arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.03927cs.SE
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一个开源软件数据集

A Dataset of Enterprise-Driven Open Source Software

Diomidis Spinellis, Zoe Kotti, Konstantinos Kravvaritis, Georgios Theodorou, Panos Louridas

摘要:

我们提出了一个主要由企业而不是志愿者开发的开源软件的数据集。这可以用于解决已知的普遍性问题,也可以用于对开源商业软件开发进行研究。基于企业员工可能会使用其提供的电子邮件帐户为其组织开发的项目做出贡献的前提,我们从开放数据源以及通过白名单和黑名单挖掘与企业相关的域名,并通过三次搜索来识别17,264个企业GitHub项目。我们提供这些作为一个数据集,详细说明其出处和属性。对数据集样本的手动评估显示识别准确率为89%。通过探索性的数据分析,我们发现,项目由多个企业内部人员组成,他们似乎比他们的重量更重要,并且在一小部分相对较大的项目中,开发完全通过企业内部人员进行。

英文摘要:

We present a dataset of open source software developed mainly by enterprises rather than volunteers. This can be used to address known generalizability concerns, and, also, to perform research on open source business software development. Based on the premise that an enterprise's employees are likely to contribute to a project developed by their organization using the email account provided by it, we mine domain names associated with enterprises from open data sources as well as through white- and blacklisting, and use them through three heuristics to identify 17,264 enterprise GitHub projects. We provide these as a dataset detailing their provenance and properties. A manual evaluation of a dataset sample shows an identification accuracy of 89%. Through an exploratory data analysis we found that projects are staffed by a plurality of enterprise insiders, who appear to be pulling more than their weight, and that in a small percentage of relatively large projects development happens exclusively through enterprise insiders.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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