الفهرس Only 14 pages are availabe for public view
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Abstract
The thesis presents a new technique with different versions for clone detection using sequential pattern mining, titled EgyCD. We developed a clone detection technique based on Sequential Pattern Mining (Apriori-based). The thesis also presents a parallel and distributed data mining approach to code clone detection. EgyCD can detect three types of code clones, Type-I, Type-II and Type-III as well as detecting plagiarism. It aims to prove the value and importance of deploying parallel and distributed computing for real-time large scale code clone detection. Finally the thesis presented a new graph for the code clones detected by EgyCD, it submits a new way of representation in which it has no lines.