Imperfect debugging in software reliability: A Bayesian approach

Imperfect debugging in software reliability: A Bayesian approach

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Article ID: iaor20131067
Volume: 227
Issue: 1
Start Page Number: 112
End Page Number: 121
Publication Date: May 2013
Journal: European Journal of Operational Research
Authors: ,
Keywords: Bayesian analysis, Monte Carlo method, software reliability
Abstract:

The objective of studying software reliability is to assist software engineers in understanding more of the probabilistic nature of software failures during the debugging stages and to construct reliability models. In this paper, we consider modeling of a multiplicative failure rate whose components are evolving stochastically over testing stages and discuss its Bayesian estimation. In doing so, we focus on the modeling of parameters such as the fault detection rate per fault and the number of faults. We discuss how the proposed model can account for ‘imperfect debugging’ under certain conditions. We use actual inter‐failure data to carry out inference on model parameters via Markov chain Monte Carlo methods and present additional insights from Bayesian analysis.

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