A Bayesian Inference Tool for NHPP-Based Software Reliability Assessment

Authors:
Takumi Hirata;Hiroyuki Okamura;Tadashi Dohi
Affiliations:
Department of Information Engineering, Graduate School of Engineering, Hiroshima University, Higashi-Hiroshima, Japan 739-8527;Department of Information Engineering, Graduate School of Engineering, Hiroshima University, Higashi-Hiroshima, Japan 739-8527;Department of Information Engineering, Graduate School of Engineering, Hiroshima University, Higashi-Hiroshima, Japan 739-8527
Venue:
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
Year:
2009

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Abstract

In this paper, we concern a sampling method for Markov chain Monte Carlo (MCMC) in estimating software reliability, and propose a unified MCMC algorithm based on the Metropolis-Hasting method regardless of model on data structures. The resulting MCMC algorithm is implemented as a Java-based tool. Using the Java-based Bayesian inference tool, we illustrate how to assess the software reliability in actual software development processes.