Many open source projects have long become commercial. This paper shows just how much of open source software development is paid work and how much has remained volunteer work. Using a conservative approach, we find that about 50% of all open source software development has been paid work for many years now and that many small projects are fully paid for by companies. However, we also find that any non-trivial project balances the amount of paid developer with volunteer work, and we suggest that the ratio of volunteer to paid work can serve as an indicator for the health of open source projects and aid the management of the respective communities. Index Terms-Open source software, empirical software engineering, volunteer open source, paid open source.

Modern cars exist in an vast number of variants. Thus, variability has to be dealt with in all phases of the development process, in particular during model-based development of software-intensive functionality using Matlab/Simulink. Currently, variability is often encoded within a functional model leading to so called 150%-models which easily become very complex and do not scale for larger product lines.To counter these problems, we propose a modular variability modeling approach for Matlab/Simulink based on the concept of delta modeling [8,9,24]. A functional variant is described by a delta encapsulating a set of modifications. A sequence of deltas can be applied to a core product to derive the desired variant. We present a prototypical implementation, which is integrated into Matlab/Simulink and offers graphical editing of delta models.

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.

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.Comment: 17 pages, 7 figures. Proceedings of the 39th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2013), LNCS 7741. Page 52-66. Springer Verlag, 201