A review-based comparative study of bad smell detection tools

Author:

Fernandes Eduardo1,Oliveira Johnatan1,Vale Gustavo1,Paiva Thanis1,Figueiredo Eduardo1

Affiliation:

1. Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil

Funder

Fundação de Amparo à Pesquisa do Estado de Minas Gerais

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

ACM

Cited by 104 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CBReT: A Cluster-Based Resampling Technique for dealing with imbalanced data in code smell prediction;Knowledge-Based Systems;2024-02

2. Code smell detection based on supervised learning models: A survey;Neurocomputing;2024-01

3. Deep Learning Based Feature Envy Detection Boosted by Real-World Examples;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

4. Do Bad Smells Lead to Defects?;2023 13th International Conference on Software Technology and Engineering (ICSTE);2023-10-27

5. Examining deep learning’s capability to spot code smells: a systematic literature review;Cluster Computing;2023-10-03

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