Preprint Article Version 1 This version not peer reviewed

A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments

Version 1 : Received: 18 August 2017 / Approved: 18 August 2017 / Online: 18 August 2017 (13:05:46 CEST)

How to cite: Song, K.Y.; Chang, I.H.; Pham, H. A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments. Preprints 2017, 2017080066 (doi: 10.20944/preprints201708.0066.v1). Song, K.Y.; Chang, I.H.; Pham, H. A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments. Preprints 2017, 2017080066 (doi: 10.20944/preprints201708.0066.v1).

Abstract

The main focus when developing software is to improve the reliability and stability of a software system. When software systems are introduced, these systems are used in field environments that are the same as or close to those used in the development-testing environment; however, they may also be used in many different locations that may differ from the environment in which they were developed and tested. In this paper, we propose a new software reliability model that takes into account the uncertainty of operating environments. The explicit mean value function solution for the proposed model is presented. Examples are presented to illustrate the goodness-of-fit of the proposed model and several existing non-homogeneous Poisson process (NHPP) models and confidence intervals of all models based on two sets of failure data collected from software applications. The results show that the proposed model fits the data more closely than other existing NHPP models to a significant extent.

Subject Areas

non-homogeneous poisson process; software reliability; weibull function; mean square error

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