Preprocessed data for find motives behind cross-platform forks from SWHGD dataset

Bhattacharjee, Avijit; Chakroborti, Debasish; Roy, Chanchal K.; Schneider, Kevin

doi:10.5281/zenodo.3699031

Cited by 1 publication

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“…We used Python code to run SQL queries on the PostgreSQL instance using Sqlalchemy [8] module. We uploaded the extracted data [3] and used Python program [6] to Zendoo.…”

Section: Subject Systems and Data Collectionmentioning

confidence: 99%

An Exploratory Study to Find Motives Behind Cross-platform Forks from Software Heritage Dataset

Bhattacharjee

Nath

Zhou

et al. 2020

Proceedings of the 17th International Conference on Mining Software Repositories

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The fork-based development mechanism provides the flexibility and the unified processes for software teams to collaborate easily in a distributed setting without too much coordination overhead. Currently, multiple social coding platforms support fork-based development, such as GitHub, GitLab, and Bitbucket. Although these different platforms virtually share the same features, they have different emphasis. As GitHub is the most popular platform and the corresponding data is publicly available, most of the current studies are focusing on GitHub hosted projects. However, we observed anecdote evidences that people are confused about choosing among these platforms, and some projects are migrating from one platform to another, and the reasons behind these activities remain unknown. With the advances of Software Heritage Graph Dataset (SWHGD), we have the opportunity to investigate the forking activities across platforms. In this paper, we conduct an exploratory study on 10 popular open-source projects to identify cross-platform forks and investigate the motivation behind. Preliminary result shows that cross-platform forks do exist. For the 10 subject systems in this study, we found 81,357 forks in total among which 179 forks are on GitLab. Based on our qualitative analysis, we found that most of the cross-platform forks that we identified are mirrors of the repositories on another platform, but we still find cases that were created due to preference of using certain functionalities (e.g. Continuous Integration (CI)) supported by different platforms. This study lays the foundation of future research directions, such as understanding the differences between platforms and supporting cross-platform collaboration.

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“…We used Python code to run SQL queries on the PostgreSQL instance using Sqlalchemy [8] module. We uploaded the extracted data [3] and used Python program [6] to Zendoo.…”

Section: Subject Systems and Data Collectionmentioning

confidence: 99%