GAP: forecasting commit activity in git projects

Alexandre Decan (Corresponding author), Eleni Constantinou, Tom Mens, Henrique Rocha

    Research output: Contribution to journalArticleAcademicpeer-review

    9 Citations (Scopus)


    Abandonment of active developers poses a significant risk for many open source software projects. This risk can be reduced by forecasting the future activity of contributors involved in such projects. Focusing on the commit activity of individuals involved in git repositories, this paper proposes a practicable probabilistic forecasting model based on the statistical technique of survival analysis. The model is empirically validated on a wide variety of projects accounting for 7,528 git repositories and 5,947 active contributors. We found that a model based on the last 20 observed days of commit activity per contributor provides the best concordance. We also found that the predictions provided by the model are generally close to actual observations, with slight underestimations for low probability predictions and slight overestimations for higher probability predictions. This model is implemented as part of an open source tool, called GAP, that predicts future commit activity.
    Original languageEnglish
    Article number110573
    Number of pages10
    JournalJournal of Systems and Software
    Publication statusPublished - 1 Jul 2020


    • Git
    • Commit activity
    • Developer abandonment
    • Distributed software development
    • Prediction model


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