Systems | Development | Analytics | API | Testing

Software quality has evolved over time. Initially, the focus was on finding and resolving defects prior to a product launch. As technology advanced, the emphasis shifted towards maintaining quality across the whole development process, particularly with the rise of Agile and DevOps methodologies. Quality is now approached proactively, encompassing all phases of the product lifecycle - from planning to deployment.

AI is becoming a part of our everyday lives, and in the software testing industry, it is starting to show its impact as well. Traditional testing methods can often happen at a later stage of the development life cycle, which may present challenges for meeting the demands of modern software delivery. This is where shift-left testing comes to shine. This testing methodology has become one of the most used strategies for delivering high-quality software without missing bug findings along the way.

Traditional testing approaches can struggle to keep up with the dynamic nature of modern development cycles. While effective in certain contexts, these methods may miss some defects, which can lead to costly fixes, customer dissatisfaction, and damage to the product's reputation. The problem lies in the limitations of scripted testing, which might lack the flexibility required to identify novel defects.