Articles by Andrew Halberstadt
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Testing Firefox more efficiently with machine learning
A browser is an enormously complex piece of software, and it's always in development. About a year ago, we asked ourselves: how could we do better? Our CI relied heavily on human intervention. What if we could instead correlate patches to tests using historical regression data? Could we use a machine learning algorithm to figure out the optimal set of tests to run? We hypothesized that we could run fewer tests to save money, get results faster, and reduce the cognitive burden on developers.