Existing source code plagiarism systems focus on the problem of identifying plagiarism between pairs of submissions. The task of detection, while essential, is only a small part of managing plagiarism in an instructional setting. Holistic plagiarism detection and management requires coordination and sharing of assignment similarity — elevating plagiarism detection from pairwise similarity to cluster-based similarity; from a single assignment to a sequence of assignments in the same course, and even among instructors of different courses. To address these shortcomings, we have developed Student Submissions Integrity Diagnosis (SSID), an open-source system that provides holistic plagiarism detection in an instructor-centric way.
- Jonathan Y. H. Poon (Alumni Undergraduate Student)
- [insert_php] echo get_avatar( $id_or_email=’firstname.lastname@example.org’, $size=30 ); [/insert_php] Kazunari Sugiyama (Advisor and Professor)
- Yee Fan Tan (Alumni Graduate Student)
- Jesse Gozali (Alumni Graduate Student)
- Jun-Ping Ng (Alumni Graduate Student)
- [insert_php] echo get_avatar( $id_or_email=’email@example.com’, $size=30 ); [/insert_php] Min-Yen Kan (Advisor and Professor)