David Rine

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In this paper neural networks have been proposed as an alternative technique to build software reliability growth models. A feed-forward neural network was used to predict the number of faults initially resident in a program at the beginning of a test/debug process. To evaluate the predictive capability of the developed model data sets from various projects(More)
In this paper we propose the idea of building a new software reliability models using Radial Basis Function (RBF) network. The RBF network is easy to design and the network structure can be represented in a simple mathematical equation. Our goal is to build a generalized model that can be used for software predication [1]. The RBF network was trained with a(More)