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

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

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As artificial intelligence, automation and machine learning rapidly transform software development, one question rises to the top for quality assurance professionals: What role will human testers play ...

Artificial intelligence and machine learning are changing how businesses operate. Enterprises are amassing a vast amount of data, which is being used within AI and ML models to automate and improve ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as well as for bug fixing and identification. Now, one of its new studies ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

Artificial intelligence, big data, and hybrid cloud computing have made a significant impact on the business industry. Joining this list is machine learning. This new advancement in business ...