Imperfect debugging in software reliability: A Bayesian approach |
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Authors: | Tevfik Aktekin Toros Caglar |
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Institution: | 1. Department of Decision Sciences, University of New Hampshire, Durham, NH, United States;2. Institute for Integrating Statistics in Decision Sciences, The George Washington University, Washington, DC, United States |
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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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Keywords: | Software reliability Bayesian inference Imperfect debugging |
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