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A Markov Reward Model for Software Reliability
Kwon, Y. Agha, G.
Dept. of Comput. Sci., Illinois Univ., Urbana, IL;

This paper appears in: Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Publication Date: 26-30 March 2007
On page(s): 1-6
Location: Long Beach, CA,
ISBN: 1-4244-0910-1
INSPEC Accession Number: 9516828
Digital Object Identifier: 10.1109/IPDPS.2007.370525
Current Version Published: 2007-06-11

Abstract
A compositional method for estimating software reliability of many threaded programs is developed. The method uses estimates of the reliability of individual modules and the probability of transitions between the modules to estimate the reliability of a program in terms of its current state. The reliability of a program is expressed using iLTL, a probabilistic linear temporal logic whose atomic propositions are linear inequalities about transitions of the probability mass function of a discrete time Markov chain. We then use a Markov reward model to estimate software reliability. The technique is illustrated in terms of an example.

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