Automatic Detection of Source Code Plagiarism in Programming Courses

Sammanfattning: Source code plagiarism is an ongoing problem in programming courses at higher academic institutions. For this reason, different automated source code plagiarism detection tools have been developed. However, they require several manual steps before the submissions can be compared. Linnaeus University uses GitLab to handle their students’ code-related assignments but lacks an integrated workflow for checking submissions against plagiarism. Instead, Linnaeus University’s plagiarism-checking process is done manually, which is a challenging and time-consuming process. This thesis is a case study on Linnaeus University, focusing on integrating one of the plagiarism detection tools with GitLab using Continuous integration pipelines. The objectives have been to collect students’ submissions, communicate with the plagiarism tool, and visually present the results within GitLab. The prototype has been evaluated by a set of manually created submissions with different levels of plagiarism to ensure that the detection tool differentiates plagiarized and non-plagiarized submissions. Teachers at Linnaeus University have tested the workflow and reasoned whether the prototype fulfills their requirements.