Automation has become an integral part of QA processes, as it enables companies to cover more software efficiently in less time.

How do you transition from traditional quality engineering (QE) to an AI-driven testing strategy while ensuring long-term sustainability?

Challenges of AI in Software Testing Insufficient Data Quality: Data quality and availability are two major barriers to using AI for software testing.

Despite its value, test automation is not a silver bullet for dynamic and complex systems. InfoQ interviewed Victor Ionascu about automating testing and using AI in software testing.

A new study from Kobiton found nearly 100% of software testers use automation, and managers prefer new hires with automation experience.

Troubleshoot Your Software With These Common Testing Challenges and Possible Solutions. Plus, Find Helpful Resources and Examples. Visit To Learn More.

OpenAI has agreed to buy product testing startup Statsig for $1.1 billion in an all-stock deal, the company said, marking one of the largest acquisitions in the ChatGPT maker’s ...

Parasoft, a global leader in AI-automated software testing solutions, earned a top spot as a Leader and Fast Mover in the latest GigaOm Radar Report on API Functional Automated Testing. Building ...

Collaboration combines LambdaTest’s AI-native test automation with Lab49’s advanced domain expertise in capital markets to accelerate software delivery for financial institutions.

The convergence of AI and flexible, software-defined instrumentation is revolutionizing the test and measurement industry, offering efficient ways to analyze data and optimize processes.