Análise de plágio em código fonte usando similaridade de sinal 1D

Abstract

Source code plagiarism is a recurring issue in academia, and its manual detection is a highly time-consuming task due to the large volume of assignments in programming courses. To address this, this study proposes an approach to measuring similarity between source codes using signal processing techniques, treating them as one-dimensional signals. The hypothesis is that this approach may be more resistant to obfuscation techniques than conventional methods. Three approaches were explored: time-domain analysis, Fourier Transform, and Wavelet Transform. The applied metrics were evaluated on datasets containing previously identified cases of plagiarism and compared with the MOSS and JPlag tools. The results indicate that time-domain analysis, particularly with Dynamic Time Warping (DTW) distance and Pearson correlation, was the most effective in identifying plagiarism, achieving performance comparable to traditional tools.