Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/51851
Title: A study of the exponential smoothing technique in software reliability growth prediction
Authors: Xie, M. 
Hong, G.Y.
Wohlin, C.
Keywords: Double exponential smoothing
Model comparison
Reliability prediction
Repairable systems
Software reliability
Issue Date: 1997
Source: Xie, M.,Hong, G.Y.,Wohlin, C. (1997). A study of the exponential smoothing technique in software reliability growth prediction. Quality and Reliability Engineering International 13 (6) : 347-353. ScholarBank@NUS Repository.
Abstract: Software reliability models can provide quantitative measures of the reliability of software systems which are of growing importance today. Most of the models are parametric ones which rely on the modelling of the software failure process as a Markov or non-homogeneous Poisson process. It has been noticed that many of them do not give a very accurate prediction of future software failures as the focus is on the fitting of past data. In this paper we study the use of the double exponential smoothing technique to predict software failures. The proposed approach is a non-parametric one and has the ability of providing more accurate prediction compared with traditional parametric models because it gives a higher weight to the most recent failure data for a better prediction of future behaviour. The method is very easy to use and requires a very limited amount of data storage and computational effort. It can be updated instantly without much calculation. Hence it is a tool that should be more commonly used in practice. Numerical examples are shown to highlight the applicability. Comparisons with other commonly used software reliability growth models are also presented. © 1997 John Wiley & Sons, Ltd.
Source Title: Quality and Reliability Engineering International
URI: http://scholarbank.nus.edu.sg/handle/10635/51851
ISSN: 07488017
Appears in Collections:Staff Publications

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