Scaling open source communities

Tan, Xin; Zhou, Minghui; Fitzgerald, Brian

doi:10.1145/3377811.3380920

Cited by 14 publications

(7 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 ). The commit size was measured by a widely used metric [72,79,84]: lines of code (LOC) in a commit. For each developer, we took the median of the LOC of all contributed commits to represent their commit size.…”

Section: Measuring Contribution Performance Contribution Frequencymentioning

confidence: 99%

How Are Paid and Volunteer Open Source Developers Different? A Study of the Rust Project

Zhang,

Qin,

Stol

et al. 2024

Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

View full text Add to dashboard Cite

It is now commonplace for organizations to pay developers to work on specific open source software (OSS) projects to pursue their business goals. Such paid developers work alongside voluntary contributors, but given the different motivations of these two groups of developers, conflict may arise, which may pose a threat to a project's sustainability. This paper presents an empirical study of paid developers and volunteers in Rust, a popular open source programming language project. Rust is a particularly interesting case given considerable concerns about corporate participation. We compare volunteers and paid developers through contribution characteristics and long-term participation, and solicit volunteers' perceptions on paid developers. We find that core paid developers tend to contribute more frequently; commits contributed by onetime paid developers have bigger sizes; peripheral paid developers implement more features; and being paid plays a positive role in becoming a long-term contributor. We also find that volunteers do have some prejudices against paid developers. This study suggests that the dichotomous view of paid vs. volunteer developers is too simplistic and that further subgroups can be identified. Companies should become more sensitive to how they engage with OSS communities, in certain ways as suggested by this study.

show abstract

Section: Measuring Contribution Performance Contribution Frequencymentioning

confidence: 99%

How Are Paid and Volunteer Open Source Developers Different? A Study of the Rust Project

Zhang,

Qin,

Stol

et al. 2024

Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

View full text Add to dashboard Cite

show abstract

“…The more recent studies of collaboration networks look deeper into the collaboration data, searching for various social and organisational phenomena [6], [15]. A notable work involving collaborative network analysis on a project scale is done by Gote et al [15] with git2net -a toolkit for constructing temporal co-editing networks from Git history.…”

Section: A Studies On Collaboration In Ossmentioning

confidence: 99%

“…Collaboration of OSS developers has been extensively studied on the small scale. Numerous studies have focused on collaboration in individual projects, such as the Linux kernel [6], or small samples of projects from GitHub [7]. Such works shed light on the collaboration process in individual small teams and projects and help the project owners to organise the development in a more efficient way [6].…”

Section: Introductionmentioning

confidence: 99%

"Constructing and Analyzing Temporal Networks of OSS Programming Language Ecosystems" reproducibility package

2022

View full text Add to dashboard Cite

One of the primary factors that encourage developers to contribute to open source software (OSS) projects is the collaborative nature of OSS development. However, the collaborative structure of these communities largely remains unclear, partly due to the enormous scale of data to be gathered, processed, and analyzed.In this work, we utilize the World Of Code dataset, which contains commit activity data for millions of OSS projects, to build collaboration networks for ten popular programming language ecosystems, containing in total over 290M commits across over 18M projects. We build a collaboration graph representation for each language ecosystem, having authors and projects as nodes, which enables various forms of social network analysis on the scale of language ecosystems. Moreover, we capture the information on the ecosystems' evolution by slicing each network into 30 historical snapshots. Additionally, we calculate multiple collaboration metrics that characterize the ecosystems' states.We make the resulting dataset publicly available 1 , including the constructed graphs and the pipeline enabling the analysis of more ecosystems.

show abstract

“…During that transition phase, the automatisms among developers that were possible during the early stages of the project are not possible. And anyhow, becoming a community-driven project is a sign that the project attracts much interest, and that external effort, if conveniently integrated into the project, can set the project in another level (Zhou et al 2017;Tan et al 2020). It is in such scenarios where having metrics (and tools) on project instability that point out to risky parts in the source code would be very valuable.…”

Section: Introductionmentioning

confidence: 99%

Can instability variations warn developers when open-source projects boost?

Capilla,

Salamanca,

Valdezate

et al. 2024

Empir Software Eng

View full text Add to dashboard Cite

Although architecture instability has been studied and measured using a variety of metrics, a deeper analysis of which project parts are less stable and how such instability varies over time is still needed. While having more information on architecture instability is, in general, useful for any software development project, it is especially important in Open Source Software (OSS) projects where the supervision of the development process is more difficult to achieve. In particular, we are interested when OSS projects grow from a small controlled environment (i.e., the cathedral phase) to a community-driven project (i.e., the bazaar phase). In such a transition, the project often explodes in terms of software size and number of contributing developers. Hence, the complexity of the newly added features, and the frequency of the commits and files modified may cause significant variations of the instability of the structure of the classes and packages. Consequently, in this article we analyze the instability in OSS projects, especially during that sensitive phase where they become community-driven. Our results show that instability metrics can be easily obtained in such type of transitions. We also observed from our case studies that instability metrics can help finding out the balance between adding new functionality and performing refactoring. As a conclusions we state that instability metrics offer relevant information in the transition phase from the cathedral to the bazaar.

show abstract

Scaling open source communities

Abstract: Large-scale open source communities, such as the Linux kernel, have gone through decades of development, substantially growing in scale and complexity. In the traditional workflow, maintainers serve as "gatekeepers" for the subsystems that they maintain. As

Cited by 14 publications

References 45 publications

How Are Paid and Volunteer Open Source Developers Different? A Study of the Rust Project

How Are Paid and Volunteer Open Source Developers Different? A Study of the Rust Project

"Constructing and Analyzing Temporal Networks of OSS Programming Language Ecosystems" reproducibility package

Can instability variations warn developers when open-source projects boost?

Contact Info

Product

Resources

About