Show simple item record

dc.contributor.authorBin Wang
dc.contributor.authorXiaochun Yang
dc.contributor.authorGuoren Wang
dc.date.accessioned2019-10-24T04:46:43Z
dc.date.available2019-10-24T04:46:43Z
dc.date.created2017-01-05 01:09
dc.date.issued2015
dc.identifieroai:hindawi.com:10.1155/2015/793697
dc.identifierhttp://dx.doi.org/10.1155/2015/793697
dc.identifier.urihttp://hdl.handle.net/20.500.12424/853915
dc.description.abstractBecause of the complexity of software development, some software developers may plagiarize source code from other projects or open source software in order to shorten development cycle. Many methods have been proposed to detect plagiarism among programs based on the program dependence graph, a graph representation of a program. However, to our best knowledge, existing works only detect similarity between programs without detecting copy direction among them. By employing extreme learning machine (ELM), we construct feature space for describing features of every two programs with possible plagiarism relationship. Such feature space could be large and time consuming, so we propose approaches to construct a small feature space by pruning isolated control statements and removable statements from each program to accelerate both training and classification time. We also analyze the features of data dependencies between any original program and its copy program, and based on it we propose a feedback framework to find a good feature space that can achieve both accuracy and efficiency. We conducted a thorough experimental study of this technique on real C programs collected from the Internet. The experimental results show the high accuracy and efficiency of our ELM-based approaches.
dc.languageen
dc.language.isoeng
dc.publisherMathematical Problems in Engineering
dc.rightsCopyright © 2015 Bin Wang et al.
dc.titleDetecting Copy Directions among Programs Using Extreme Learning Machines
dc.typeResearch Article
ge.collectioncodeOAIDATA
ge.dataimportlabelOAI metadata object
ge.identifier.legacyglobethics:10451859
ge.identifier.permalinkhttps://www.globethics.net/gel/10451859
ge.lastmodificationdate2017-01-05 01:09
ge.lastmodificationuseradmin@pointsoftware.ch (import)
ge.submissions0
ge.oai.exportid148934
ge.oai.repositoryid1261
ge.oai.streamid2
ge.setnameGlobeEthicsLib
ge.setspecglobeethicslib
ge.linkhttps://dx.doi.org/10.1155/2015/793697


This item appears in the following Collection(s)

Show simple item record