Examining deep learning’s capability to spot code smells: a systematic literature review
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-023-04144-1.pdf
Reference81 articles.
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3. Li, Z., Wang, S., Wang, W., Liang, P., Mo, R., Li, B.: Understanding bugs in multi-language deep learning frameworks, (2023). arXiv:2303.02695
4. Al Khatib, S.M., Alkharabsheh, K., Alawadi, S.: Selection of human evaluators for design smell detection using dragonfly optimization algorithm: An empirical study. Inform. Softw. Technol. 155, 107120 (2023)
5. Kim, D.K.: A deep neural network-based approach to finding similar code segments. IEICE TRANSACTIONS Inform. Syst. 103, 874–878 (2020)
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1. Data preparation for Deep Learning based Code Smell Detection: A systematic literature review;Journal of Systems and Software;2024-10
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