Testing Firefox More Efficiently With Machine Learning
This post was co-authored with Marco Castelluccio, and was originally posted to the Mozilla Hacks Blog.
A browser is an incredibly complex piece of software. With such enormous complexity, the only way to maintain a rapid pace of development is through an extensive CI system that can give developers confidence that their changes won’t introduce bugs. Given the scale of our CI, we’re always looking for ways to reduce load while maintaining a high standard of product quality. We wondered if we could use machine learning to reach a higher degree of efficiency.Read more →