Book Details
Format
Hardback or Cased Book
ISBN-10
9811600244
ISBN-13
9789811600241
Edition
2021 ed.
Publisher
Springer Verlag, Singapore
Imprint
Springer Verlag, Singapore
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Feb 27th, 2021
Print length
104 Pages
Product Classification:
Probability & statistics
Ksh 21,600.00
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This book presents the basic concepts of software reliability growth models (SRGMs), ranging from fundamental to advanced level. It discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability engineering. These models consider the debugging process as a counting process characterized by its mean value function. Model parameters have been estimated by using either the maximum likelihood method or regression. NHPP SRGMs based on inverse Weibull, generalized inverse Weibull, extended inverse Weibull, generalized extended inverse Weibull, and delayed S-shaped have been focused upon. 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.
This book presents the basic concepts of software reliability growth models (SRGMs), ranging from fundamental to advanced level. It discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability engineering. These models consider the debugging process as a counting process characterized by its mean value function. Model parameters have been estimated by using either the maximum likelihood method or regression. NHPP SRGMs based on inverse Weibull, generalized inverse Weibull, extended inverse Weibull, generalized extended inverse Weibull, and delayed S-shaped have been focused upon.
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.
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