Test coverage is an important metric within test management, and as technology evolves, we‘re able to leverage new trends to predict coverage. Weka, an open source suite of machine learning software, can take your test management beyond spreadsheets to the latest AI technologies, letting you predict your test coverage earlier with greater accuracy.
With the rise of technology like AI and practices like DevOps, teams everywhere are looking for ways to speed up testing without sacrificing quality. The articles in 2017 reflect that, with the most popular topics being test automation, testing machine learning systems, next-generation exercises, and the future of software testing. If you're looking for cutting-edge testing techniques, check out this roundup.
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.