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DOI

Composite commits are a common mistake in the use of version control software.
A composite commit groups many unrelated tasks,
rendering the commit difficult for developers to understand, revert, or integrate
and for empirical researchers to analyse.
We propose an algorithmic foundation for tool support to identify such composite commits.
Our algorithm computes both a program dependence graph and
the changes to the abstract syntax tree for the files that have been changed in a commit.
Our algorithm then groups these fine-grained changes according to the slices through the dependence graph they belong to.
To evaluate our technique, we analyse and refine an established dataset of Java commits, the results of which we also make available.
We find that our algorithm can determine whether or not a commit is composite.
For the majority of commits, this analysis takes but a few seconds.
The parts of a commit that our algorithm identifies do not map directly to the commit's tasks.
The parts tend to be smaller, but stay within their respective tasks.
Original languageEnglish
Title of host publicationProceedings - 18th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2018
PublisherIEEE
Pages193-202
Number of pages10
ISBN (Electronic)978-1-5386-8290-6
ISBN (Print) 978-1-5386-8291-3
DOIs
Publication statusPublished - 9 Nov 2018
Event18th IEEE International Working Conference on Source Code Analysis and Manipulation - Madrid, Spain, Madrid, Spain
Duration: 23 Sep 201824 Sep 2018
Conference number: 18
http://www.ieee-scam.org/2018/

Conference

Conference18th IEEE International Working Conference on Source Code Analysis and Manipulation
Abbreviated titleSCAM
CountrySpain
CityMadrid
Period23/09/1824/09/18
Internet address

    Research areas

  • Changedistiller, Changenodes, Class dependence graph, Commit, Inter procedural, Intra procedural, Program dependence graph, Program slicing, Slicing, Static analysis, System dependence graph, Tangled, Tinypdg, Untangling

ID: 39174282