YAP3: improved detection of similarities in computer program and other texts
SIGCSE '96 Proceedings of the twenty-seventh SIGCSE technical symposium on Computer science education
Software for detecting suspected plagiarism: comparing structure and attribute-counting systems
ACSE '96 Proceedings of the 1st Australasian conference on Computer science education
Software forensics: old methods for a new science
SEEP '96 Proceedings of the 1996 International Conference on Software Engineering: Education and Practice (SE:EP '96)
Similarity and originality in code: plagiarism and normal variation in student assignments
ACE '06 Proceedings of the 8th Australasian Conference on Computing Education - Volume 52
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Practical computing courses that involve significant amount of programming assessment tasks suffer from e-Plagiarism. A pragmatic solution for this problem could be by discouraging plagiarism particularly among the beginners in programming. One way to address this is to automate the detection of plagiarized work during the marking phase. Our research in this context involves at first examining various metrics used in plagiarism detection in program codes and secondly selecting an appropriate statistical measure using attribute counting metrics (ATMs) for detecting plagiarism in Java programming assignments. The goal of this investigation is to study the effectiveness of ATMs for detecting plagiarism among assignment submissions of introductory programming courses.