Measuring and Modeling Group Dynamics in Open-Source Software Development: A Tensor Decomposition Approach

Thomas Bock, Angelika Schmid, S. Apel
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引用次数: 5

Abstract

Many open-source software projects depend on a few core developers, who take over both the bulk of coordination and programming tasks. They are supported by peripheral developers, who contribute either via discussions or programming tasks, often for a limited time. It is unclear what role these peripheral developers play in the programming and communication efforts, as well as the temporary task-related sub-groups in the projects. We mine code-repository data and mailing-list discussions to model the relationships and contributions of developers in a social network and devise a method to analyze the temporal collaboration structures in communication and programming, learning about the strength and stability of social sub-groups in open-source software projects. Our method uses multi-modal social networks on a series of time windows. Previous work has reduced the network structure representing developer collaboration to networks with only one type of interaction, which impedes the simultaneous analysis of more than one type of interaction. We use both communication and version-control data of open-source software projects and model different types of interaction over time. To demonstrate the practicability of our measurement and analysis method, we investigate 10 substantial and popular open-source software projects and show that, if sub-groups evolve, modeling these sub-groups helps predict the future evolution of interaction levels of programmers and groups of developers. Our method allows maintainers and other stakeholders of open-source software projects to assess instabilities and organizational changes in developer interaction and can be applied to different use cases in organizational analysis, such as understanding the dynamics of a specific incident or discussion.
开源软件开发中群体动力学的测量和建模:张量分解方法
许多开源软件项目依赖于少数核心开发人员,他们承担了大量的协调和编程任务。它们由外围开发人员提供支持,这些开发人员通常在有限的时间内通过讨论或编程任务做出贡献。目前还不清楚这些外围开发人员在编程和通信工作中扮演什么角色,以及项目中与临时任务相关的子小组。我们挖掘代码存储库数据和邮件列表讨论,以模拟社交网络中开发人员的关系和贡献,并设计了一种方法来分析通信和编程中的时间协作结构,了解开源软件项目中社会子群体的强度和稳定性。我们的方法在一系列时间窗口上使用多模态社会网络。以前的工作已经将表示开发人员协作的网络结构简化为只有一种交互类型的网络,这阻碍了对多种交互类型的同时分析。我们使用开源软件项目的通信和版本控制数据,并对不同类型的交互建模。为了证明我们的测量和分析方法的实用性,我们调查了10个实质性的和流行的开源软件项目,并表明,如果子群体发展,对这些子群体建模有助于预测程序员和开发人员群体的交互水平的未来发展。我们的方法允许开源软件项目的维护者和其他利益相关者评估开发人员交互中的不稳定性和组织变化,并且可以应用于组织分析中的不同用例,例如理解特定事件或讨论的动态。
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