Plagiarism detection based on blinded logical test automation results and detection of textual similarity between source codes

Abstract

This Research to Practice Full Paper presents in this paper. Finding logical errors is the most difficult skill for students from all sorts of disciplines that involve computer programming. Unfortunately, because of this difficulty, some students resort to plagiarism. Plagiarism corrupts the evaluation process. Several tools are used in different researches for this purpose. Recent research has defined a taxonomy of the most relevant types of plagiarism that can be found in source codes. The Hybrid Framework was made to map the student plagiarisms using NLP tecnhics and software test automation techniques for automatic exercise correction with tools available for this purpose. This framework has been tested in the laboratory with promising results.