On a Method for Mending Time to Failure Distributions

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

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Year of publication:	2004
Authors:	Grottke, Michael ; Trivedi, Kishor S.
Publisher:	Universität <Erlangen
Subject:	Fehlerbehandlung \| Distribution <Informatik> \| Poisson-Prozess

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1. Introduction
2. Defective TTF distributions in SRGMs - General condition
3. Defective TTF distributions in NHPP models
3.1 General considerations
3.2 Finite failures category NHPP models
3.3 Infinite failures category NHPP models
4. Truncating Poisson distributions
4.1 Truncating the distribution of the number of inherent faults
4.2 Truncating the conditional distributions of the number of faults remaining
5. Defective TTF distributions in other models
6. A specific all-stages truncated model and its application
6.1 The truncated Goel-Okumoto model
6.2 Numerical example
7. Conclusions

Persistent link: https://www.econbiz.de/10005857550