Learn about our reimagined version of Kwo Ding's original mobile test automation pyramid for modern DevOps practices.

My first attempt to understand accessibility and how to test it started back in 2016. I was working for a company where accessibility was already an important part of the process. I was asked to perform accessibility testing on the product to determine whether we could claim to be accessible. Since it was a new subject for me, I was quite confused. Where should I start? Should I be certified to provide a proper assessment? Do I need to request assessments from third-party companies?

In the past, testing for non-functional requirements (NFR) was often neglected, done to the extent possible at the end of the life cycle. For modern development teams, that is no longer an option - to deliver high-quality applications, they have to implement a comprehensive testing strategy with proper allocation of resources to both functional and non-functional components.

The software testing landscape, while crucial for ensuring application quality, has grappled with limitations in traditional methods for decades. This article explores how Artificial Intelligence (AI) is emerging as a game-changer, addressing these challenges and augmenting the capabilities of testers. By combining advanced machine learning, deep learning, natural language processing, and other techniques, AI offers a powerful toolkit to propel software testing into a new era.

In today’s dynamic business world, seamless transitions between application life cycle management systems (ALM) are crucial for organizations striving to optimize workflows and enhance productivity. JIRA, a robust and versatile project management tool, often becomes the best choice for teams seeking efficient task management, issue tracking, and collaboration capabilities.