The popularity of Python programming has seen some dramatic surge over the recent years. This rise in its popularity can be attributed to reasons such as the simplified syntax, high productivity compared to programming languages like C++ and Java, and the fact that it requires less effort, time and lines of code to perform the same operations than in other programming languages. Python is also very famous for its English-like commands and easy code readability that make learning coding a lot more easy and efficient, especially for beginners and newcomers. As a result, naturally, the popularity of Python at universities and colleges has also grown rapidly.
With an increasing number of students pursuing courses in Python, it has become further important to maintain academic integrity in these assignments. Detecting plagiarism is important not just to avoid having duplicated content or ideas from others’ work but also to encourage students to learn, practice and test their own programming skills and submit original content. While it is impractical to manually perform plagiarism checks in multiple student submissions, we see that often teachers find the use of separate tools cumbersome. Having to manually copy and paste source code and parse results to another tool often only increases an already huge workload of teachers. Because of this, checking for plagiarism is often skipped by the teacher because it simply takes too much time.