Lichen: Customizable, Open Source Plagiarism Detection in Submitty

Prior education research, including Computer Science, has established that students will attempt to cheat and violate academic integrity, with one of the more common forms being code plagiarism. The majority of existing tools for software plagiarism are closed source, requiring instructors to use them in a prescribed configuration and sending student code to a third-party server for analysis. At the core of this analysis is the need to perform a language-specific tokenization of the input program and then to use "digital fingerprinting" on the code to identify significant markers. This has required developers to write their own parser for each supported language, which is time-consuming to create and keep up-to-date, and thus a barrier to creation of these tools. Instead we bootstrap new languages into our plagiarism system by leveraging the "Language Server Protocol", an initiative to create open-source parsers and tokenizers for many languages (principally to be used within a range of popular IDEs). In this poster, we present our work on Lichen, the open source plagiarism detection tool that is integrated into the Submitty course management platform we use at Rensselaer Polytechnic Institute. This tool is a pipeline of modules for the specific tasks of tokenizing, fingerprinting, and then comparing the fingerprints for any number of files. Through this, a similarity score is generated for pairs of files, and these are used to help instructors determine to what extent code plagiarism has occurred.