DocumentCode :
1824080
Title :
An empirical study of the impact of count models predictions on module-order models
Author :
Khoshgoftaar, T. Aghi M ; Geleyn, Erik ; Gao, Kehan
Author_Institution :
Florida Atlantic Univ., Boca Raton, FL, USA
fYear :
2002
fDate :
2002
Firstpage :
161
Lastpage :
172
Abstract :
Software quality prediction models are used to achieve high software reliability. A module-order model (MOM) uses an underlying quantitative prediction model to predict this rank-order. This paper compares performances of module-order models of two different count models which are used as the underlying prediction models. They are the Poisson regression model and the zero-inflated Poisson regression model. It is demonstrated that improving a count model for prediction does not ensure a better MOM performance. A case study of a full-scale industrial software system is used to compare performances of module-order models of the two count models. It was observed that improving prediction of the Poisson count model by using zero-inflated Poisson regression did not yield module-order models with better performance. Thus, it was concluded that the degree of prediction accuracy of the underlying model did not influence the results of the subsequent module-order model. Module-order modeling is proven to be a robust and effective method even though both underlying prediction may sometimes lack acceptable prediction accuracy.
Keywords :
software metrics; software performance evaluation; software quality; software reliability; count models; module-order modeling; software metrics; software performance evaluation; software quality prediction model; software reliability; zero-inflated Poisson regression model; Accuracy; Computer industry; Economic forecasting; Fuzzy logic; Message-oriented middleware; Predictive models; Q factor; Software metrics; Software quality; Software systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Metrics, 2002. Proceedings. Eighth IEEE Symposium on
ISSN :
1530-1435
Print_ISBN :
0-7695-1339-5
Type :
conf
DOI :
10.1109/METRIC.2002.1011335
Filename :
1011335
Link To Document :
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