Dolos 2.0: Towards Seamless Source Code Plagiarism Detection in Online Learning Environments

Abstract

With the increasing demand for programming skills comes a trend towards more online programming courses and assessments. While this allows educators to teach larger groups of students, it also opens the door to dishonest student behaviour, such as copying code from other students. When teachers use assignments where all students write code for the same problem, source code similarity tools can help to combat plagiarism. Unfortunately, teachers often do not use these tools to prevent such behaviour. In response to this challenge, we have developed a new source code plagiarism detection tool named Dolos. Dolos is open-source, supports a wide range of programming languages, and is designed to be user-friendly. It enables teachers to detect, prove and prevent plagiarism in programming courses by using fast algorithms and powerful visualisations. We present further enhancements to Dolos and discuss how it can be integrated into modern computing education courses to meet the challenges of online learning and assessment. By lowering the barriers for teachers to detect, prove and prevent plagiarism in programming courses, Dolos can help protect academic integrity and ensure that students earn their grades honestly.