Six Lessons For Building A Quality Software Testing Culture

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 ...
InfoQ

Leapwork Research Shows Why AI in Testing Still Depends on Reliability, Not Just Innovation

Leapwork recently released new research showing that while confidence in AI-driven software testing is growing rapidly, accuracy, stability, and ongoing manual effort remain decisive factors in how ...
Nature

Software Testing and Test Data Generation Using Evolutionary Algorithms

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 ...
Ministry of Testing

Managing cognitive load for better software testing

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

Leveraging Generative AI For Enhanced Efficiency, Accuracy And Scalability In Chaos And Mutation Testing

Deepak Gupta, VP Engineering at Cars24. Specializes in FinTech, AI/ML, E-comm, digital transformation, business strategy and revenue growth. Software systems are getting more complex, like a giant ...
Kauppalehti

Study Finds AI Is a Priority for Software Testing Teams, but Confidence Hinges on Accuracy and Reliability

Testing places unique demands on AI. Errors carry real business risk, and fragile tests or slow updates can quickly erode trust in results. As a result, while momentum around AI in testing is strong, ...