A Moving Average Modeling Approach for Computing Component-Based Software Reliability Growth Trends

This paper introduces a moving average reliability growth model to describe the evolution of component-based software. In this model, the reliability of a system is a function of the reliabilities of its constituent components. The moving average provides a trend indicator to depict reliability grow...

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Bibliographic Details
Authors: Wang, Wen-Li, Hemminger, Thomas L., Tang, Mei-Huei
Format: article
Status:Published version
Publication Date:2006
Country:Brasil
Institution:Universidade Federal de Lavras (UFLA)
Repository:INFOCOMP: Jornal de Ciência da Computação
Language:English
OAI Identifier:oai:infocomp.dcc.ufla.br:article/138
Online Access:https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/138
Access Level:Open access
Keyword:component-based software
moving average
convolution
fast Fourier transform
Markov model.
Description
Summary:This paper introduces a moving average reliability growth model to describe the evolution of component-based software. In this model, the reliability of a system is a function of the reliabilities of its constituent components. The moving average provides a trend indicator to depict reliability growth movement within the evolution of a series of component enhancements. The moving average can reduce the effects of bias or measurement error of certain components by rendering a smoothed trend of system reliability growth. The input parameters are the components’ configurations and individual reliability growths. The output is a vector of moving averaged system reliability growths indicating increasing component enhancement. The application of this model can facilitate cost/performance evaluation and support decision making for future software maintenance. More importantly, without introducing excessive computation, the model can be combined with many existing component-based reliability models to compute overall reliability growth.