Trivariate Bernoulli distribution with application to software fault tolerance

Lance Fiondella () and Panlop Zeephongsekul ()
Additional contact information
Lance Fiondella: University of Massachusetts
Panlop Zeephongsekul: RMIT University

Annals of Operations Research, 2016, vol. 244, issue 1, No 14, 255 pages

Abstract: Abstract The widespread reliance on software for mission and life critical applications makes the reliability of these systems essential. Techniques such as fault tolerance have been proposed to achieve the highest levels of software reliability. However, the fault tolerance paradigm suffers from the risk of correlated failures, where a majority of the software versions fail on the same input leading to system failure. This paper derives a trivariate Bernoulli distribution to quantify the negative impact of correlated failures on the reliability of fault tolerant software composed of highly reliable versions. An experiment based on early empirical research demonstrates the capacity of the distribution to conduct reliability assessment for many combinations of the version reliabilities and correlations. The results indicate that correlated failures detract from system reliability, but that this reliability is often higher than a system composed of the single most reliable version.

Keywords: Trivariate Bernoulli distribution; Fault tolerance; Software reliability; $$N$$ N -version programming (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-015-1798-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-015-1798-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-015-1798-4

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().