Software testing is an essential component in ensuring the reliability and efficiency of modern software systems. In recent years, evolutionary algorithms have emerged as a robust framework for ...

When evaluating AI for testing, prioritize approaches that keep teams in control and maintain end-to-end testing connectivity.

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Prevent AI-generated tech debt with Skeleton ...

The approach toward software testing has drastically changed over the years. It has changed from manual testing to automation frameworks and now to AI-based testing. It isn’t just about increasing ...

With more than 20% of organizations deploying updates multiple times per day, according to my company's study, the complexity of test authoring has grown significantly. Test authoring is the process ...

Calsoft introduced an AI-powered approach to Test Impact Analysis that eliminates unnecessary test executions in CI/CD ...

As enterprises rethink their testing strategies, many teams are reviewing AI test automation tools that can help modernize QA ...

Quality assurance teams across modern software development face a new reality. AI enabled applications do not behave like traditional systems. Outputs shift based on context....Read More The post ...

Choosing the right test management tool directly impacts your team's ability to ship quality software fast. QA teams today juggle manual tests, automated suites, scattered documentation, and ...