Gradient Boosting Optimized Through Differential Evolution for Predicting the Testing Effort of Software Projects-Reference-Cited by-同舟云学术

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Gradient Boosting Optimized Through Differential Evolution for Predicting the Testing Effort of Software Projects

Published:2023 Issue: Volume:11 Page:135235-135254
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Sánchez-García Angel J.¹^ORCID,López-Martín Cuauhtémoc²^ORCID,Abran Alain³^ORCID

Affiliation:

1. Facultad de Estadística e Informática, Universidad Veracruzana, Xalapa, Veracruz, Mexico

2. Department of Information Systems, Universidad de Guadalajara, Zapopan, Jalisco, Mexico

3. Department of Software Engineering and Information Technology, École de Technologie Supérieure, Université du Québec, Montreal, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10335182.pdf?arnumber=10335182

Reference122 articles.

1. The guide to the Software Engineering Body of Knowledge

2. A new weighted naive Bayes method based on information diffusion for software defect prediction

3. Advances in test automation for software with special focus on artificial intelligence and machine learning

4. Guest Editorial: Special issue on Testing Software and Systems

5. An empirical approach for early estimation of software testing effort using SRS document

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