Plagiarism Detection in Software Using Efficient String Matching

dc.authorscopusid 55247484300
dc.authorscopusid 23097406900
dc.authorscopusid 56962766700
dc.authorscopusid 57191422092
dc.contributor.author Pandey,K.L.
dc.contributor.author Agarwal,S.
dc.contributor.author Misra,S.
dc.contributor.author Prasad,R.
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T15:43:51Z
dc.date.available 2024-07-05T15:43:51Z
dc.date.issued 2012
dc.department Atılım University en_US
dc.department-temp Pandey K.L., Ewing Christian College, Allahabad, India; Agarwal S., Motilal Nehru National Institute of Technology, Allahabad, India; Misra S., Atilim University, Ankara, Turkey; Prasad R., Ajay Kumar Garg Engineering College, Ghaziabad, India en_US
dc.description 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) en_US
dc.description.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. en_US
dc.identifier.citationcount 1
dc.identifier.doi 10.1007/978-3-642-31128-4_11
dc.identifier.endpage 156 en_US
dc.identifier.isbn 978-364231127-7
dc.identifier.issn 1611-3349
dc.identifier.issue PART 4 en_US
dc.identifier.scopus 2-s2.0-84863930600
dc.identifier.startpage 147 en_US
dc.identifier.uri https://doi.org/10.1007/978-3-642-31128-4_11
dc.identifier.uri https://hdl.handle.net/20.500.14411/3677
dc.identifier.volume 7336 LNCS en_US
dc.institutionauthor Mısra, Sanjay
dc.language.iso en en_US
dc.relation.ispartof 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 en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 1
dc.subject bad character shift en_US
dc.subject parameterized matching and RGF en_US
dc.subject plagiarism detection en_US
dc.subject String matching en_US
dc.title Plagiarism Detection in Software Using Efficient String Matching en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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