Early Software Reliability Prediction with Wavelet Networks Models
Denghua Mei · 2007
Accurate reliability estimates can be obtained by using software reliability models only in the later phase of software testing. However, for cost effective and timely, management prediction in the early phase is important. Non-homogenerous Poisson process (NHPP) models and Artificial Neural Network (ANN) models are the most important Analytical software reliability growth models. In this paper we study an approach to using past fault-related data with Wavelet Networks model to improve reliability predictions in the early testing phase. A numerical example is shown with both actual and simulated datasets. The analysis with example shows that the proposed approach works effectively in the early phase of software testing.