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Software Reliability Growth Models

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Software Reliability Growth Models/ by David D. Hanagal, Nileema N. Bhalerao.
Author:	Hanagal, David D.
other author:	Bhalerao, Nileema N.
Description:	XXI, 104 p. 40 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-981-16-0025-8
ISBN:	9789811600258

Software Reliability Growth Models
Hanagal, David D.

Software Reliability Growth Models[electronic resource] /by David D. Hanagal, Nileema N. Bhalerao. - 1st ed. 2021. - XXI, 104 p. 40 illus.online resource. - Infosys Science Foundation Series in Mathematical Sciences,2364-4044. - Infosys Science Foundation Series in Mathematical Sciences,.

1. Introduction to Software Reliability Models -- 2. Literature Survey in Software Reliability Growth Models -- 3. NHPP Software Reliability Growth Models -- 4. Inverse Weibull Software Reliability Growth Model -- 5. Generalized Inverse Weibull Software Reliability Growth Model -- 6. Extended Inverse Weibull Software Reliability Growth Model -- 7. Generalized Extended Inverse Weibull Software Reliability Growth Model -- 8. Delayed S-Shaped SRGM with Time Dependent Fault Content Rate Function -- 9. Scope for Future Extension to SRGM.

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.

ISBN: 9789811600258

Standard No.: 10.1007/978-981-16-0025-8doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Software Reliability Growth Models
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