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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

Transition from reactive quality assurance to proactive quality engineering by embedding shared responsibility throughout the ...

Identify sources of unnecessary cognitive load and apply strategies to focus on meaningful analysis and exploration.

The purpose of tracking and monitoring software engineering metrics is to assess the current product or process performance, enhance it, and anticipate the quality after the software development ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

The results are in: Quality assurance (QA) testing quality is going up while costs are coming down. According to the latest edition of the World Quality Report, the share of IT budget allocated to QA ...

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