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Evidence shows that developer reputation is extremely important when accepting pull requests or resolving reported issues. It is particularly salient in Free/Libre Open Source Software since the developers are distributed around the world, do not work for the same organization and, in most cases, never meet face to face. The existing solutions to expose developer reputation tend to be forge specific (GitHub), focus on activity instead of impact, do not leverage social or technical networks, and do not correct often misspelled developer identities. We aim to remedy this by amalgamating data from all public Git repositories, measuring the impact of developer work, expose developer's collaborators, and correct notoriously problematic developer identity data. We leverage World of Code (WoC), a collection of an almost complete (and continuously updated) set of Git repositories by first allowing developers to select which of the 34 million(M) Git commit author IDs belong to them and then generating their profiles by treating the selected collection of IDs as that single developer. As a side-effect, these selections serve as a training set for a supervised learning algorithm that merges multiple identity strings belonging to a single individual. As we evaluate the tool and the proposed impact measure, we expect to build on these findings to develop reputation badges that could be associated with pull requests and commits so developers could easier trust and prioritize them.
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A Complete Set of Related Git Repositories Identified viaCommunity Detection Approaches Based on Shared Commits
In order to understand the state and evolution of the entirety of open source software we need to get a handle on the set of distinct software projects. Most of open source projects presently utilize Git, which is a distributed version control system allowing easy creation of clones and resulting in numerous repositories that are almost entirely based on some parent repository from which they were cloned. Git commits are unlikely to get produce and represent a way to group cloned repositories. We use World of Code infrastructure containing approximately 2B commits and 100M repositories to create and share such a map. We discover that the largest group contains almost 14M repositories most of which are unrelated to each other. As it turns out, the developers can push git object to an arbitrary repository or pull objects from unrelated repositories, thus linking unrelated repositories. To address this, we apply Louvain community detection algorithm to this very large graph consisting of links between commits and projects. The approach successfully reduces the size of the megacluster with the largest group of highly interconnected projects containing under 400K repositories. We expect that the resulting map of related projects as well as tools and methods to handle the very large graph will serve as a reference set for mining software projects and other applications. Further work is needed to determine different types of relationships among projects induced by shared commits and other relationships, for example, by shared source code or similar filenames.
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- PAR ID:
- 10189286
- Date Published:
- Journal Name:
- IEEE International Working Conference on Mining Software Repositories
- ISSN:
- 2160-1860
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- The DOI is not currently available.
