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Volume & Issue no: Volume 3, Issue 11, November 2014

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Title:
Neural Network analysis of Software Reliability Growth Models
Author Name:
Sugam Srivastava and Monika Sharma
Abstract:
ABSTRACT There is a major concern which has come across all the researchers in the field of software-reliability that is how to develop a universal model which can predict the reliability under all circumstances, since reliability-growth models predictions varies across different testing phases. The best way is to develop a model which makes no assumptions about the behavior of software failure. This is where Neural Network model comes into play. Neural Network models have significant advantage over simple parametric reliability models because they only require failure history as input and make no assumptions. Based on those failure inputs neural network model predicts the future failure. This paper shows the reliability prediction through neural network model as well as through reliability growth models. Keywords:- Neural network model, parametric reliability models, non-parametric reliability models, Hann filter.
Cite this article:
Sugam Srivastava and Monika Sharma , " Neural Network analysis of Software Reliability Growth Models" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 11, November 2014 , pp. 212-217 , ISSN 2319 - 4847.
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