The empirical commit frequency distribution of open source projects

Abstract

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. 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 differences 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.

Paid vs. Volunteer Work in Open Source

“…Thus, the actual work is performed right up to that point in time. In other work we show that the median time between two commits of the same open source developer is about 100min [15]. When we ran the analyses with shifted working time frames, we found little difference to the numbers from the 9am-5pm time frame and decided to ignore this imprecision.…”

Dynamics of open-source software developer's commit behavior

“…Revision control software such as SVN has been deemed as an important factor to the success of OSS collaborative development. A commit is the smallest piece of increment a software developer contributes to the SVN repository that hosts an OSS project [19]. Although a few researchers recently began to focus on commit size distribution, commit classification/categorization and developer's contribution estimation, as far as we know, few of those papers conduct empirical studies on the dynamics of software developer's individual and collective commit behavior in terms of commit interval.…”

“…Compared with the traditional closed source software development process, the basic principles how and why the collective development of OSS works remain unclear [14]. Analyzing software developer's commit behavior has been considered as a feasible way to investigate this problem [4] [5] [15] [19]. Moreover, such analysis on commit behavior can provide us with relevant and empirically validated insights into how we can improve software quality and collective software development efficiency further [15].…”

Practical guidelines for change recommendation using association rule mining

“…Alali et al also investigated the total number of lines modified in the files and the total number of hunks (continuous groups of lines) that were changed [40]. Kolassa et al performed a similar study on commit frequency, reporting an average inter-commit time of about three days [41]. However, none of these studies investigate how characteristics of the change history affect the quality of the change recommendation.…”