
Research Article
A Novel Approach for Code Smells Detection Based on Deep Learning
2 downloads
@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
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.
Copyright © 2021–2025 ICST