Author: Anil Polywal

In the evolving landscape of software development, microservices architecture has emerged as a preferred approach for building scalable and maintainable applications. By decomposing applications into smaller, independent services, teams can develop, deploy, and scale components more efficiently. However, this architectural shift introduces new complexities, particularly in testing. Ensuring quality in a distributed system requires a…

In today’s fast-paced digital landscape, delivering high-quality software rapidly is paramount. Traditional test automation, while beneficial, often struggles to keep up with the dynamic nature of modern applications. Enter Artificial Intelligence (AI) — a transformative force redefining test automation by introducing adaptability, efficiency, and intelligence into the testing process. Why AI is Redefining Test Automation…

In today’s digital landscape, users access websites and applications through a myriad of browsers and devices. Ensuring consistent performance and appearance across these platforms is crucial for delivering a seamless user experience. Cross-browser testing addresses this need, verifying that applications function correctly on different browsers and devices. However, traditional cross-browser testing can be time-consuming and…

End-to-end (E2E) testing is a cornerstone of quality assurance in modern software development. Unlike unit or integration testing, E2E testing simulates real-world usage by validating an application from start to finish — ensuring that every component interacts correctly, from user interface to backend systems. While E2E testing is vital for guaranteeing a product behaves as…

In the world of software development, the mantra “test early, test often” has become second nature. Unit tests, integration tests, regression tests, acceptance tests — testing is everywhere. It’s a safety net, a quality check, and often, a non-negotiable part of deployment. But as systems grow and deadlines loom, many teams find themselves asking: “Do…

Have you ever found yourself frustrated with test automation projects? You’re not alone. In the world of software testing, it’s all about the details. The complexity comes in knowing the details of what the business intends and then designing tests to verify the behavior is as expected. While a human tester or Subject Matter Expert…

In the ever-evolving world of software testing, Model-Based Testing (MBT) has long been heralded as the next big thing — a method that promises to revolutionize the way we approach quality assurance. With claims of reducing manual effort, increasing coverage, and enabling smarter test automation, MBT is often painted as a futuristic dream come true for developers…

In today’s fast-paced development cycles, regression testing isn’t just helpful—it’s essential. Every code change, no matter how small, risks introducing bugs into existing functionality. That’s where regression testing comes in. But not all regression tests are created equal. Depending on your project size, goals, and resource availability, different types of regression testing may be more…

Artificial Intelligence (AI) has rapidly advanced, especially in the domain of natural language processing (NLP). Large Language Models (LLMs) like GPT-4 have demonstrated incredible capabilities — but also notable limitations. One major concern is AI hallucinations — confident but factually incorrect outputs. In this article, we delve into what AI hallucinations are, their types and causes, their…

As artificial intelligence continues to permeate every aspect of modern technology, the question of how to test AI systems effectively becomes increasingly important. Traditional testing methods, designed for deterministic software, fall short when applied to AI-driven applications. The unpredictability, complexity, and data-driven nature of AI create unique challenges that require innovative testing approaches. Interestingly, AI…