Measuring Developer Contribution From Software Repository Data

Our work is concerned with an enriched perspective of what constitutes developer contribution in software infrastructures supporting incremental development and distributed software projects. We use the term “contribution” to express the combination of all the actions a developer has performed during the development process and propose a model for calculating this individually for developers participating in a software project. Our approach departs from the traditional practice of only measuring the contribution to the final outcome (the code) and puts emphasis additionally on other activities that do not directly affect the product itself but are essential to the development process.We use the Open Source Software (OSS) context to take advantage of the public availability of data in software repositories. In this paper, we present our method of calculation and its system implementation and we apply our measurements on various projects from the gnome ecosystem

Exploring the Impact of Socio-Technical Core-Periphery Structures in Open Source Software Development

In this paper we apply the social network concept of core-periphery structure to the sociotechnical structure of a software development team. We propose a socio-technical pattern that can be used to locate emerging coordination problems in Open Source projects. With the help of our tool and method called TESNA, we demonstrate a method to monitor the socio-technical core-periphery movement in Open Source projects. We then study the impact of different core-periphery movements on Open Source projects. We conclude that a steady core-periphery shift towards the core is beneficial to the project, whereas shifts away from the core are clearly not good. Furthermore, oscillatory shifts towards and away from the core can be considered as an indication of the instability of the project. Such an analysis can provide developers with a good insight into the health of an Open Source project. Researchers can gain from the pattern theory, and from the method we use to study the core-periphery movements

Estimating development effort in free/open source software projects by mining software repositories: A case study of OpenStack

Because of the distributed and collaborative nature of free/open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially-but not only-because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.Gregorio Robles, Carlos Cervig on and Jes us M. Gonz alez-Barahona, project SobreSale (TIN2011-28110). and The work of Daniel Izquierdo has been funded in part by the Torres Quevedo program (PTQ-12-05577

How Much is the Whole Really More than the Sum of its Parts? 1 + 1 = 2.5: Superlinear Productivity in Collective Group Actions

In a variety of open source software projects, we document a superlinear growth of production ($R \sim c^\beta$) as a function of the number of active developers $c$, with $\beta \simeq 4/3$ with large dispersions. For a typical project in this class, doubling of the group size multiplies typically the output by a factor $2^\beta=2.5$, explaining the title. This superlinear law is found to hold for group sizes ranging from 5 to a few hundred developers. We propose two classes of mechanisms, {\it interaction-based} and {\it large deviation}, along with a cascade model of productive activity, which unifies them. In this common framework, superlinear productivity requires that the involved social groups function at or close to criticality, in the sense of a subtle balance between order and disorder. We report the first empirical test of the renormalization of the exponent of the distribution of the sizes of first generation events into the renormalized exponent of the distribution of clusters resulting from the cascade of triggering over all generation in a critical branching process in the non-meanfield regime. Finally, we document a size effect in the strength and variability of the superlinear effect, with smaller groups exhibiting widely distributed superlinear exponents, some of them characterizing highly productive teams. In contrast, large groups tend to have a smaller superlinearity and less variability.Comment: 29 pages, 8 figure