Code Smell Detection using Hybrid Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Code Smell Detection using Hybrid Machine Learning Algorithms

Published:2023-08-03 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA)
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Author:

Mahalakshmi D¹,Kasinathan Prabakaran²,Elangovan D.³,Bhat C. Rohith⁴,Balamurugan M⁵,Sivakumar S.⁶

Affiliation:

1. Panimalar Engineering College,Dept. of Information Technology

2. School of Computing, Veltech Rangarajan Dr. Sagunthula R & D Institute of Science and Technology,Dept. of CSE

3. Panimalar Engineering College,Dept. of CSE

4. Institute of computer science and engineering, Saveetha School of engineering, (SIMATS),Chennai

5. Sri Sairam Engineering College Affiliated to Anna University,Dept. of CSE

6. Lakshmi Bangaru Arts and Science College,Dept. of Computer Applications,melmaruvathur

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10220576/10220579/10220911.pdf?arnumber=10220911

Reference21 articles.

1. Machine Learning Approaches for Predicting the Severity Level of Software Bug Reports in Closed Source Projects

2. Predicting the Severity of Closed Source Bug Reports Using Ensemble Methods

3. A Novel Approach for Code Smell Detection: An Empirical Study

4. Predicting the Severity of Open Source Bug Reports Using Unsupervised and Supervised Techniques

5. Review of deep learning: Concepts, CNN architectures, challenges, applications, future directions;alzubaidi;Journal Of Big Data,2021

Cited by 1 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. Dynamic stacking ensemble for cross-language code smell detection;PeerJ Computer Science;2024-08-15

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