Software fault prediction using lion optimization algorithm-Reference-Cited by-同舟云学术

Software fault prediction using lion optimization algorithm

Published:2021-09-21 Issue:6 Volume:13 Page:2185-2190
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Goyal Somya,Bhatia Pradeep Kumar

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-021-00804-w.pdf

Reference21 articles.

1. Goyal S (2021) Predicting the defects using stacked ensemble learner with filtered dataset. Autom Softw Eng 28:14. https://doi.org/10.1007/s10515-021-00285-y

2. Goyal S, Bhatia P (2020) Comparison of machine learning techniques for software quality prediction, International Journal of Knowledge and Systems Science (IJKSS). IGI Global 11(2):21–40. https://doi.org/10.4018/IJKSS.2020040102

3. Goyal S (2021) Handling class-imbalance with KNN (Neighbourhood) under-sampling for software defect prediction. Artif Intell Rev. https://doi.org/10.1007/s10462-021-10044-w

4. Kondo M, Bezemer C-P, Kamei Y, Hassan AE, Mizuno O (2019) The impact of feature reduction techniques on defect prediction models. Empir Softw Eng 24:1925–1963

5. Hosseini S, Turhan B, Mäntylä M (2018) A benchmark study on the effectiveness of search-based data selection and feature selection for cross project defect prediction. Inf Softw Technol J 95:296–312

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