从GitHub活动中挖掘OSS技能

Jenny T Liang, Thomas Zimmermann, Denae Ford
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引用次数: 4

摘要

开源软件(OSS)的开发依赖于不同的技能集。然而,据我们所知,还没有工具可以检测oss相关的技能。在本文中,我们提出了一种新的方法来检测OSS技能,并在一个名为DisKo的工具中对其进行原型化。我们的方法依赖于识别相关信号,这些信号是与技能相关的可测量活动或线索。我们的工具检测贡献者如何1)教导其他人参与到OSS项目中,2)显示对OSS项目的承诺,3)具有特定编程语言的知识,以及4)熟悉OSS实践。然后我们通过对455个OSS贡献者进行调查来评估这个工具。我们证明了DisKo产生了有希望的结果:它检测到这些技能的存在,准确率在77%到97%之间。我们还发现,超过54%的参与者会展示他们的高水平技能。我们的方法可以用于转换现有的OSS经验,例如确定合作者,将导师与受训者相匹配,以及分配项目角色。鉴于我们的方法的积极结果和潜在影响,我们概述了在解释和共享OSS技能方面的未来研究机会。CCS CONCEPTS•软件及其工程→开源模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Mining OSS Skills from GitHub Activity
Open source software (OSS) development relies on diverse skill sets. However, to our knowledge, there are no tools which detect OSSrelated skills. In this paper, we present a novel method to detect OSS skills and prototype it in a tool called DisKo. Our approach relies on identifying relevant signals, which are measurable activities or cues associated with a skill. Our tool detects how contributors 1) teach others to be involved in OSS projects, 2) show commitment towards an OSS project, 3) have knowledge in specific programming languages, and 4) are familiar with OSS practices. We then evaluate the tool by administering a survey to 455 OSS contributors. We demonstrate that DisKo yields promising results: it detects the presence of these skills with precision scores between 77% to 97%. We also find that over 54% of participants would display their high-proficiency skills. Our approach can be used to transform existing OSS experiences, such as identifying collaborators, matching mentors to mentees, and assigning project roles. Given the positive results and potential impact of our approach, we outline future research opportunities in interpreting and sharing OSS skills. CCS CONCEPTS • Software and its engineering → Open source model.
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