In some ways, data and its quality can seem strange to people used to assessing the quality of software. There’s often no observable behaviour to check and little in the way of structure to help you ...

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, ...

AI-powered penetration testing is an advanced approach to security testing that uses artificial intelligence, machine learning, and autonomous agents to simulate real-world cyberattacks, identify ...

Researchers led by Assoc. Prof. Dr. Savaş Taşoğlu from the Department of Mechanical Engineering at Koç University have ...

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

Opinion: A patent case involving inventor Guillaume Desjardins has evolved into a cornerstone of modern patent eligibility ...

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

In essence, PAI is being used for data center optimization to support the demands of digital AI (DAI) applications like ...

Virtual tools that can help manufacturers simulate processes on the shop floor are only a valuable if the information being ...

AI has fundamentally altered how teams think about mobile software, moving the focus from feature accumulation to long-term intelligence.

"AI is fundamentally changing how software is built, but not in the way many headlines suggest," Joisa explains. "Instead of replacing engineers, it’s reshaping the workflow by automating repetitive ...