Early Software Reliability Prediction with Wavelet Networks Models

DOI

10.2991/iske.2007.87How to use a DOI?

Keywords

Wavelet Networks Models; Early Software Reliability; Prediction; accurate

Abstract

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. 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.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Denghua Mei
PY  - 2007/10
DA  - 2007/10
TI  - Early Software Reliability Prediction with Wavelet Networks Models
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 515
EP  - 518
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.87
DO  - 10.2991/iske.2007.87
ID  - Mei2007/10
ER  -