Title :
A binary Markov process model for random testing
Author :
Chen, Sanping ; Mills, Shirley
Author_Institution :
Stat. Consulting Centre, Carleton Univ., Ottawa, Ont., Canada
fDate :
3/1/1996 12:00:00 AM
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;
Journal_Title :
Software Engineering, IEEE Transactions on