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

Abstract

Featured Application: This study introduces a new software reliability model with the Weibull fault detection rate function that takes into account the uncertainty of operating environments.Abstract: 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 environments; however, they may also be used in many different locations that may differ from the environment in which they were developed and tested. As such, it is difficult to improve software reliability for a variety of reasons, such as a given environment, or a bug location in code. 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.

On an Alternative to Four Notable Distribution Functions with Applications in Engineering and the Business Sciences

“…It is worth noting here that the Weibull distribution is widely applied to model reliability of software systems (see, e.g. [19,29]), therefore, our pliant probability distribution, as an alternative to the Weibull probability distribution, can also be applied in this area.…”

An NHPP Software Reliability Model with S-Shaped Growth Curve Subject to Random Operating Environments and Optimal Release Time

“…We propose an NHPP software reliability model including the random operating environment using Equations (3)-(5) and the following assumptions [7,8]: The software failure detection rate at any time depends on both the fault detection rate and the number of remaining faults in the software at that time. (d) Debugging is performed to remove faults immediately when a software failure occurs.…”

“…We use (8) below to obtain the confidence interval [13] of the proposed NHPP software reliability model. The confidence interval is described as follows;…”

“…Okamura and Dohi [6] introduced a phase-type software reliability model and developed parameter estimation algorithms using grouped data. Song et al [7,8] recently developed an NHPP software reliability model to consider a three-parameter fault detection rate, and applied a Weibull fault detection rate function during the software development process. They related the model to the error detection rate function by considering the uncertainty of the operating environment.…”

A Software Reliability Model Considering the Syntax Error in Uncertainty Environment, Optimal Release Time, and Sensitivity Analysis

“…Li et al [12] performed new testing coverage modeling that considers not only the error generation but also the fault removal efficiency based on NHPP. Song et al [13][14][15] considered operating environments. They applied random variable to the software reliability model, which represent the uncertainty in the operating environment.…”