Search

Plagiarism is deemed a serious ethical offense. Without proper protection and accurate detection algorithms, the number of innovations would significantly dwindle, impeding the advancement of national research and education. Especially in programming courses, plagiarism is extremely common. Most students tend to do their homework in the simplest way: copying the source code of others. Such unpleasant issues must be addressed to preclude this misbehavior before it becomes students’ habit, and to promote positive attitudes in our juveniles. In this paper, we, propose an algorithm to identify original source codes, helping instructors to pinpoint whom to monitor and be able to set measures or correctly warn each wrong-doing student. This work introduces a rule, derived from a m+l evolutionary algorithm, for identifying which source codes are original. First, we run the maximum spanning tree algorithm to generate a phylogenetic tree, representing the relationships and sequences of plagiarisms. Then, we apply our proposed rule to identify the source and its copies, whose relations are represented by arrows’ directions. The experiment result shows that the proposed rule yields the accuracy of 90.24%. [ABSTRACT FROM AUTHOR]

Plagiarism is deemed a serious ethical offense. Without proper protection and accurate detection algorithms, the number of innovations would significantly dwindle, impeding the advancement of national research and education. Especially in programming courses, plagiarism is extremely common. Most students tend to do their homework in the simplest way: copying the source code of others. Such unpleasant issues must be addressed to preclude this misbehavior before it becomes students’ habit, and to promote positive attitudes in our juveniles. In this paper, we, propose an algorithm to identify original source codes, helping instructors to pinpoint whom to monitor and be able to set measures or correctly warn each wrong-doing student. This work introduces a rule, derived from a m+l evolutionary algorithm, for identifying which source codes are original. First, we run the maximum spanning tree algorithm to generate a phylogenetic tree, representing the relationships and sequences of plagiarisms.Then, we apply our proposed rule to identify the source and its copies, whose relations are represented by arrows’ directions. The experiment result shows that the proposed rule yields the accuracy of 90.24%.