(TNS) — A pair of Pittsburgh companies have teamed up to design software they hope will make it safer to test self-driving cars in the city and around the world. Simulation software developed by Edge ...

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 ...

The complexity of software architecture and diverse user interactions presents challenges to conventional testing approaches. Traditional test automation and quality assurance engineering represented ...

TestSprite Inc., a platform that offers end-to-end software testing using fully autonomous artificial intelligence, today announced early access to its platform today. The company’s platform provides ...

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 ...

Times are changing fast. Take the automotive industry for example. Software has evolved far beyond infotainment, now controlling everything in the car, including braking and steering for the driver.

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 ...

Are you grappling with managing your test data in an automation framework? Here’s a fact: effective Test Data Management (TDM) can significantly improve your software testing process. This ...

Most everyone would agree how important FPGA prototyping is to test and validate an IP, sub-system, or a complete SoC design. Before the design is taped-out it can be validated at speeds near real ...