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ICSE 2018

Identifying features in forks

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

Full textDOI 10.1145/3180155.3180205dblp

Abstract

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.

BibTeX
@inproceedings{Zhou-al:ICSE18,
  author    = {Shurui Zhou and
               Stefan Stanciulescu and
               Olaf Le{\ss}enich and
               Yingfei Xiong and
               Andrzej Wasowski and
               Christian K{\"{a}}stner},
  title     = {Identifying features in forks},
  booktitle = {ICSE},
  pages     = {105--116},
  publisher = {{ACM}},
  year      = {2018},
}

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