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



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Autore: Bisi Manjubala Visualizza persona
Titolo: Artificial neural network for software reliability prediction / / by Manjubala Bisi and Neeraj Kumar Goyal Visualizza cluster
Pubblicazione: Hoboken, New Jersey ; ; Beverly, Massachusetts : , : John Wiley & Sons : , : Scrivener Publishing, , 2017
©2017
Edizione: First edition
Descrizione fisica: 1 online resource (220 pages) : illustrations, figures, tables
Disciplina: 006.32
Soggetto topico: Neural networks (Computer science)
Computer software - Reliability
Persona (resp. second.): GoyalNeeraj Kumar
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Introduction -- 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.
Sommario/riassunto: 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.
Titolo autorizzato: Artificial neural network for software reliability prediction  Visualizza cluster
ISBN: 1-119-22396-2
1-119-22392-X
1-119-22393-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910828170003321
Lo trovi qui: Univ. Federico II
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Serie: Performability engineering series.