
Artificial Neural Network Applications for Software Reliability Prediction
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Artificial Neural Network Applications for Software Reliability Prediction
About this book
This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization.
Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process are presented. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.
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Information
Table of contents
- Cover
- Title page
- Copyright page
- Dedication
- Preface
- Acknowledgement
- Abbreviations
- Chapter 1: Introduction
- Chapter 2: Software Reliability Modelling
- Chapter 3: Prediction of Cumulative Number of Software Failures
- Chapter 4: Prediction of Time Between Successive Software Failures
- Chapter 5: Identification of Software Fault-Prone Modules
- Chapter 6: Prediction of Software Development Efforts
- Chapter 7: Recent Trends in Software Reliability
- References
- Appendix Failure Count Data Set
- Appendix Time Between Failure Data Set
- Appendix CM1 Data Set
- Appendix COCOMO 63 Data Set
- Index
- End User License Agreement