Quality assurance teams across modern software development face a new reality. AI enabled applications do not behave like traditional systems. Outputs shift based on context....Read More The post ...

In the next few years, software testing — a critical but traditionally manual phase of development — is poised for a ...

Strategic AI-driven QE can be the key to accelerating delivery, strengthening reliability and maintaining market velocity.

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Key opportunities in the Global App Test Automation Market include leveraging AI and machine learning to enhance testing ...

Imagine a customer placing an order online. They browse a website, add items to a cart, and complete the checkout process. It ...

What happens when Ramp-testing a vehicle happens around the assembly line, earlier-faster-deeper-and-smarter than before? And ...

Generative AI is rapidly changing how software is designed, built, and maintained. As these systems become more capable, they are also reshaping how quality assurance teams approach testing, ...

Automation is necessary, but it can bring an "automation paradox": Speed without insight may simply propagate errors faster ...

If AI writes code like a teenager, then testers need to be the adults in the room. That doesn’t mean standing at the end of ...

Imagine launching a website that works perfectly in testing, only to watch it struggle or crash the moment real users arrive.

To prevent platform failures, financial services firms must shift testing focus from the vendor core to their customisaptions ...