Cart (Loading....) | Create Account
Close category search window

Wavelet Shrinkage Estimation for Non-Homogeneous Poisson Process Based Software Reliability Models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Xiao Xiao ; Dept. of Inf. Eng., Hiroshima Univ., Higashi-Hiroshima, Japan ; Dohi, T.

We develop a novel estimation approach for quantitative software reliability by means of wavelet-based technique, where the underlying software reliability model is described by a non-homogeneous Poisson process. Our approach involves some advantages over the commonly used techniques such as maximum likelihood estimation: 1) the wavelet shrinkage estimation enables us to carry out the time-series analysis with high speed and accuracy requirements; and 2) The wavelet shrinkage estimation is classified into a non-parametric estimation without specifying a parametric form of the software intensity function. We consider data-transform-based wavelet shrinkage estimation with four kinds of thresholding schemes for empirical wavelet coefficients to estimate the software intensity function. In numerical experiments with real software-fault count data, we show that our wavelet-based estimation methods can provide better goodness-of-fit performance than not only the conventional maximum likelihood estimation and least squares estimation but also the local likelihood estimation method, in many cases, in spite of their non-parametric nature. Furthermore, we investigate the predictive performance of the proposed methods by employing the so-called one-stage look-ahead prediction method, and estimate some predictive measures such as software reliability.

Published in:

Reliability, IEEE Transactions on  (Volume:62 ,  Issue: 1 )

Date of Publication:

March 2013

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.