Image Credits: Katalon In Software Testing, a solid test strategy is more than just a document. It’s a blueprint for quality and it defines what needs to be tested, how, when, by who, and which tools. In traditional crafting a test strategy involved manual effort, relying heavily on experience, risky guesswork and time consuming planning […]
Software testing has been a key part of high quality product delivery, but most traditional methods require a significant manual work and technical knowledge. Gen AI Testing is transforming this, by enabling testers to interact with AI via basic prompts without needing deep automation expertise. Instead of building complex test scripts, testers can ask AI […]
As technology evolves rapidly, delivering flawless software has become a top priority. QA teams often deal with repetitive tasks like running tests, reporting bugs, and checking for UI issues across different browsers. AI-powered personal bot browser extensions can change the way QA teams work by automating these tasks, reducing human effort, and making testing more […]
AI- powered test case generation is transforming software testing by automating one of the most time consuming and critical tasks in quality assurance. Traditional test case creation relies heavily on manual effort, requiring testers to analyze requirements, design test scenarios, and ensure full coverage. This approach often results in inefficiencies, missed edge cases, and increased […]
Agile Methodologies revolutionized the way software is developed, moving away from rigid, waterfall-style approaches to iterative, incremental delivery. However, when Agile frameworks like SAFe (Scaled Agile Frameworks) and LeSS (Large-Scale Scrum) come into play, the complexity of quality assurance escalates significantly. Testing in scaled Agile Environments demands not only technical adaptability but also a cultural […]
In software testing, tracking defect density before a release is one of the most important ways to ensure the product meets quality standards. Defect density measures the number defects found in a module or system compared to its size giving QA teams a clear picture of the software’s quality. This metric helps testers pinpoint areas […]
AI empowers software testers by predicting potential future defects in software testing. It does this by analyzing historical data, identifying patterns, and applying machine learning algorithms. This predictive capability significantly enhances the efficiency and effectiveness of the testing process, giving testers a greater sense of confidence in their work. Here’s how AI can be leveraged […]