Most machine learning systems are based on neural networks, or sets of layered algorithms whose variables can be adjusted via a learning process. These types of systems don’t produce an exact result; in fact, sometimes they can produce an obviously incorrect result. So, how do you test them? Peter Varhol tells you what you should consider when evaluating machine learning systems.

As 2016 draws to a close, we at TechWell took a look back at the topics that most interested our StickyMinds readers. We hope you enjoy this curated list of top-ranking articles and interviews covering everything in the software testing industry from Selenium and test automation to API testing, kanban, and the future of the software testing profession.

The key for test data privacy is fulfilling testers’ needs for efficiency, speed, and the most accurate representations of data and application behavior in the production environment, while ensuring privacy and protecting testers from unintentional hazards. Here are some tips for getting started on a test data privacy project to comply with the EU’s coming General Data Protection Regulation.

Even if you're currently only using manual testing, it's still important to know about what's going on in the world of automation. Whatever your role is, your day-to-day job will probably be enhanced by using at least some of the approaches in this article. Here, learn what some common terms mean and some examples of how they might be used in a software development shop.