Source code plagiarism analysis and visualization for programming course
Abstract
The problem of unfair borrowing in the academic environment is still relevant. Unfair borrowing, or plagiarism, is found today in various forms of academic activity, ranging from semester papers of students to dissertations of scientists. The development of communications and the global nature of interaction have led to a wide availability of materials that are easy to copy. This leads to the fact that it becomes easier for students to find a solution than to compose it. A separate problem is the unfair borrowing in the
works of students of educational institutions, which they perform in the framework of practical programming courses. As in the case of text, it is possible to detect plagiarism manually only in the smallest subsamples of data. Fortunately, today there are quite a large number of systems that allow you to automatically identify the similarity of the source code. Moreover, there are tools that allow you to aggregate the results of the
search for plagiarism by several different systems, which also increases the likelihood of detecting cases of unfair borrowing. At the same time, the use of these tools is still not so widespread in educational institutions. This article describes the process of plagiarism analysis built for use in practical programming courses, as well as a tool for interactive graph visualization of the results of plagiarism analysis.
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