An Application of Fuzzy Clustering to Software Quality Prediction

Authors:
Xiaohong Yuan;Taghi M. Khoshgoftaar;Edward B. Allen;K. Ganesan
Affiliations:
-;-;-;-
Venue:
ASSET '00 Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET'00)
Year:
2000

Citing 0
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Abstract

The ever-increasing demand for high software reliability requires more robust modeling techniques for software quality prediction. This paper presents a modeling technique that integrates fuzzy subtractive clustering with module-order modeling for software quality prediction. First fuzzy subtractive clustering is used to predict the number of faults, then module-order modeling is used to predict whether modules are fault-prone or not. Note that multiple linear regressions are a special case of fuzzy subtractive clustering.We conducted a case study of a large legacy telecommunication system to predict whether each module will be considered fault-prone. The case study found that using fuzzy subtractive clustering and module-order modeling, one can classify modules which will likely have faults discovered by customers with useful accuracy prior to release.