Category: GenQE – AI Assisted Testing

Introduction As artificial intelligence (AI) continues to evolve, two dominant paradigms have emerged in AI-driven automation: AI Assistants and AI Agents. While both aim to enhance productivity and decision-making, they differ fundamentally in functionality, autonomy, and complexity. Testing these AI systems requires distinct approaches due to their unique behaviors and operational scopes. This article explores the differences between…

Introduction As digital applications become more visually complex, ensuring the accuracy and consistency of images across different platforms is critical. Traditional automation tools for image testing have limitations in handling dynamic content, visual variations, and contextual validations. AI-powered image testing offers a smarter approach by leveraging machine learning and computer vision to improve accuracy, efficiency,…

Forms are a fundamental part of user interaction in web and mobile applications—from sign-ups and contact forms to complex checkout and onboarding workflows. However, testing form filling can be time-consuming and error-prone due to varied input types, dynamic content, and changing validations. This is where AI-powered testing comes into play, automating complex scenarios and reducing…

What Are AI Hallucinations? AI hallucinations occur when an artificial intelligence model generates incorrect, misleading, or entirely fabricated information with high confidence. These errors are particularly common in large language models (LLMs), image generators, and other generative AI systems. Hallucinations can range from minor factual inaccuracies to completely nonsensical outputs, posing risks in applications like…

What is a Neural Network? A neural network is a computational model inspired by the structure and function of the human brain. It consists of interconnected layers of nodes (or “neurons”), where each node processes input data and passes the results to other nodes in the next layer. These networks are particularly effective at recognizing patterns, learning…

In the world of software testing, delivering a defect-free product is every team’s goal. However, it’s common for some defects to slip through the cracks and show up after the software has been released to production. These are called defect leakages, and they play a crucial role in measuring the effectiveness of the software testing process.…

Traditional mobile app testing has often been a complex, time-consuming process. With the proliferation of devices, operating systems, and user behaviors, ensuring consistent app performance across all scenarios has become increasingly challenging. Manual testing and script-based automation struggle to keep pace with rapid development cycles, leading to delayed releases and compromised user experiences. In response…

In the ever-evolving landscape of software development, two critical processes ensure the delivery of reliable and efficient software: testing and debugging. While they often go hand-in-hand, each plays a distinct role in the Software Development Life Cycle (SDLC). Understanding their differences, objectives, and applications can lead to smoother development and higher-quality outcomes. Testing Definition Testing…

In the fast-paced world of modern software development, delivering high-quality software quickly is more critical than ever. With users expecting flawless digital experiences and businesses pushing for faster release cycles, testing has evolved from a backend, manual process into a strategic pillar of software delivery. This evolution has given rise to automated testing frameworks, which are…

In today’s highly competitive software landscape, automated testing has become an indispensable part of the software development lifecycle. As organizations strive for faster release cycles and higher software quality, the demands placed on testing infrastructure continue to grow. This evolution brings with it a set of formidable challenges, particularly in the area of test resource expansion.…