Strong quality cultures analyze this historical execution data to identify flaky tests, unstable code sections and deployment patterns that correlate with incidents. Machine learning algorithms can ...

Test automation has always been about speed. We measured success by how many tests we ran per minute and celebrated shorter regression cycles. However, we now stand at the edge of the next evolution.

AI can speed up testing, but if you trust it too much, you might ship bugs faster than ever — with no one clearly accountable.

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 ...

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 ...

Palisade Research said AI developers may inadvertently reward models more for circumventing obstacles than for perfectly following instructions. Several artificial intelligence models ignored and ...

Check if a file is really a file, whether a string contains anything, and whether you can run a program with these vital patterns.