SE Radio 572: Gregory Kapfhammer on Flaky Tests
Software Engineering Radio - the podcast for professional software developers
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How to Use a Supervised Machine Learning Technique to Predict Flaky Test Cases
When it comes to machine learning, the first thing that we should talk about is whether we're using a supervised or unsupervised or reinforcement machine learning technique. My specific examples and the tools that we've built and released on GitHub all use what are called supervised machine learning algorithms. The idea there is that you're going to collect information about the program and the test suite. And then you's going to connect that with information about whether the test case is or is not flaky.
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