Artificial Neural Network Applications For Software Reliability Prediction (performability Engineering Series)
by Neeraj Kumar Goyal /
2017 / English / PDF
1.2 MB Download
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 is presented as well. 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.
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 is presented as well. 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.