Machine Learning for Continuous Integration

Editor's Note: Andrea Frittoli and Kyra Wulffert are presenting their talk"Machine Learning for Continuous Integration" at ODSC 2019 Europe. As more applications move to a DevOps model with CI/CD pipelines, the testing required for this development model to work inevitably generates lots of data. This is also true for large open-source projects, that may see millions of tests executed on a daily basis. The data produced by such CI systems contains information about several aspects of the continuous testing system; engineers with specific domain experience usually parse such data on a daily basis in an effort to maintain the system running smoothly. After years of experience in the field, we wanted to investigate if machine learning could help us extract valuable insights from CI data with minimal human intervention.