A Markov reward model for software reliability

Young Min Kwon, Gul Agha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
DOIs
StatePublished - 2007
Event21st International Parallel and Distributed Processing Symposium, IPDPS 2007 - Long Beach, CA, United States
Duration: Mar 26 2007Mar 30 2007

Publication series

NameProceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM

Other

Other21st International Parallel and Distributed Processing Symposium, IPDPS 2007
CountryUnited States
CityLong Beach, CA
Period3/26/073/30/07

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Mathematics(all)

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