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A markov process model for software reliability analysis

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  • M. Xie

Abstract

Software reliability is a rapidly developing discipline. In this paper we model the fault‐detecting processes by Markov processes with decreasing jump intensity. The intensity function is suggested to be a power function of the number of the remaining faults in the software. The models generalize the software reliability model suggested by Jelinski and Moranda (‘Software reliability research’, in W. Freiberger (ed.), Statistical Computer Performance Evaluation, Academic Press, New York, 1972. pp. 465–497). The main advantage of our models is that we do not use the assumption that all software faults correspond to the same failure rate. Preliminary studies suggest that a second‐order power function is quite a good approximation. Statistical tests also indicate that this may be the case. Numerical results show that the estimation of the expected time to next failure is both reasonable and decreases relatively stably when the number of removed faults is increased.

Suggested Citation

  • M. Xie, 1990. "A markov process model for software reliability analysis," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 6(4), pages 207-213, December.
    • Handle: RePEc:wly:apsmda:v:6:y:1990:i:4:p:207-213
    DOI: 10.1002/asm.3150060404
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    Cited by:

    1. Siqiao Li & Tadashi Dohi & Hiroyuki Okamura, 2023. "Software reliability analysis via geometric de-eutrophication models with group data," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 156-164, February.

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