With computer-related courses becoming an integral part of modern education, being able to detect the originality of code is growing more important.
Unlike common paper plagiarism, source code plagiarism is much easier to commit yet difficult to detect. Most of the existing plagiarism detection tools fail to accurately identify similarities concealed within plagiarized code due to poorly adopted algorithms. These tools are also usually difficult to launch, have bulky interfaces, and provide illegible results. All of these factors make a code plagiarism detector an obstacle rather than a helper.
In response to these issues, Unicheck has launched an AI-driven, fast, and easy-to-use solution. Its algorithms operate based on the peculiarities of source code and thus allow to understand it exactly the way computers do.
How does the Unicheck code plagiarism detection tool work?
Since code plagiarism usually occurs in the classroom setting, with students copying each other’s works, Unicheck was designed to process the Python submissions and compare them to one another. This way, the instructor can either compare two submissions side by side or analyze the work of the entire course.
The algorithm differentiates between variables and their values, commentaries and code segments, and long string values and commands. It’s also familiar with programming language specific keywords and built-in functions.
All in all, this revolutionary, AI-based algorithm allows for achieving perfect quality and impressive performance in checking student assignments.
Unicheck’s source code plagiarism detection tool is in the early stages of testing and will soon be available for usage in educational institutions. To find out the details and to have your questions answered, contact us at firstname.lastname@example.org.