Code smell detection by deep direct-learning and transfer-learning-Reference-Cited by-同舟云学术

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Code smell detection by deep direct-learning and transfer-learning

Published:2021-06 Issue: Volume:176 Page:110936
ISSN:0164-1212
Container-title:Journal of Systems and Software
language:en
Short-container-title:Journal of Systems and Software

Author:

Sharma Tushar,Efstathiou Vasiliki,Louridas Panos,Spinellis Diomidis

Funder

Horizon 2020

EU Framework Programme for Research and Innovation Marie Skłodowska-Curie Actions

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference152 articles.

1. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks;Abdeljaber;J. Sound Vib.,2017

2. Replicating parser behavior using neural machine translation;Alexandru,2017

3. Allamanis, M., 2019. The adverse effects of code duplication in machine learning models of code. In: Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software, pp. 143–153.

4. A survey of machine learning for big code and naturalness;Allamanis;ACM Comput. Surv.,2018

5. Learning to represent programs with graphs;Allamanis,2017

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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

2. Enhancing source code classification effectiveness via prompt learning incorporating knowledge features;Scientific Reports;2024-08-30

3. Practitioners' Expectations on Code Smell Detection;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

4. Improving accuracy of code smells detection using machine learning with data balancing techniques;The Journal of Supercomputing;2024-06-05

5. Application of Deep Learning for Code Smell Detection: Challenges and Opportunities;SN Computer Science;2024-06-03

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