Software Reliability Prediction Using Predictive Filter


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 7, No. 7, pp. 2076-2085, Jul. 2000
10.3745/KIPSTE.2000.7.7.2076,   PDF Download:

Abstract

Almost all existing software reliability models are based on the assumptions of the software usage and software failure process. There, therefore, is no universally applicable software reliability model. To develop a universal software reliability model, this paper suggests the predictive filter as a general software reliability prediction model for time domain failure data. Its usefulness is empirically verified by analyzing the failure data sets obtained from 14 different software projects. Based on the average relative prediction error, the suggested predictive filter is compared with other well-known neural network models and statistical software reliability growth models. Experimental results show that the predictive filter generally results in a simple model and adapts well across different software projects.


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Cite this article
[IEEE Style]
J. Y. Park, S. U. Lee, J. H. Park, "Software Reliability Prediction Using Predictive Filter," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 7, no. 7, pp. 2076-2085, 2000. DOI: 10.3745/KIPSTE.2000.7.7.2076.

[ACM Style]
Joong Yang Park, Sang Un Lee, and Jae Heung Park. 2000. Software Reliability Prediction Using Predictive Filter. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 7, 7, (2000), 2076-2085. DOI: 10.3745/KIPSTE.2000.7.7.2076.