Testing places unique demands on AI. Errors carry real business risk, and fragile tests or slow updates can quickly erode trust in results. As a result, while momentum around AI in testing is strong, ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Calsoft introduced an AI-powered approach to Test Impact Analysis that eliminates unnecessary test executions in CI/CD ...

The cost of not upping software quality assurance will be evident not only in the marketplace but on a company’s bottom line and in the lives of people.

AI-generated test cases have significantly accelerated software testing workflows, but refining outputs often requires manual edits or restarting the generation process. TestMu AI’s latest release ...

From generating test cases and transforming test data to accelerating planning and improving developer communication, AI is having a profound impact on software testing. The integration of artificial ...

When LambdaTest was founded, the problem it set out to solve was far more contained but with the rise of AI-generated code ...

The software testing landscape is undergoing a seismic shift. For years, continuous automation testing (CAT) platforms have been the gold standard for reducing manual testing and ensuring ...

From autonomous vulnerability remediation to real-time scrutiny of AI-generated code, AI is impacting security at every stage of the software development process. At Black Hat USA 2025 and DEF CON 33, ...

Offensive security has spent years caught between two extremes: deeply manual penetration tests that do not scale, and automated scanners that scale easily but surface volumes of low-confidence ...