Hello everyone,
I’m thrilled to announce that I’ll be participating as a mentor for the openSUSE Project in this year’s Google Summer of Code 2025! It’s always a privilege to work with talented contributors and help guide innovative projects within our open-source community.
This year, I’ll be mentoring an exciting large-scale project titled: “AI-Driven Test Selection in Uyuni’s Pull Request Acceptance Tests”.
I’m also very happy to introduce our contributor, Ahmed Khaled (Akayiz), who will be leading the charge on this project.
To ensure code quality in Uyuni, we run an extensive suite of acceptance tests for every new pull request. While this is crucial for preventing breakages from reaching our master branch, the process has its challenges. Currently, these tests execute most of the suite, leading to an average runtime of about one hour. This long wait delays valuable feedback for our developers and also increases our infrastructure costs.
Our goal with this GSoC project is to tackle this challenge head-on by developing a machine learning model.
Inspired by Facebook’s “Predictive Test Selection” paper, the model will be trained on historical data, including past pull requests, test results, and code coverage data. Its purpose is to predict the smallest possible subset of tests that are most likely to fail for any new pull request.
By running only this highly relevant, smaller set of tests, we aim to:
The project will involve a fantastic mix of technologies, including Python for machine learning, Ruby and Cucumber from our test suite, and GitHub Actions and the GitHub API for integration.
The project is now active, and we’re looking forward to the journey ahead, with the midterm evaluation coming up in August and the final submission in late October. I’m incredibly excited to see what Ahmed will build and the positive impact it will have on Uyuni’s developer productivity.
Stay tuned for more updates as we progress!