Category: GenQE – AI Assisted Testing

In 2025, the landscape of DevOps is undergoing a significant transformation, with testing emerging as a central pillar in the software development lifecycle. The integration of artificial intelligence (AI), the balance between manual and automated testing, and the emphasis on security and compliance are reshaping how organizations approach software quality. Platforms like GenQE.ai are at…

In the ever-evolving world of software development, test coverage remains one of the most debated and misunderstood quality metrics. Organizations strive to build reliable, scalable software, but achieving “good” test coverage isn’t as simple as hitting a percentage threshold. Instead, it requires a strategic blend of testing practices, from unit tests to end-to-end (E2E) validations,…

Why Cloud Testing Needs a Security-First Mindset and How to Achieve It As more software development teams adopt cloud-based test automation to boost scalability, speed, and agility, one crucial element often lags behind: security. While cloud testing offers tremendous benefits — like anytime/anywhere access, seamless parallel testing, and elastic environments — it also introduces new…

How Investing in Quality Saves Time, Builds Trust, and Drives Growth In today’s mobile-first world, your app isn’t just a product — it’s your brand, your storefront, and your customer relationship manager, all rolled into one. As expectations for performance, security, and usability soar, the margin for error has never been thinner. Users expect apps…

The GenQE.ai Experience 2025 wrapped up with a bold vision and sharp focus: AI isn’t just augmenting software testing — it’s transforming it. This year’s event brought together leaders in QA, engineering, and DevOps to explore how GenQE.ai platform is reshaping testing strategies in organizations of every size and sector. If you missed the experience, here’s…

Rethinking Unit Testing with GenQE.ai Unit testing is often touted as the cornerstone of high-quality software development. In theory, it should be the easiest and most effective way to catch bugs early, improve code reliability, and support continuous delivery. But in practice, many developers dread it. Why does something designed to help end up being avoided, postponed, or…

1. Test Coverage (Workflow-Based) Traditional code coverage doesn’t capture the full value of E2E testing. Instead, focus on workflow or scenario coverage: Why it matters: You can have 90% code coverage and still miss the most common user flows. Prioritize real use cases over line-by-line coverage. 2. Pass/Fail Rate Track the ratio of successful vs. failed…

In the modern healthcare landscape, medical devices are increasingly reliant on sophisticated software to perform critical functions. From diagnostic imaging systems to implantable devices, software ensures precision, efficiency, and enhanced patient care. However, this reliance also introduces potential risks. Ensuring that medical device software operates safely and effectively is paramount, making risk analysis an essential…

Modern software development has increasingly adopted microservices architecture, breaking down applications into smaller, independent services that communicate through APIs. While this approach offers benefits like scalability and faster deployment cycles, it introduces new testing complexities that require specialized strategies. Effective microservices testing ensures reliability across distributed systems while maintaining development velocity. The Complexity of Microservices…

Microservices architecture has revolutionized software development by promoting modularity, scalability, and agility. However, testing microservices presents unique challenges due to their distributed nature and inter-service communications. This article explores these challenges and outlines strategies to effectively test microservices, ensuring robust and reliable applications. Microservices Introduce New Challenges Transitioning from monolithic to microservices architecture introduces complexities…