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Identifying Features in Forks

  • Shurui Zhou
    ,
  • Stefan Stanciulescu
    ,
  • Olaf Lessnich
    ,
  • Yingfei Xiong
    ,
  • ,
  • Christian Kästner
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

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.

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Publication milestones

  • Published - 2018

Publication status

Published - 2018

Publisher

IEEE, United States
978-1-4503-5638-1

Publication IDs

  • Scopus: 85133559476

Host publication title

Proceedings of the 40th ACM/IEEE International Conference on Software Engineering (ICSE2018), Gothenburg, Sweden

Publication metrics

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Captures
44
Citation count
63

Related Event

Title

ICSE 2018 40th International Conference on Software Engineering

Event type

Conference

Degree of recognition

International event

Date

27/05/2018 - 03/06/2018

Location

GothenburgSweden