Author: Anil Polywal

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…

In the software development lifecycle, testing plays a vital role in ensuring that an application is functional, reliable, and free from defects. Among the various types of testing, unit testing and integration testing are two of the most fundamental and commonly used. While both serve distinct purposes, they are often misunderstood or used interchangeably. This…

Unit testing is an important component of ensuring code quality, but as projects grow in complexity and development cycles shorten, traditional testing methods are struggling to keep pace. Unit testing is in need of a dramatic transformation, and it’s clear that this transformation will be driven by advancements in artificial intelligence (AI). By automating many…

As a software developer, testing your software is essential to ensure it’s free from defects that could cause security breaches, data loss, or system failures. Traditionally, this has involved manually creating test cases—a time-consuming and often inefficient process, especially for larger systems. Automated test case creation offers a solution by speeding up the process and…

In the ever-evolving world of software development, achieving a balance between speed and quality is crucial. While test automation has revolutionized how we approach repetitive and large-scale testing tasks, manual testing still holds its ground where human insight is irreplaceable. This has led to the rise of hybrid testing — a testing methodology that strategically combines manual and…