loading...
An Application of Zero-Inflated Poisson Regression for Software Fault Prediction
Hong Kong, China November 27-November 30
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISSRE.2001.98945912th International Symposium on Softw ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Poisson regression model is widely used in software quality modeling. When the response variable of a data set includes a large number of zeros, Poisson regression model will underestimate the probability of zeros. A zero-inflated model changes the mean structure of the pure Poisson model. The predictive quality is therefore improved. In this paper, we examine a full-scale in-dustrial software system and develop two models, Poisson regression and zero-inflated Poisson regression. To our knowledge, this is the first study that introduces the zero-inflated Poisson regression model in software reliability. Comparing the predictivequalities of the two competing models, we conclude that for this system, the zero-inflated Poisson regression model is more appropriate in theory and practice.
Index Terms:
Software quality modeling, Poisson regression model, zero-inflated Poisson regression model, nested models, Vuong hypothesis test, program module.
Citation:
Taghi Khoshgoftaar, Kehan Gao, Robert M. Szabo, "An Application of Zero-Inflated Poisson Regression for Software Fault Prediction," issre, pp.66, 12th International Symposium on Software Reliability Engineering (ISSRE'01), 2001
Usage of this product signifies your acceptance of the Terms of Use.