Napredna pretraga

Pregled bibliografske jedinice broj: 1007817

Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review


Novak, Matija; Joy, Mike; Kermek, Dragutin
Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review // ACM Transactions on Computing Education, 19 (2019), 3; 27, 37 doi:10.1145/3313290 (međunarodna recenzija, pregledni rad, znanstveni)


Naslov
Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review

Autori
Novak, Matija ; Joy, Mike ; Kermek, Dragutin

Izvornik
ACM Transactions on Computing Education (1946-6226) 19 (2019), 3; 27, 37

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni

Ključne riječi
Source-code, academia, detection, education, plagiarism, programming, similarity, systematic review

Sažetak
Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some classes. Students who cheat often try to hide their plagiarism (obfuscate), and many different similarity detection engines (often called plagiarism detection tools) have been built to help teachers. This article focuses only on plagiarism detection and presents a detailed systematic review of the field of source-code plagiarism detection in academia. This review gives an overview of definitions of plagiarism, plagiarism detection tools, comparison metrics, obfuscation methods, datasets used for comparison, and algorithm types. Perspectives on the meaning of source-code plagiarism detection in academia are presented, together with categorisations of the available detection tools and analyses of their effectiveness. While writing the review, some interesting insights have been found about metrics and datasets for quantitative tool comparison and categorisation of detection algorithms. Also, existing obfuscation methods classifications have been expanded together with a new definition of “source-code plagiarism detection in academia."

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove
Fakultet organizacije i informatike, Varaždin,
Sveučilište u Zagrebu

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati