Identifying Features in Forks

Shurui Zhou, Stefan Stanciulescu, Olaf Lessnich, Yingfei Xiong, Andrzej Wasowski, Christian Kästner

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


Fork-based development has been widely used both in open source
communities and in industry, because it gives developers flexibility
to modify their own fork without affecting others. Unfortunately,
this mechanism has downsides: When the number of forks becomes
large, it is difficult for developers to get or maintain an overview of
activities in the forks. Current tools provide little help. We introduce
Infox, an approach to automatically identify non-merged features
in forks and to generate an overview of active forks in a project. The
approach clusters cohesive code fragments using code and network-
analysis techniques and uses information-retrieval techniques to
label clusters with keywords. The clustering is effective, with 90 %
accuracy on a set of known features. In addition, a human-subject
evaluation shows that Infox can provide actionable insight for
developers of forks.
Original languageEnglish
Title of host publicationProceedings of the 40th ACM/IEEE International Conference on Software Engineering (ICSE2018), Gothenburg, Sweden
Number of pages12
Publication date2018
ISBN (Print)978-1-4503-5638-1
Publication statusPublished - 2018
EventICSE 2018 40th International Conference on Software Engineering - Gothenburg, Sweden
Duration: 27 May 20183 Jun 2018


ConferenceICSE 2018 40th International Conference on Software Engineering
Internet address


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