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Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) >
Lehrstuhl für Statistik und Ökonometrie, Universität Erlangen-Nürnberg >
Diskussionspapiere des Lehrstuhls für Statistik und Ökonometrie, FAU Erlangen-Nürnberg >
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http://hdl.handle.net/10419/29583
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| Title: | | On a method for mending time to failure distributions  |
| Authors: | | Grottke, Michael Trivedi, Kishor S. |
| Issue Date: | | 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 |
| Appears in Collections: | | Diskussionspapiere des Lehrstuhls für Statistik und Ökonometrie, FAU Erlangen-Nürnberg
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