Shared information and program plagiarism detection

Abstract—A fundamental question in information theory and in com-puter science is how to measure similarity or the amount of shared in-formation between two sequences. We have proposed a metric, based on Kolmogorov complexity, to answer this question and have proven it to be universal. We apply this metric in measuring the amount of shared infor-mation between two computer programs, to enable plagiarism detection. We have designed and implemented a practical system SID (Software In-tegrity Diagnosis system) that approximates this metric by a heuristic com-pression algorithm. Experimental results demonstrate that SID has clear advantages over other plagiarism detection systems. SID system server is online a