Cross-Language Source Code Plagiarism Detection using Explicit Semantic Analysis and Scored Greedy String Tilling

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F20%3A43918181" target="_blank" >RIV/62156489:43110/20:43918181 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1145/3383583.3398594" target="_blank" >https://doi.org/10.1145/3383583.3398594</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3383583.3398594" target="_blank" >10.1145/3383583.3398594</a>

Result language
angličtina
Original language name
Cross-Language Source Code Plagiarism Detection using Explicit Semantic Analysis and Scored Greedy String Tilling
Original language description
We present a method for source code plagiarism detection that is independent of the programming language. Our method EsaGst combines Explicit Semantic Analysis and Greedy String Tiling. Using 25 cases of source code plagiarism in C++, Java, JavaScript, PHP, and Python, we show that EsaGst outperforms a baseline method in identifying plagiarism across programming languages.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020 (JCDL '20)
ISBN
978-1-4503-7585-6
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
523-524
Publisher name
Association for Computing Machinery (ACM)
Place of publication
New York
Event location
Wu-chan
Event date
Aug 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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