@inproceedings{7a56121530a14d86b2bbbfb7fa3f3a63,
title = "Kitsune: Structurally Aware and Adaptable Plagiarism Detection",
abstract = "Plagiarism is a huge problem in a learning environment. In programming classes especially, plagiarism can be hard to detect as source codes' appearance can be easily modified without changing the intent through simple formatting changes or refactoring. Many source code plagiarism tools do not support a high number of languages because doing so requires maintaining too large of a codebase. It is also difficult to add support for new languages because each language can be vastly different syntactically. Tools that are more extensible often do so by reducing the features of a language that are encoded and end up closer to text comparison tools than structurally aware program analysis tools [27]. This paper introduces a new tool called Kitsune, a plagiarism detection tool, focused on syntactically and structurally aware yet adaptable plagiarism detection. Kitsune has been evaluated for 10 of the languages in the Antlr4 grammar repository with success and could easily be extended to support all the grammars currently developed by Antlr4 or future grammars which are developed as new languages are written.",
keywords = "adaptable, plagiarism detection tools, structurally aware",
author = "Zachary Monroe and Ajay Bansal",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Frontiers in Education Conference, FIE 2021 ; Conference date: 13-10-2021 Through 16-10-2021",
year = "2021",
doi = "10.1109/FIE49875.2021.9637364",
language = "English (US)",
series = "Proceedings - Frontiers in Education Conference, FIE",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - 2021 IEEE Frontiers in Education Conference, FIE 2021",
}