View in EDS

A comparative study for language independent code clone detection.

Saved in:
Bibliographic Details
Title: A comparative study for language independent code clone detection.
Authors: Omer, Shahad S., Hammo, Asma'a Y.
Source: AIP Conference Proceedings; 2025, Vol. 3211 Issue 1, p1-9, 9p
Subject Terms: COMPUTER software development, C++, SYNTAX (Grammar), PYTHON programming language, ALGORITHMS
Abstract: Code clones are chunks of code that are identical or nearly identical to other pieces of code in the same or a separate codebase. Code clones are classified into four types: Type 1, Type 2, Type 3, and Type 4. Code clones can be troublesome for a variety of reasons, including: superfluous code, errors, and vulnerabilities. To address these challenges, Code Clone Detection (CCD) is required in software development to detect and control code clones. Text-based Approaches, Token-based Techniques, Abstract Syntax Tree (AST), Program Dependency Graph (PDG), and Hybrid-based Techniques are the most popular techniques for CCD. The goal of this research is to detect the code clone between programs written in any language (C++, C#, Java, Python). Because the syntax of those languages is different, five similarity algorithms are used. The algorithms are: Cosine similarity, Jaccard similarity, Longest Common Subsequence, Smith Waterman similarity, and Levenshtien similarity. The result shows that Cosine is the best algorithm while Jaccard is the worst one. [ABSTRACT FROM AUTHOR]
Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:Code clones are chunks of code that are identical or nearly identical to other pieces of code in the same or a separate codebase. Code clones are classified into four types: Type 1, Type 2, Type 3, and Type 4. Code clones can be troublesome for a variety of reasons, including: superfluous code, errors, and vulnerabilities. To address these challenges, Code Clone Detection (CCD) is required in software development to detect and control code clones. Text-based Approaches, Token-based Techniques, Abstract Syntax Tree (AST), Program Dependency Graph (PDG), and Hybrid-based Techniques are the most popular techniques for CCD. The goal of this research is to detect the code clone between programs written in any language (C++, C#, Java, Python). Because the syntax of those languages is different, five similarity algorithms are used. The algorithms are: Cosine similarity, Jaccard similarity, Longest Common Subsequence, Smith Waterman similarity, and Levenshtien similarity. The result shows that Cosine is the best algorithm while Jaccard is the worst one. [ABSTRACT FROM AUTHOR]
ISSN:0094243X
DOI:10.1063/5.0259558