Applied Sciences (Oct 2023)

Review of Code Similarity and Plagiarism Detection Research Studies

  • Gunwoo Lee,
  • Jindae Kim,
  • Myung-seok Choi,
  • Rae-Young Jang,
  • Ryong Lee

DOI
https://doi.org/10.3390/app132011358
Journal volume & issue
Vol. 13, no. 20
p. 11358

Abstract

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The foundational technique of code similarity detection, which underpins plagiarism detection tools, has already reached a level of maturity where it can be effectively employed for practical applications, demonstrating commendable performance. However, although the understanding of code clones—referred to as similar codes—has evolved, there has been a noticeable decline in the emergence of novel proposals for code similarity detection techniques. The landscape of code similarity detection techniques is diverse and can be divided based on how codes are represented. Each method, designed to cater to different types of detectable code similarity instances, has distinct advantages and drawbacks. Therefore, the selection of an appropriate method is crucial and is contingent on the specific objectives of the analysis. This paper provides a comprehensive exploration of code similarity detection techniques and illuminates the prevailing trends in plagiarism detection research. It acquaints readers with a spectrum of distinct code similarity detection methods, accompanied by the requisite contextual background knowledge. Additionally, it presents a detailed overview of the trajectory of research trends in plagiarism detection.

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