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Prism: Decomposing Program Semantics for Code Clone Detection Through Compilation
International Conference on Software EngineeringCode clone detection (CCD) is of critical importance in software engineering, while semantic similarity is a key evaluation factor for CCD. The embedding technique, which represents an object using a numerical vector, is utilized to generate code ...
Haoran Li +5 more
semanticscholar +1 more source
BinClone: Detecting Code Clones in Malware
2014 Eighth International Conference on Software Security and Reliability, 2014To gain an in-depth understanding of the behaviour of a malware, reverse engineers have to disassemble the malware, analyze the resulting assembly code, and then archive the commented assembly code in a malware repository for future reference. In this paper, we have developed an assembly code clone detection system called Bin Clone to identify the code
Mohammad Reza Farhadi +3 more
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Improving Accuracy of LLM-based Code Clone Detection U sing Functionally Equivalent Methods
International Conference on Software Engineering Research and ApplicationsAvstract-A code clone is a code snippet identical or similar to another in the source code. The presence of code clones causes the spread of bugs, which means that efficient code clone detection and appropriate refactoring are necessary.
Ryutaro Inoue, Yoshiki Higo
semanticscholar +1 more source
Detecting code clones in binary executables
Proceedings of the eighteenth international symposium on Software testing and analysis, 2009Large software projects contain significant code duplication, mainly due to copying and pasting code. Many techniques have been developed to identify duplicated code to enable applications such as refactoring, detecting bugs, and protecting intellectual property.
Andreas Sæbjørnsen +4 more
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Code clone detection experience at microsoft
Proceedings of the 5th International Workshop on Software Clones, 2011Cloning source code is a common practice in the software development process. In general, the number of code clones increases in proportion to the growth of the code base. It is challenging to proactively keep clones consistent and remove unnecessary clones during the entire software development process of large-scale commercial software.
Yingnong Dang +3 more
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LLVM-based code clone detection framework
2015 Computer Science and Information Technologies (CSIT), 2015Existed methods of code clones detection have some restrictions. Textual and lexical approaches cannot detect strongly modified fragments of code. Syntactic and metrics based approaches detect strong modifications with low accuracy. On the contrary, semantic approach accurately detects the cloned fragments of code with small changes as well as the ...
Arutyun Avetisyan +4 more
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Cross-language Source Code Clone Detection Based On Graph Neural Network
Proceedings of the 2024 3rd International Conference on Cryptography, Network Security and Communication TechnologyCode clone detection has important applications in the security field, including vulnerability mining and recovery, malware detection, and copyright protection.
Yuguo Zhang, Jia Yang, Ou Ruan
semanticscholar +1 more source
AST-path Based Compare-Aggregate Network for Code Clone Detection
IEEE International Joint Conference on Neural Network, 2021Code clone detection remains one of the main challenges in maintaining software projects. Recently, state-of-the-art researches have shown that neural models based on abstract syntax trees (ASTs) can better represent code fragment. However, existing tree-
Hongliang Liang, Lu Ai
semanticscholar +1 more source
The Struggles of LLMs in Cross-Lingual Code Clone Detection
Proc. ACM Softw. Eng.With the involvement of multiple programming languages in modern software development, cross-lingual code clone detection has gained traction within the software engineering community.
Micheline B'en'edicte Moumoula +3 more
semanticscholar +1 more source
IEEE Transactions on Software Engineering
In various research domains, artificial intelligence (AI) has gained significant prominence, leading to the development of numerous learning-based models in research laboratories, which are evaluated using benchmark datasets. While the models proposed in
Yanming Yang +6 more
semanticscholar +1 more source
In various research domains, artificial intelligence (AI) has gained significant prominence, leading to the development of numerous learning-based models in research laboratories, which are evaluated using benchmark datasets. While the models proposed in
Yanming Yang +6 more
semanticscholar +1 more source

