Add to ORKGIn this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example
We present a sequential software release procedure that certifies with some confidence level that th...
Predicting the reliability of software systems based on a component-based approach is inherently dif...
We present a sequential software release procedure that certifies with some confidence level that th...
In this paper, we are concerned with predicting the number of faults N and the time to next failure ...
We wish to predict the number of faults N and the time to next failure of a piece of software. Softw...
We wish to predict the number of faults N and the time to next failure of a piece of software. Softw...
The Gibbs sampling approach is developed for Bayesian inferences and predictions in software reliabi...
In this dissertation, we present Bayesian inference for models based on non-homogeneous Poisson proc...
In reliability analyses recording the lifetimes of a sample of test units is not always possible, fo...
Abstract: We consider a software reliability model where the failure rate of each fault depends on t...
The use of statistical methods is central to improving the quality of products utilized in society t...
In this article, we define a model for fault detection during the beta testing phase of a software d...
In this article, we define a model for fault detection during the beta testing phase of a software d...
This paper presents a Bayesian methodology for the Ohba-Yamada model. The Ohba-Yamada model assumes ...
SIGLEAvailable from British Library Document Supply Centre- DSC:7673.051(89/28) / BLDSC - British Li...
We present a sequential software release procedure that certifies with some confidence level that th...
Predicting the reliability of software systems based on a component-based approach is inherently dif...
We present a sequential software release procedure that certifies with some confidence level that th...
In this paper, we are concerned with predicting the number of faults N and the time to next failure ...
We wish to predict the number of faults N and the time to next failure of a piece of software. Softw...
We wish to predict the number of faults N and the time to next failure of a piece of software. Softw...
The Gibbs sampling approach is developed for Bayesian inferences and predictions in software reliabi...
In this dissertation, we present Bayesian inference for models based on non-homogeneous Poisson proc...
In reliability analyses recording the lifetimes of a sample of test units is not always possible, fo...
Abstract: We consider a software reliability model where the failure rate of each fault depends on t...
The use of statistical methods is central to improving the quality of products utilized in society t...
In this article, we define a model for fault detection during the beta testing phase of a software d...
In this article, we define a model for fault detection during the beta testing phase of a software d...
This paper presents a Bayesian methodology for the Ohba-Yamada model. The Ohba-Yamada model assumes ...
SIGLEAvailable from British Library Document Supply Centre- DSC:7673.051(89/28) / BLDSC - British Li...
We present a sequential software release procedure that certifies with some confidence level that th...
Predicting the reliability of software systems based on a component-based approach is inherently dif...
We present a sequential software release procedure that certifies with some confidence level that th...