A comparison of machine learning algorithms on design smell detection using balanced and imbalanced dataset: A study of God class-Reference-Cited by-同舟云学术

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A comparison of machine learning algorithms on design smell detection using balanced and imbalanced dataset: A study of God class

Published:2022-03 Issue: Volume:143 Page:106736
ISSN:0950-5849
Container-title:Information and Software Technology
language:en
Short-container-title:Information and Software Technology

Author:

Alkharabsheh Khalid,Alawadi Sadi^ORCID,Kebande Victor R.,Crespo Yania^ORCID,Fernández-Delgado Manuel^ORCID,Taboada José A.^ORCID

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference66 articles.

1. Software design smell detection: a systematic mapping study;Alkharabsheh;Softw. Qual. J.,2018

2. Refactoring Planning for Design Smell Correction in Object-Oriented Software;Pérez,2011

3. AntiPatterns: Refactoring Software, Architectures, and Projects in Crisis;Brown,1998

4. Detecting defects in object oriented designs using design metrics;Choinzon,2006

5. A metric-based approach for anti-pattern detection in UML designs;Fourati;Comput. Inf. Sci.,2011

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

5. Prioritizing God Class Code Smells in Object-Oriented Software Using Fuzzy Inference System;Arabian Journal for Science and Engineering;2024-03-05

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