To scale quality without slowing down deployments, engineering organizations need a structured alignment between their ...

From test engineer to quality orchestrator: human oversight in AI-enabled test automation ...

What is the purpose of software testing? Although there are many ways to answer this question, the simplest answer is verification and validation. Verification and validation go beyond just test ...

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 ...

DeviQA formalizes a QA methodology for AI-assisted development, addressing new risks in AI-generated code, tests, and ...

New visual object detection capability increases test coverage, reduces risk, and provides an industry-first approach comparable to human perception SmartBear, helping teams build, test, and ship ...

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 ...

In a recent article about upgrading continuous testing for generative AI, I asked how code generation tools, copilots, and other generative AI capabilities would impact quality assurance (QA) and ...

Agentic AI is a software system that interacts with data and tools with minimal human input. It uses a goal-oriented approach, breaking tasks into steps and completing them on its own. In software ...