Paper Info
Title
SimilaR: R Code Clone and Plagiarism Detection.
Abstract
Third-party software for assuring source code quality is becoming increasingly popular. Tools that evaluate the coverage of unit tests, perform static code analysis, or inspect run-time memory use are crucial in the software development life cycle. More sophisticated methods allow for performing meta-analyses of large software repositories, e.g., to discover abstract topics they relate to or common design patterns applied by their developers. They may be useful in gaining a better understanding of the component interdependencies, avoiding cloned code as well as detecting plagiarism in programming classes. A meaningful measure of similarity of computer programs often forms the basis of such tools. While there are a few noteworthy instruments for similarity assessment, none of them turns out particularly suitable for analysing R code chunks. Existing solutions rely on rather simple techniques and heuristics and fail to provide a user with the kind of sensitivity and specificity required for working with R scripts. In order to fill this gap, we propose a new algorithm based on a Program Dependence Graph, implemented in the SimilaR package. It can serve as a tool not only for improving R code quality but also for detecting plagiarism, even when it has been masked by applying some obfuscation techniques or imputing dead code. We demonstrate its accuracy and efficiency in a real-world case study.
Year
DOI
Venue
2020
10.32614/rj-2020-017
R JOURNAL
DocType
Volume
Issue
Journal
12
1
ISSN
Citations 
PageRank 
2073-4859
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Maciej Bartoszuk1173.62
Marek Gagolewski218623.86