Shared information and program plagiarism detection

Author

Chen, Xin ; Francia, Brent ; Li, Ming ; McKinnon, Brian ; Seker, Amit

Author_Institution

Dept. of Comput. Sci., Univ. of California, Riverside, CA, USA

Volume

50

Issue

7

fYear

2004

fDate

7/1/2004 12:00:00 AM

Firstpage

1545

Lastpage

1551

Abstract

A fundamental question in information theory and in computer science is how to measure similarity or the amount of shared information 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 information between two computer programs, to enable plagiarism detection. We have designed and implemented a practical system SID (Software Integrity Diagnosis system) that approximates this metric by a heuristic compression algorithm. Experimental results demonstrate that SID has clear advantages over other plagiarism detection systems. SID system server is online at http://software.bioinformatics.uwaterloo.ca/SID/.

Keywords

computational complexity; data compression; data integrity; heuristic programming; software metrics; Kolmogorov complexity; computer programs; heuristic compression algorithm; program plagiarism detection; shared information; software integrity diagnosis system; Algorithm design and analysis; Application software; Bioinformatics; Computer science; Genomics; Information theory; Internet; Phylogeny; Plagiarism; Programming profession;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/TIT.2004.830793

Filename

1306552