Sampling Projects in GitHub for MSR Studies
Sampling Projects in GitHub for MSR Studies
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DOI：
10.1109/msr52588.2021.00074
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Ozren Dabic;Emad Aghajani;G. Bavota
中科院分区：
文献类型：
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作者：
Ozren Dabic;Emad Aghajani;G. Bavota
作为第一步，几乎每个采矿软件存储库（MSR）的研究都需要选择主题软件存储库。这些存储库通常是使用研究目标规定的特定选择标准从托管服务等托管服务中收集的。例如，与许可有关的研究可能有兴趣选择明确宣布许可的项目。定义了选择标准后，可以使用诸如GITHUB API之类的实用程序来“查询”托管服务。但是，研究人员必须应对这些API施加的使用限制以及缺乏所需信息。例如，GitHub搜索API允许每分钟30个请求，并且在搜索存储库时，仅提供有限的信息（例如，不包括存储库中的提交数量）。为了支持GITHUB的研究人员进行抽样项目，我们提出了GHS（GitHub搜索），该数据集包含735,669个用10种编程语言编写的735,669个存储库，其中包含25个特征（例如，提交数量，许可等）。一组特征是通过在MSR研究中寻找经常使用的项目选择标准来得出的，并且数据集被不断更新到（i）始终提供有关现有项目的新数据，并且（ii）增加索引项目的数量。可以通过我们构建的Web应用程序查询GHS数据集，该应用程序允许设置研究所需的许多选择标准组合，并下载匹配存储库的信息：https：//seart-ghs.si.usi.ch。
Almost every Mining Software Repositories (MSR) study requires, as first step, the selection of the subject software repositories. These repositories are usually collected from hosting services like GitHub using specific selection criteria dictated by the study goal. For example, a study related to licensing might be interested in selecting projects explicitly declaring a license. Once the selection criteria have been defined, utilities such as the GitHub APIs can be used to "query" the hosting service. However, researchers have to deal with usage limitations imposed by these APIs and a lack of required information. For example, the GitHub search APIs allow 30 requests per minute and, when searching repositories, only provide limited information (e.g., the number of commits in a repository is not included). To support researchers in sampling projects from GitHub, we present GHS (GitHub Search), a dataset containing 25 characteristics (e.g., number of commits, license, etc.) of 735,669 repositories written in 10 programming languages. The set of characteristics has been derived by looking for frequently used project selection criteria in MSR studies and the dataset is continuously updated to (i) always provide fresh data about the existing projects, and (ii) increase the number of indexed projects. The GHS dataset can be queried through a web application we built that allows to set many combinations of selection criteria needed for a study and download the information of matching repositories: https://seart-ghs.si.usi.ch.