Fully automatic assessment of programming exercises
Proceedings of the 6th annual conference on Innovation and technology in computer science education
A tool that detects plagiarism in Pascal programs
SIGCSE '81 Proceedings of the twelfth SIGCSE technical symposium on Computer science education
EPCI: extracting potentially copyright infringement texts from the web
Proceedings of the 16th international conference on World Wide Web
The toolbox for local and global plagiarism detection
Computers & Education
Plagiarism Prevention by Logging Students' Paper-Writing Activities
Proceedings of the 2007 conference on Supporting Learning Flow through Integrative Technologies
Multilayer SOM with tree-structured data for efficient document retrieval and plagiarism detection
IEEE Transactions on Neural Networks
SimPaD: A word-similarity sentence-based plagiarism detection tool on Web documents
Web Intelligence and Agent Systems
Online plagiarism detection through exploiting lexical, syntactic, and semantic information
ACL '12 Proceedings of the ACL 2012 System Demonstrations
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Plagiarism of material from the Internet is a widespread and growing problem. Computer science students, and those in other science and engineering courses, can sometimes get away with a "cut and paste" approach to assembling a paper in part because the expected style of technical writing is less expositional than in liberal arts courses. Detection of cut and paste plagiarism is time-consuming when done by hand, and can be greatly aided by automated software tools. This paper reports on the design of a software tool called SNITCH that implements a fast and accurate plagiarism detection algorithm using the Google Web API. Issues related to plagiarism detection software are discussed and empirical results of a performance and accuracy study are presented.