In this article, let’s explore how machine learning is revolutionizing software testing and breaking new ground for QA teams and enterprises alike, as well as how to successfully implement it.

Whereas smoke testing does a quick general check, the full QA process methodically ensures every aspect of your SaaS product works.

A couple weeks ago I ran this post showing how one Hong Kong developer, Animoca, tests its Android games. The company, which has had more than 70 million downloads, tests every one of their apps ...

HiQE is our vision for a new model where human oversight coexists with autonomous AI agents. Human oversight becomes more strategic, while AI agents take on the repetitive, data-heavy work, such as ...

What QA can do QA can best implement test automation scripts and tools in cases where application processes are repetitive and predictable.

IT can still test without access to underlying source code. Use agile acceptance testing, address the business logic, and adopt test platforms with machine learning.

Learn why – and how – you can easily integrate SEO testing into your own QA process to prevent SEO problems from ever going live.

The first wave of generative AI-augmented software testing and automation tools has arrived. Here’s how QA and devops teams will measure their impact.

QA Wolf has exited stealth, securing $20 million for its platform that automates and ostensibly streamlines the process of testing web-accessible software apps.