NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Amazon cover image
Image from Amazon.com

Artificial neural network for software reliability prediction / by Manjubala Bisi and Neeraj Kumar Goyal.

By: Contributor(s): Material type: TextSeries: Performability engineering seriesPublisher: Hoboken, NJ : John Wiley & Sons ; Beverly, MA : Scrivener Publishing, 2017Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119223924
  • 111922392X
  • 9781119223962
  • 1119223962
  • 9781119223931
  • 1119223938
  • 1119223547
  • 9781119223542
Subject(s): Additional physical formats: Print version:: Artificial neural network for software reliability prediction.DDC classification:
  • 006.3/2 23
LOC classification:
  • QA76.87
Online resources:
Contents:
Software reliability modelling -- Prediction of cumulative number of software failures -- Prediction of time between successive software failures -- Identification of software fault-prone modules -- Prediction of software development efforts -- Recent trends in software reliability.
Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Includes bibliographical references and index.

Software reliability modelling -- Prediction of cumulative number of software failures -- Prediction of time between successive software failures -- Identification of software fault-prone modules -- Prediction of software development efforts -- Recent trends in software reliability.

Print version record and CIP data provided by publisher.

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.

John Wiley and Sons Wiley Online Library: Complete oBooks

There are no comments on this title.

to post a comment.
Previous
Back to results
Next
Close