Rajneesh's Logbook

Beth M worked with AI tools for testing and concludes that tools like Cursor and Fine.ai can significantly accelerate the development of test automation frameworks. However, human angle will continue to lay the important role to ensure the accuracy and reliability of the generated code. She recommends to continue using such tools for these can offer substantial time savings, but points out the lack of intuitiveness and a learning curve for users accustomed to traditional IDEs.   Link

Latest World Quality Report (2024-25) is out and as usual, it examines current Quality Engineering trends and challenges across various industries. This year, report highlights the increasing adoption of Gen AI in QE, emphasizing its impact on test automation and data quality. Key Highlights: 1. Gen AI Integration - Organizations are actively integrating/planning Gen AI into Quality Engineering processes, with a focus on test automation, data analysis, and eventually into defect prediction. 2. Intelligent Product Validation - Validating intelligent and connected products is becoming increasingly important, requiring specialized testing approaches and skills. 3. Prioritizing Data Quality - Importance of data quality is still underestimated by many organizations, thus, posing challenges for AI implementation and overall IT efficiency. 4. Sustainability Focus - Organizations are actively working to integrate sustainability into Quality Engineering, including defining Gre...

1. Key features to consider when selecting modern testing tools, such as automation efficiency, integration with CI/CD pipelines, cross-platform support, AI-powered insights, comprehensive reporting, and ease of use   Link 2. Why do we refer to the real requirements for a product as ‘non-functional’ requirements?  Link 3. Integrating Application Performance Management (APM) tools can enhance load testing by providing deeper insights into CPU usage, memory consumption, garbage collection, thread pool utilization, latency, Apdex scores, and database query performance. This integration enables a more thorough understanding of system behavior under load, facilitating the identification and resolution of performance bottlenecks. Link