Automated builds are integral to the Continuous Integration (CI) software development practice. In CI, developers are encouraged to integrate early and often. However, long build times can be an issue when integrations are frequent. This research focuses on finding a balance between integrating often and keeping developers productive. We propose and analyze models that can predict the build time of a job. Such models can help developers to better manage their time and tasks. Also, project managers can explore different factors to determine the best setup for a build job that will keep the build wait time to an acceptable level. Software organizations transitioning to CI practices can use the predictive models to anticipate build times before CI is implemented. The research community can modify our predictive models to further understand the factors and relationships affecting build times.

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Keywords build time, builds, continuous integration, Machine learning
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Conference 14th IEEE/ACM International Conference on Mining Software Repositories, MSR 2017
Bisong, E. (Ekaba), Tran, E. (Eric), & Baysal, O. (2017). Built to last or built too fast? Evaluating prediction models for build times. In IEEE International Working Conference on Mining Software Repositories (pp. 487–490). doi:10.1109/MSR.2017.36