Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/29583
Authors: 
Grottke, Michael
Trivedi, Kishor S.
Year of Publication: 
2004
Series/Report no.: 
Diskussionspapiere // Friedrich-Alexander-Universität Erlangen-Nürnberg, Lehrstuhl für Statistik und Ökonometrie 66/2004
Abstract: 
Many software reliability growth models assume that the time to next failure may be infinite; i.e., there is a chance that no failure will occur at all. For most software products this is too good to be true even after the testing phase. Moreover, if a non-zero probability is assigned to an infinite time to failure, metrics like the mean time to failure do not exist. In this paper, we try to answer several questions: Under what condition does a model permit an infinite time to next failure? Why do all finite failures non-homogeneous Poisson process (NHPP) models share this property? And is there any transformation mending the time to failure distributions? Indeed, such a transformation exists; it leads to a new family of NHPP models. We also show how the distribution function of the time to first failure can be used for unifying finite failures and infinite failures NHPP models.
Subjects: 
software reliability growth model
non-homogeneous Poisson process
defective distribution
(mean) time to failure
model unification
Document Type: 
Working Paper

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