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2020-03-10 - Article/Dans un journal avec peer-review - Anglais - 10 page(s)

Decan Alexandre , Constantinou Eleni , Mens Tom , Rocha Henrique, "GAP: Forecasting commit activity in git projects" in Journal of Systems and Software, 165, 110573

  • Edition : Elsevier (Netherlands)
  • Codes CREF : Informatique appliquée logiciel (DI2570), Informatique générale (DI1162), Analyse de systèmes informatiques (DI2572)
  • Unités de recherche UMONS : Génie Logiciel (S852)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut de Recherche sur les Systèmes Complexes (Complexys)
Texte intégral :

Abstract(s) :

(Anglais) 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 7528 git repositories and 5947 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.

Identifiants :
  • DOI : https://doi.org/10.1016/j.jss.2020.110573

Mots-clés :
  • (Anglais) Commit activity
  • (Anglais) Developer abandonment
  • (Anglais) Prediction model
  • (Anglais) Distributed software development