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Pregled bibliografske jedinice broj: 1237061

Using graph databases in source code plagiarism detection


Novak, Matija; Levak, Iva
Using graph databases in source code plagiarism detection // Proceedings of Central European Conference on Information and Intelligent Systems / Vrček, Neven ; Guàrdia, Lourdes ; Grd, Petra (ur.).
Varaždin: Faculty of Ogranization and Informatics, 2022. str. 465-470 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Using graph databases in source code plagiarism detection

Autori
Novak, Matija ; Levak, Iva

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of Central European Conference on Information and Intelligent Systems / Vrček, Neven ; Guàrdia, Lourdes ; Grd, Petra - Varaždin : Faculty of Ogranization and Informatics, 2022, 465-470

Skup
Central European Conference on Information and Intelligent Systems

Mjesto i datum
Dubrovnik, Croatia, 23.01.2023

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
plagiarism, graph databases, similarity detection

Sažetak
Modern plagiarism detection tools calculate the percentage of the similarity between two given source code files. In academia, the process of checking for potential plagiarized students solutions can be challenging in terms of resources due to the large number of combinations between many students. In such conditions, the reliability of plagiarism detection tools may be put to risk. Every plagiarism detection tool produces a similarity report as files containing the results of the analysis for each pair of analyzed source code files. While such a report is useful for a one-time checking, sometimes it is needed to store the result data for future use. In our previous work, the results were stored in a relational database and a list of relevant queries was defined for meaningful analysis. Nevertheless, the large number of pair-wise impacts the storage and query execution speeds. In this paper, we present a solution to this problem by importing the similarity analysis data into a graph database and evaluate the difference in the query execution speed between a graph and a relational database.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet organizacije i informatike, Varaždin,
Sveučilište u Zagrebu

Profili:

Avatar Url Iva Levak (autor)

Avatar Url Matija Novak (autor)

Poveznice na cjeloviti tekst rada:

archive.ceciis.foi.hr www.proquest.com

Citiraj ovu publikaciju:

Novak, Matija; Levak, Iva
Using graph databases in source code plagiarism detection // Proceedings of Central European Conference on Information and Intelligent Systems / Vrček, Neven ; Guàrdia, Lourdes ; Grd, Petra (ur.).
Varaždin: Faculty of Ogranization and Informatics, 2022. str. 465-470 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Novak, M. & Levak, I. (2022) Using graph databases in source code plagiarism detection. U: Vrček, N., Guàrdia, L. & Grd, P. (ur.)Proceedings of Central European Conference on Information and Intelligent Systems.
@article{article, author = {Novak, Matija and Levak, Iva}, year = {2022}, pages = {465-470}, keywords = {plagiarism, graph databases, similarity detection}, title = {Using graph databases in source code plagiarism detection}, keyword = {plagiarism, graph databases, similarity detection}, publisher = {Faculty of Ogranization and Informatics}, publisherplace = {Dubrovnik, Croatia} }
@article{article, author = {Novak, Matija and Levak, Iva}, year = {2022}, pages = {465-470}, keywords = {plagiarism, graph databases, similarity detection}, title = {Using graph databases in source code plagiarism detection}, keyword = {plagiarism, graph databases, similarity detection}, publisher = {Faculty of Ogranization and Informatics}, publisherplace = {Dubrovnik, Croatia} }




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