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Prediction of software defects using deep learning with improved cuckoo search algorithm

  • Published:2022-09-06 Issue:26 Volume:34 Page:
  • ISSN:1532-0626
  • Container-title:Concurrency and Computation: Practice and Experience
  • language:en
  • Short-container-title:Concurrency and Computation

Author:

Badvath Dhanalaxmi1ORCID,Miriyala Aruna safali2,Gunupudi Sai chaitanya Kumar3,Kuricheti Parish venkata Kumar4

Affiliation:

1. Department of Computer Science and Engineering Malla Reddy Institute of Engineering and Technology (Autonomous) Hyderabad Telangana India

2. Department of Computer Science and Engineering Dhanekula Institute of Engineering and Technology Vijayawada Andhra Pradesh India

3. Department of Computer Science and Engineering DVR & Dr. Hs Mic College of Technology Kanchikacherla Andrapradesh India

4. Department of Computer Applications Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Andhra Pradesh India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference29 articles.

1. Progress on approaches to software defect prediction

2. Survey on software defect prediction techniques;Thota MK;Int J Appl Sci Eng,2020

3. A rule based prediction method for defect detection in software system;Dhanalaxmi B;J Theor Appl Inf Technol,2017

4. Software defect prediction: do different classifiers find the same defects?

5. A systematic review of unsupervised learning techniques for software defect prediction

Cited by 2 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. Salp Swarm Algorithm Based on Opposition-Based Learning and Good Point Set for Numerical Function Optimization;2023 International Conference on Algorithms, Computing and Data Processing (ACDP);2023-06-23

2. Multiple Feature Selection Frameworks Based on Evolutionary Computing and Ensemble Learning for Software Defect Prediction;2022 5th International Conference on Computational Intelligence and Networks (CINE);2022-12-01
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