A Model of the Commit Size Distribution of Open Source - Kolassa, Carsten; Riehle, Dirk; Salim, Michel Alexandre (Proceedings of the 39th International Conference on Current Trends in Theory and Practice of Computer Science (LNCS 7741), 2013)
A fundamental unit of work in programming is the code contribution ("commit") that a developer makes to the code base of the project in work. We use statistical methods to derive a model of the probabilistic distribution of commit sizes in open source projects and we show that the model is applicable to different project sizes. We use both graphical as well as statistical methods to validate the goodness of fit of our model. By measuring and modeling a fundamental dimension of programming we help improve software development tools and our understanding of software development. © 2013 Springer-Verlag Berlin Heidelberg.
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.popsos.amodel_4
Keywords: Open Collaboration; Open Source; Research

Developer Belief vs. Reality: The Case of the Commit Size Distribution - Riehle, Dirk; Kolassa, Carsten; Salim, Michel Alexandre (Proceedings of Software Engineering 2012, 2012)
UnivIS-Import:2015-04-16:Pub.2012.tech.IMMD.popsos.develo
Keywords: Commit size; commit size distribution

The Empirical Commit Frequency Distribution of Open Source Projects - Kolassa, Carsten; Riehle, Dirk; Salim, Michel Alexandre (Proceedings of the 9th International Symposium on Open Collaboration, 2013)
A fundamental unit of work in programming is the code contribution (") that a developer makes to the code base of the project in work. An author's commit frequency describes how often that author commits. Knowing the distribution of all commit frequencies is a fundamental part of understanding software development processes. This paper presents a detailed quantitative analysis of commit frequencies in open-source software development. The analysis is based on a large sample of open source projects, and presents the overall distribution of commit frequencies. We analyze the data to show the dierences between authors and projects by project size; we also includes a comparison of successful and non successful projects and we derive an activity indicator from these analyses. By measuring a fundamental dimension of programming we help improve software development tools and our understanding of software development. We also validate some fundamental assumptions about software development. Copyright 2010 ACM.
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.popsos.theemp
Keywords: Open Source; Open Source Projects