Team discussions and dynamics during DevOps tool adoptions in OSS projects
Team discussions and dynamics during DevOps tool adoptions in OSS projects
复制标题
OSS 项目中采用 DevOps 工具期间的团队讨论和动态
DOI：
10.1145/3324884.3416640
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Filkov, Vladimir
中科院分区：
文献类型：
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作者：
Yin, Likang;Filkov, Vladimir
在开源软件（OSS）项目中，预构建工具主导着面向DevOps的管道。在实践中，存在大量的配置管理、基于云的持续集成和自动化部署工具，并且每个任务通常不止一个。OSS项目经常采用（和放弃）工具。先前的工作表明，一些工具的采用是在讨论之前进行的，并且工具的采用可以为项目带来好处。但重要的问题仍然存在：团队如何决定采用一种工具？在通过之前讨论了什么，讨论了多久？什么样的团队特征是决定采用的决定因素？在本文中，我们采用了一个大规模的实证研究，以团队讨论的特点，并识别到OSS项目的开发管道的工具采用的团队水平的决定因素。在团队和个人动机和动力理论的指导下，我们进行探索性数据分析，进行深入的案例研究，并开发回归模型，以了解采用和讨论长度的决定因素，以及它们对采用的影响方向。从大型GitHub项目的提交和评论跟踪数据来看，我们的模型发现，之前接触过的工具和成员参与度与工具采用呈正相关，而更长的讨论和新团队成员的数量则呈负相关。这些结果可以为不同程序员团队采用工具的及时性提供技术适当性之外的指导。https://github.com/lkyin/tool_adoptions
In Open Source Software (OSS) projects, pre-built tools dominate DevOps-oriented pipelines. In practice, a multitude of configuration management, cloud-based continuous integration, and automated deployment tools exist, and often more than one for each task. Tools are adopted (and given up) by OSS projects regularly. Prior work has shown that some tool adoptions are preceded by discussions, and that tool adoptions can result in benefits to the project. But important questions remain: how do teams decide to adopt a tool? What is discussed before the adoption and for how long? And, what team characteristics are determinant of the adoption?In this paper, we employ a large-scale empirical study in order to characterize the team discussions and to discern the teamlevel determinants of tool adoption into OSS projects' development pipelines. Guided by theories of team and individual motivations and dynamics, we perform exploratory data analyses, do deep-dive case studies, and develop regression models to learn the determinants of adoption and discussion length, and the direction of their effect on the adoption. From data of commit and comment traces of large-scale GitHub projects, our models find that prior exposure to a tool and member involvement are positively associated with the tool adoption, while longer discussions and the number of newer team members associate negatively. These results can provide guidance beyond the technical appropriateness for the timeliness of tool adoptions in diverse programmer teams.Our data and code is available at https://github.com/lkyin/tool_adoptions.