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 ...

Identify sources of unnecessary cognitive load and apply strategies to focus on meaningful analysis and exploration.

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

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 ...

Product demos get all the attention, but software development more often involves things like debugging, quality assurance, and testing. It’s the dull but critical work that keeps software running the ...