On a method for mending time to failure distributions

被引：17

作者：

Grottke, M ^{[1
]}

Trivedi, KS ^{[1
]}

机构：

[1] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA

来源：

2005 INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, PROCEEDINGS | 2005年

关键词：

D O I：

10.1109/DSN.2005.72

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 non-homogeneous Poisson process (NHPP) models of the finite failures category 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.

引用

页码：560 / 569

页数：10

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