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https://doi.org/10.1109/scam.2...
Article . 2014 . Peer-reviewed
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Identifying Source Code Reuse across Repositories Using LCS-Based Source Code Similarity

Authors: Naohiro Kawamitsu; Takashi Ishio; Tetsuya Kanda 0001; Raula Gaikovina Kula; Coen De Roover; Katsuro Inoue;

Identifying Source Code Reuse across Repositories Using LCS-Based Source Code Similarity

Abstract

Developers often reuse source files developed for another project. In order to update a reused file to a newer version released by the original project, developers have to track which revision of a file was reused and how its content was modified. However, such tracking is tedious for developers. Many projects keep older versions of files whose bugs are already fixed in the original project. In this paper, we propose a technique to automatically identify source code reuse relationships between two repositories. Using a similarity metric based on longest common subsequence, we identify pairs of similar revisions of files across the repositories. To evaluate our approach, we have analyzed eight project pairs of open source software projects and compared the result with the recorded information in the repositories. As a result, we have identified 1394 file revisions as instances of source code reuse. While 75.3% of the instances are recorded in the repositories, 20.1% of the instances are unrecorded but recovered by our approach.

Country
Belgium
Related Organizations
Keywords

origin analysis, code similarity, Software Reuse

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Top 10%
Top 10%