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Artificial neural network for software reliability prediction /
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, faul...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ : Beverly, MA :
John Wiley & Sons ; Scrivener Publishing,
2017.
|
| Colección: | Performability engineering series.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Bisi, Manjubala, |e author. | |
| 245 | 1 | 0 | |a Artificial neural network for software reliability prediction / |c by Manjubala Bisi and Neeraj Kumar Goyal. |
| 264 | 1 | |a Hoboken, NJ : |b John Wiley & Sons ; |a Beverly, MA : |b Scrivener Publishing, |c 2017. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Performability engineering series | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 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. | |
| 588 | 0 | |a Print version record and CIP data provided by publisher. | |
| 520 | |a 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. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Computer software |x Reliability. | |
| 650 | 2 | |a Neural Networks, Computer | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) | |
| 650 | 6 | |a Logiciels |x Fiabilité. | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Computer software |x Reliability. |2 fast |0 (OCoLC)fst00872585 | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
| 700 | 1 | |a Goyal, Neeraj Kumar, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Bisi, Manjubala. |t Artificial neural network for software reliability prediction. |d Hoboken, NJ : John Wiley & Sons ; Beverly, MA : Scrivener Publishing, 2017 |z 9781119223542 |w (DLC) 2017030704 |
| 830 | 0 | |a Performability engineering series. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781119223542/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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