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The fork-based development mechanism provides the flexibilityand the unified processes for software teams to collaborate easilyin a distributed setting without too much coordination overhead.Currently, multiple social coding platforms support fork-based de-velopment, such as GitHub, GitLab, and Bitbucket. Although thesedifferent platforms virtually share the same features, they havedifferent emphasis. As GitHub is the most popular platform and thecorresponding data is publicly available, most of the current stud-ies are focusing on GitHub hosted projects. However, we observedanecdote evidences that people are confused about choosing amongthese platforms, and some projects are migrating from one platformto 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 acrossplatforms. In this paper, we conduct an exploratory study on 10popular open-source projects to identify cross-platform forks andinvestigate the motivation behind. Preliminary result shows thatcross-platform forks do exist, for the 10 subject systems in thisstudy, we found 81,357 forks in total among which 179 forks areon GitLab. Based on our qualitative analysis we found that most ofthe cross-platform forks that we identified are mirrors of anotherplatform, but we still find cases that were created due to preferenceof using certain functionalities (e.g. Continuous Integration(CI))supported by different platforms. This study lays the foundation offuture research directions, such as understanding the differencesbetween platforms and supporting cross-platform collaboration.
OSS, GitHub, Social coding, Fork, Software Heritage Dataset
OSS, GitHub, Social coding, Fork, Software Heritage Dataset
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 8 | |
| downloads | 25 |

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