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Understanding the relation between repeat developer interactions and bug resolution times in large open source ecosystems: A multisystem study
Journal of Software: Evolution and Process ( IF 2 ) Pub Date : 2020-11-29 , DOI: 10.1002/smr.2317
Subhajit Datta 1 , Reshma Roychoudhuri 2 , Subhashis Majumder 2
Affiliation  

Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we empirically examine such a question using real‐world data from three diverse development ecosystems, collectively involving 400,000+ units of work and 600,000+ comments exchanged between numerous developers. Our statistical models consistently establish a counter‐intuitive relation between repeat developer interaction and bug resolution times. Our experimental results show that more instances of repeat developer interactions over bug fixing are associated with more time taken for the bugs to be fixed. Given the expanse and variety of the underlying data, our results offer an unexpected set of insights on a key dynamic of collaboration in software development ecosystems. We discuss how these insights can influence the practice of large‐scale software development at individual, team and organizational levels.

中文翻译:

了解大型开放源代码生态系统中重复开发人员交互与错误解决时间之间的关系:多系统研究

分布在不同地区和时区的分布式开发人员团队正在越来越多地构建大型软件系统。确保此类团队内部和团队之间的知识转移顺畅和技能渗透仍然是组织面临的主要挑战。为了应对这一挑战,组织经常要解决以下问题:团队成员之间的重复协作是否以及如何与重要活动的结果相关联。在本文中,“重复互动”一词并不意味着更多的互动。它指的是曾经合作过的一对开发人员之间的重复交互。在本文中,我们使用来自三个不同发展生态系统的现实世界数据以经验方式研究了这个问题,这三个生态系统共涉及40万多个工作单元和600个工作单元,在众多开发人员之间交换了000多个评论。我们的统计模型始终在重复开发人员的互动与错误解决时间之间建立反直觉的关系。我们的实验结果表明,与错误修复相比,更多的重复开发人员交互实例与错误修复所花费的时间更多。考虑到基础数据的广泛性和多样性,我们的结果提供了关于软件开发生态系统中协作的关键动态的出乎意料的一组见解。我们讨论了这些见解如何影响个人,团队和组织级别的大规模软件开发实践。我们的实验结果表明,与错误修复相比,更多的重复开发人员交互实例与错误修复所花费的时间更多。考虑到基础数据的广泛性和多样性,我们的结果提供了关于软件开发生态系统中协作的关键动态的出乎意料的一组见解。我们讨论了这些见解如何影响个人,团队和组织级别的大规模软件开发实践。我们的实验结果表明,与错误修复相比,更多的重复开发人员交互实例与错误修复所花费的时间更多。考虑到基础数据的广泛性和多样性,我们的结果提供了关于软件开发生态系统中协作的关键动态的出乎意料的一组见解。我们讨论了这些见解如何影响个人,团队和组织级别的大规模软件开发实践。
更新日期:2020-11-29
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