Software Defect Prediction: An ML Approach-Based Comprehensive Study-Reference-Cited by-同舟云学术

Software Defect Prediction: An ML Approach-Based Comprehensive Study

Published:2022-10-28 Issue: Volume: Page:497-512
ISSN:2367-3370
Container-title:Communication, Software and Networks
language:
Short-container-title:

Author:

Anand Kunal,Jena Ajay Kumar

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-4990-6_46

Reference27 articles.

1. Jena AK, Das H, Mohapatra DP (eds) (2020) Automated software testing: foundations, applications and challenges. Springer Nature

2. Tassey G (2002) The economic impacts of inadequate infrastructure for software testing. National Institute of Standards and Technology. RTI Project, 7007(11):1–309

3. Mäntylä MV, Lassenius C (2008) What types of defects are discovered in code reviews? IEEE Trans Softw Eng 35(3):430–448

4. Saifan AA, Abu-wardih L (2020) Software defect prediction based on feature subset selection and ensemble classification. ECTI Trans Comput Inform Technol (ECTI-CIT) 14(2):213–228. https://doi.org/10.37936/ecti-cit.2020142.224489

5. Mangla M, Sharma N, Mohanty SN (2021) A sequential ensemble model for software fault prediction. Innov Syst Softw Eng 1–8

Cited by 3 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. Forecasting Software Modules with Known Defects through the Quadratic Discriminant Analysis Feature Reduction Technique;2024 International Conference on Emerging Systems and Intelligent Computing (ESIC);2024-02-09

2. Handling uncertainty issue in software defect prediction utilizing a hybrid of ANFIS and turbulent flow of water optimization algorithm;Neural Computing and Applications;2023-12-14

3. Performance Analysis of Feature Selection Techniques in Software Defect Prediction using Machine Learning;2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC);2022-11-19