Review of Plagiarism Detection Technique in Source Code

Pandit, Anala A.; Toksha, Gaurav

doi:10.1007/978-981-15-0633-8_38

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…Also, the Fast Plagiarism Detection Technique (FPDS) [42] aims to increase the algorithmic efficiency of plagiarism detection by storing input collection files in a specific indexed data structure. Document Fingerprinting: One commonly used strategy for plagiarism detection is based on N-Grams [43]. This approach converts each string or sentence into numerical representations to amplify their differences.…”

Section: Implementation Strategies and Proposed Integration Approachmentioning

confidence: 99%

Automated Detection Approaches for Source Code Plagiarism in Students' Submissions

Eliwa

Essam

Mohamed

et al. 2023

Journal of Computing and Communication

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Code plagiarism is a significant concern in software development, as it compromises the integrity of original work and can lead to ethical and legal consequences. The need for effective plagiarism detection techniques has grown in parallel with the rise in online coding resources and collaborative platforms. The paper analyses existing plagiarism detection tools, comparing their characteristics, functions, and development timelines. Emphasis is placed on essential factors such as additional case detection, direct display of matched pairings, and compatibility with multiple programming languages. By examining these features, educators and software developers can decide which tools best suit their needs. Additionally, the paper explores various plagiarism detection techniques, including attribute counting, content comparison, string tiling, and parse tree comparison. The advantages and limitations of each method are examined, underscoring the need for continuous improvement and innovation in the field. This paper presents the most widely available plagiarism detection tools that can be seamlessly integrated into learning management systems. In conclusion, the paper highlights critical areas for future research and development in plagiarism detection. These include the integration of plagiarism detection with live learning management systems to streamline the process for educators and students, the enhancement of usability and user experience in plagiarism detection tools to facilitate their adoption, the advancement of detection algorithms to improve accuracy, and the support for multi-language and crosslanguage comparisons to cater to diverse programming environments.

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Section: Implementation Strategies and Proposed Integration Approachmentioning

confidence: 99%

Automated Detection Approaches for Source Code Plagiarism in Students' Submissions

Eliwa

Essam

Mohamed

et al. 2023

Journal of Computing and Communication

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show abstract

“…Pandit and Toksha [12] have said that future directions in the field are towards machine learning use in plagiarism detection which is a promising direction for improving source code plagiarism detection.…”

Section: A Source Code Plagiarism Detectionmentioning

confidence: 99%

Clone Detection Techniques for JavaScript and Language Independence: Review

Alfageh¹,

Alhakami²,

Baz³

et al. 2020

IJACSA

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Code clone detection is an active field of study in computer science. Despite its rich history, it lacks focus on web scripting languages. Due to the expansion of web applications and web development amongst developers of varying education and experience levels, they inevitably resort to cloning through out the web. The spread of code clones is further increased by websites like StackOverflow and GitHub. In this paper, we will be focusing on clone detection research done to target clones in JavaScript code and discuss its areas of concern. Also, we will summarize language independent research done and possibility of its application on JavaScript and web applications.

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“…The act of acquiring programming skills is typically a result of practical experience gained through constant practice and the successful completion of assignments given by lecturers [5]. Each assignment is manually checked to ensure that no students engaged in code plagiarism, although it is time-consuming and challenging [6]. According to interviews with the lecturer, it takes approximately one to two hours to assess relatively 20 assignments.…”

Section: Introductionmentioning

confidence: 99%

Damerau-Levenshtein Distance Algorithm Based on Abstract Syntax Tree to Detect Code Plagiarism

Nuraminah,

Ammar

2023

SJI

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Purpose: This research aimed to detect source code plagiarism based on Abstract Syntax Tree using Damerau-Levenshtein Distance algorithm, which is expected to streamline the inaccuracies and time-consumption associated with the manual process.Methods: Damerau-Levenshtein Distance algorithm was used to determine the similarity between source code files and calculate F-Measure. The dataset, which consisted of 178 source code files from 20 coursework assignments, was obtained from GitHub by Lawton Nichols in 2019. Damerau-Levenshtein Distance algorithm was used to compute the minimum cost required to transform one line of code into another. Furthermore, ANTLR detected AST, which was processed through preprocessing, including node pruning, function and variable sorting, and log output removal. Result: The result showed that the two methods took 5.704 seconds and 0.996 seconds to complete. The lowest and highest values obtained using F-Measure were 0.16 and 0.8, respectively. Therefore, the system performed detection processes quickly and effectively detected common forms of code plagiarism with difficulty in the more complex forms. Novelty: In conclusion, this research used AST and Damerau-Levenshtein Distance algorithm to calculate the 5 levels of similarity in Java programming language source code. For further development, preprocessing steps were needed to prune unnecessary nodes and detect equivalent but differently syntaxed code.

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Review of Plagiarism Detection Technique in Source Code

Cited by 7 publications

References 14 publications

Automated Detection Approaches for Source Code Plagiarism in Students' Submissions

Automated Detection Approaches for Source Code Plagiarism in Students' Submissions

Clone Detection Techniques for JavaScript and Language Independence: Review

Damerau-Levenshtein Distance Algorithm Based on Abstract Syntax Tree to Detect Code Plagiarism

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