects of software development from DevOps to design patterns. The key difference between a false positive and a false negative is that a false positive ...