GIRT-Data: Sampling GitHub Issue Report Templates

Nafiseh NikeghbalAmir Hossein KargaranAbbas HeydarnooriHinrich Sch\"utze

Mar 2023

摘要

GitHub's issue reports provide developers with valuable information that isessential to the evolution of a software development project. Contributors canuse these reports to perform software engineering tasks like submitting bugs,requesting features, and collaborating on ideas. In the initial versions ofissue reports, there was no standard way of using them. As a result, thequality of issue reports varied widely. To improve the quality of issuereports, GitHub introduced issue report templates (IRTs), which pre-fill issuedescriptions when a new issue is opened. An IRT usually contains greetingcontributors, describing project guidelines, and collecting relevantinformation. However, despite of effectiveness of this feature which wasintroduced in 2016, only nearly 5% of GitHub repositories (with more than 10stars) utilize it. There are currently few articles on IRTs, and the availableones only consider a small number of repositories. In this work, we introduceGIRT-Data, the first and largest dataset of IRTs in both YAML and Markdownformat. This dataset and its corresponding open-source crawler tool areintended to support research in this area and to encourage more developers touse IRTs in their repositories. The stable version of the dataset contains1,084,300 repositories and 50,032 of them support IRTs. The stable version ofthe dataset and crawler is available here:https://github.com/kargaranamir/girt-data

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