A binary Markov process model for random testing

Author

Chen, Sanping ; Mills, Shirley

Author_Institution

Stat. Consulting Centre, Carleton Univ., Ottawa, Ont., Canada

Volume

22

Issue

3

fYear

1996

fDate

3/1/1996 12:00:00 AM

Firstpage

218

Lastpage

223

Abstract

A binary Markov process model is proposed for the random testing of software. This model is suggested for replacing the standard binomial distribution model, which is based on the easily-violated assumption of test runs being statistically independent of each other. In addition to a general result on the probability of having any specific number of software failures during testing, practical implications of the new model are also discussed. In particular, we demonstrate that, in general, the effect of a possible correlation between test runs cannot be ignored in estimating software reliability

Keywords

Markov processes; binomial distribution; program testing; software reliability; binary Markov process model; binomial distribution model; correlation; dependent test runs; random software testing; software failure probability; software reliability estimation; statistical testing; statistically independent test runs; ultra-reliability application; Application software; Graphics; Markov processes; Milling machines; Software testing; Statistics;

fLanguage

English

Journal_Title

Software Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0098-5589

Type

jour

DOI

10.1109/32.489081

Filename

489081