论文标题
从GitHub活动中挖掘OSS技能
Towards Mining OSS Skills from GitHub Activity
论文作者
论文摘要
开源软件（OSS）开发依赖于各种技能集。但是，据我们所知，没有一些工具可以检测到与OSS相关的技能。在本文中，我们提出了一种新颖的方法，可以在称为Disko的工具中检测OSS技能和原型。我们的方法依赖于确定相关信号，这些信号是与技能相关的可测量活动或提示。我们的工具检测到贡献者是如何的1）教会其他人参与OSS项目，2）表现出对OSS项目的承诺，3）具有特定编程语言的知识，而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该工具。我们证明磁盘产生了令人鼓舞的结果：它以77％至97％的精度得分检测到这些技能的存在。我们还发现，超过54％的参与者会表现出他们的高级能力。我们的方法可用于改变现有的OSS体验，例如识别合作者，将导师匹配到受训者以及分配项目角色。鉴于我们的方法的积极结果和潜在的影响，我们概述了未来的研究机会解释和分享OSS技能。
Open source software (OSS) development relies on diverse skill sets. However, to our knowledge, there are no tools which detect OSS-related 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.
