Assessing (Software) Reliability Growth Using a Random Coefficient Autoregressive Process and Its Ramifications

Author

Singpurwalla, Nozer D. ; Soyer, Refik

Author_Institution

Institute for Reliability and Risk Analysis, School of Engineering and Applied Science, George Washington University

Issue

12

fYear

1985

Firstpage

1456

Lastpage

1464

Abstract

In this paper we motivate a random coefficient autoregressive process of order 1 for describing reliability growth or decay. We introduce several ramifications of this process, some of which reduce it to a Kalman Filter model. We illustrate the usefulness of our approach by applying these processes to some real life data on software failures. Finally, we make a pairwise comparison of the models in terms of the ratio of likelihoods of their predictive distributions, and identify the "best" model.

Keywords

Dynamic linear and nonlinear models; Kalman Filtering; likelihood ratios; predictive distributions; prequential analysis; random coefficient autoregressive processes; reliability growth; software reliability; Autoregressive processes; Filtering; Kalman filters; Life testing; Nonlinear filters; Predictive models; Risk analysis; Software reliability; Software testing; System testing; Dynamic linear and nonlinear models; Kalman Filtering; likelihood ratios; predictive distributions; prequential analysis; random coefficient autoregressive processes; reliability growth; software reliability;

fLanguage

English

Journal_Title

Software Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0098-5589

Type

jour

DOI

10.1109/TSE.1985.231889

Filename

1701968