Markov process model for software reliability analysis

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

5 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)207-213
Journal / PublicationApplied Stochastic Models and Data Analysis
Volume6
Issue number4
Publication statusPublished - Dec 1990
Externally publishedYes

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. 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.