This is how we set up Bitrise's internal platform’s GCP environment for teams to host their infrastructure resources.

By incorporating AI and machine learning into mobile testing tools, teams can become more efficient in test automation. In this article, we'll look at how the adoption of AI and machine learning will improve these tools and what the future of testing might look like.

Feature engineering is a crucial part of any ML workflow. At Continual, we believe that it is actually the most impactful part of the ML process and the one that should have the most human intervention applied to it. However, in ML literature, the term is often overloaded among several different topics, and we wanted to provide a bit of guidance for users of Continual in navigating this concept.

Even with the increasing adoption of Agile and DevOps, many organizations still consider testers the gatekeepers of quality and are solely held responsible for the quality and approving releases. Such organizations blame testers for a missed production bug. No matter how much you test, a few bugs can still slip through the testing phase & reach production. Every software tester would have come across a situation of a missed bug. For many testers, it’s a terrifying nightmare.

In the latest instalment of our interviews speaking to leaders throughout the world of tech, we’ve welcomed CEO of AIClub, Nisha Talagala to share her thoughts. Nisha has significant experience in introducing technologies like Artificial Intelligence to new learners.

Writing UI tests is always challenging. Many developers leave views without testing or devoting much effort to the development of tests. This article is a quick guide to help you automate your iOS Snapshot testing process!