Plagiarism Detection in Software Using Efficient String Matching

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2012

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Computer Engineering
(1998)
The Atılım University Department of Computer Engineering was founded in 1998. The department curriculum is prepared in a way that meets the demands for knowledge and skills after graduation, and is subject to periodical reviews and updates in line with international standards. Our Department offers education in many fields of expertise, such as software development, hardware systems, data structures, computer networks, artificial intelligence, machine learning, image processing, natural language processing, object based design, information security, and cloud computing. The education offered by our department is based on practical approaches, with modern laboratories, projects and internship programs. The undergraduate program at our department was accredited in 2014 by the Association of Evaluation and Accreditation of Engineering Programs (MÜDEK) and was granted the label EUR-ACE, valid through Europe. In addition to the undergraduate program, our department offers thesis or non-thesis graduate degree programs (MS).

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Abstract

String matching refers to the problem of finding occurrence(s) of a pattern string within another string or body of a text. It plays a vital role in plagiarism detection in software codes, where it is required to identify similar program in a large populations. String matching has been used as a tool in a software metrics, which is used to measure the quality of software development process. In the recent years, many algorithms exist for solving the string matching problem. Among them, Berry-Ravindran algorithm was found to be fairly efficient. Further refinement of this algorithm is made in TVSBS and SSABS algorithms. However, these algorithms do not give the best possible shift in the search phase. In this paper, we propose an algorithm which gives the best possible shift in the search phase and is faster than the previously known algorithms. This algorithm behaves like Berry-Ravindran in the worst case. Further extension of this algorithm has been made for parameterized string matching which is able to detect plagiarism in a software code. © 2012 Springer-Verlag.

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Universidade Federal da Bahia (UFBA); Universidade Federal do Reconcavo da Bahia (UFRB); Universidade Estadual de Feira de Santana (UEFS); University of Perugia; University of Basilicata (UB)

Keywords

bad character shift, parameterized matching and RGF, plagiarism detection, String matching

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1

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 12th International Conference on Computational Science and Its Applications, ICCSA 2012 -- 18 June 2012 through 21 June 2012 -- Salvador de Bahia -- 90945

Volume

7336 LNCS

Issue

PART 4

Start Page

147

End Page

156

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