SourcePlag - Source Code Plagiarism Detection Based on Abstract Syntax Trees
Code plagiarism poses a significant challenge in programming communities, necessitating effective detection mechanisms. This paper introduces a novel system that employs Abstract Syntax Trees (ASTs) for code representation and comparison. The system utilizes ASTs to capture the structural essence of code, facilitating a comprehensive analysis of code similarity, it offers flexibility for application across multiple programming languages. In addition to leveraging the Levenshtein Distance Algorithm for Python code comparison, the system incorporates node counting for other languages such as Java and C/C++. By integrating AST-based representation and a combination of comparison techniques, the system offers a robust solution for identifying plagiarized code instances accurately across various programming environments. Through a detailed exploration of the system's methodology, this paper underscores its potential to address the pervasive issue of code plagiarism in programming communities.
Authors
- Nakul Sharma (ORCID: https://orcid.org/0000-0003-3947-904X)
- Siddharth Shinde (ORCID: https://orcid.org/0000-0001-6236-9944)
- Siddhi A. Bhosale
- Sunil Patil
Institutions
- International Institute of Information Technology (IN)
Publication Details
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1109/icbds61829.2024.10837209
- Primary Topic
- Academic integrity and plagiarism
- Type
- article
- Field-Weighted Citation Impact
- 0.00