Preventing Automatic Code Plagiarism Generation Through Token String Normalization: Unterschied zwischen den Versionen
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|vortragstyp=Bachelorarbeit | |vortragstyp=Bachelorarbeit | ||
|betreuer=Timur Sağlam | |betreuer=Timur Sağlam | ||
|termin=Institutsseminar/2023-05-05 | |termin=Institutsseminar/2023-05-05 | ||
|vortragsmodus=in Präsenz | |vortragsmodus=in Präsenz | ||
|kurzfassung=Code plagiarism is a significant problem in computer science education. Token-based plagiarism detectors, which represent the state-of-the-art in code plagiarism detection, excel at identifying manually plagiarized submissions. Unfortunately, they are vulnerable to automatic plagiarism generation, particularly when statements are inserted or reordered. Therefore, this thesis introduces token string normalization, which makes the results of token-based plagiarism detectors invariant to statement insertion and reordering. It inher- its token-based plagiarism detectors’ high language independence and utilizes a program graph. We integrate token string normalization into the state-of-the-art token-based plagiarism detector JPlag. We show that this prevents automatic plagiarism generation using statement insertion and reordering. Additionally, we confirm that JPlag’s existing capabilities are retained. | |kurzfassung=Code plagiarism is a significant problem in computer science education. Token-based plagiarism detectors, which represent the state-of-the-art in code plagiarism detection, excel at identifying manually plagiarized submissions. Unfortunately, they are vulnerable to automatic plagiarism generation, particularly when statements are inserted or reordered. Therefore, this thesis introduces token string normalization, which makes the results of token-based plagiarism detectors invariant to statement insertion and reordering. It inher- its token-based plagiarism detectors’ high language independence and utilizes a program graph. We integrate token string normalization into the state-of-the-art token-based plagiarism detector JPlag. We show that this prevents automatic plagiarism generation using statement insertion and reordering. Additionally, we confirm that JPlag’s existing capabilities are retained. | ||
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Aktuelle Version vom 28. April 2023, 13:54 Uhr
Vortragende(r) | Moritz Brödel | |
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Vortragstyp | Bachelorarbeit | |
Betreuer(in) | Timur Sağlam | |
Termin | Fr 5. Mai 2023 | |
Vortragsmodus | in Präsenz | |
Kurzfassung | Code plagiarism is a significant problem in computer science education. Token-based plagiarism detectors, which represent the state-of-the-art in code plagiarism detection, excel at identifying manually plagiarized submissions. Unfortunately, they are vulnerable to automatic plagiarism generation, particularly when statements are inserted or reordered. Therefore, this thesis introduces token string normalization, which makes the results of token-based plagiarism detectors invariant to statement insertion and reordering. It inher- its token-based plagiarism detectors’ high language independence and utilizes a program graph. We integrate token string normalization into the state-of-the-art token-based plagiarism detector JPlag. We show that this prevents automatic plagiarism generation using statement insertion and reordering. Additionally, we confirm that JPlag’s existing capabilities are retained. |