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Applied Cryptography in Computer and Communications. First EAI International Conference, AC3 2021, Virtual Event, May 15-16, 2021, Proceedings

Research Article

A Novel Approach for Code Smells Detection Based on Deep Learning

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  • @INPROCEEDINGS{10.1007/978-3-030-80851-8_12,
        author={Tao Lin and Xue Fu and Fu Chen and Luqun Li},
        title={A Novel Approach for Code Smells Detection Based on Deep Learning},
        proceedings={Applied Cryptography in Computer and Communications. First EAI International Conference, AC3 2021, Virtual Event, May 15-16, 2021, Proceedings},
        proceedings_a={AC3},
        year={2021},
        month={7},
        keywords={Code smells Deep learning Convolutional neural network},
        doi={10.1007/978-3-030-80851-8_12}
    }
    
  • Tao Lin
    Xue Fu
    Fu Chen
    Luqun Li
    Year: 2021
    A Novel Approach for Code Smells Detection Based on Deep Learning
    AC3
    Springer
    DOI: 10.1007/978-3-030-80851-8_12
Tao Lin1,*, Xue Fu, Fu Chen, Luqun Li
  • 1: Amazon, Seattle
*Contact email: paper@Ltao.org

Abstract

Compared to software bugs, code smells are more significant in software engineering research. It is not easy to detect code smells through traditional methods. In this work, we propose a novel code smells detection approach based on deep learning. The experiments show that our work achieves high scores in terms of F2 score.

Keywords
Code smells Deep learning Convolutional neural network
Published
2021-07-05
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-80851-8_12
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