Experience report: Evaluating the effectiveness of decision trees for detecting code smells

Author:

Amorim Lucas,Costa Evandro,Antunes Nuno,Fonseca Baldoino,Ribeiro Marcio

Publisher

IEEE

Cited by 58 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. Optimizing beyond boundaries: empowering the salp swarm algorithm for global optimization and defective software module classification;Neural Computing and Applications;2024-07-31

2. Machine Learning-Based Methods for Code Smell Detection: A Survey;Applied Sciences;2024-07-15

3. Study of Code Smells: A Review and Research Agenda;International Journal of Mathematical, Engineering and Management Sciences;2024-06-01

4. An Exploratory Evaluation of Continuous Feedback to Enhance Machine Learning Code Smell Detection;Anais do XXVII Congresso Ibero-Americano em Engenharia de Software (CIbSE 2024);2024-05-06

5. Tuning Code Smell Prediction Models: A Replication Study;Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension;2024-04-15

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