SimilaR: R Code Clone and Plagiarism Detection
Maciej Bartoszuk, Marek Ga̧golewski · The R Journal · 2020
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.