Overview
- Discusses the basic concepts of software reliability growth models
- Explains different non-homogeneous Poisson process of software reliability models
- Presents applications in artificial neural networks, machine learning, and artificial intelligence
- Appeals to practitioners, researchers, and students who need information on software reliability engineering
Part of the book series: Infosys Science Foundation Series (ISFS)
Part of the book sub series: Infosys Science Foundation Series in Mathematical Sciences (ISFM)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Review of literature on SRGM has been included from the scratch to recent developments, applicable in artificial neural networks, machine learning, artificial intelligence, data-driven approaches, fault-detection, fault-correction processes, and also in random environmental conditions. This book is designed for practitioners and researchers at all levels of competency, and also targets groups who need information on software reliability engineering.
Authors and Affiliations
About the authors
He is Editor-in-Chief, Associate Editor, and an editorial board member of several reputed national and international journals. He is the chairperson, the subject expert, and an advisory committee member on several UGC committees. He is a National Assessment and Accreditation Council (NAAC) Assessor from UGC. He is the subject expert (statistics) in board of studies committee of several universities. He is a governing council member, an executive council member, and a life member of several statistical societies, organizations, and associations. His research interests include statistical inference, selection problems, reliability, survival analysis, frailty models, Bayesian inference, stress–strength models, Monte–Carlo methods, MCMC algorithms, bootstrapping, censoring schemes, distribution theory, multivariate models, characterizations, repair and replacement models, software reliability, quality loss index, and nonparametric inference. With more than 40 years of teaching experience and more than 35 years of research experience, he is an expert on writing programs using SAS, R, MATLAB, MINITAB, SPSS, and SPLUS statistical packages.
Nileema N. Bhalerao is Assistant Professor at Fergusson College, Pune, India. With 20 years of teaching experience and 5 years of research experience, she is an expert on writing programs using several statistical packages. Her research interest includes software reliability models.
Bibliographic Information
Book Title: Software Reliability Growth Models
Authors: David D. Hanagal, Nileema N. Bhalerao
Series Title: Infosys Science Foundation Series
DOI: https://doi.org/10.1007/978-981-16-0025-8
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
Hardcover ISBN: 978-981-16-0024-1Published: 27 February 2021
Softcover ISBN: 978-981-16-0027-2Published: 27 February 2022
eBook ISBN: 978-981-16-0025-8Published: 26 February 2021
Series ISSN: 2363-6149
Series E-ISSN: 2363-6157
Edition Number: 1
Number of Pages: XXI, 104
Number of Illustrations: 40 b/w illustrations
Topics: Statistics, general