DocumentCode :
2776540
Title :
Fuzzy Clustering of Open-Source Software Quality Data: A Case Study of Mozilla
Author :
Dick, Scott ; Sadia, Aina
Author_Institution :
Univ. of Alberta, Edmonton
fYear :
0
fDate :
0-0 0
Firstpage :
4089
Lastpage :
4096
Abstract :
We present a fuzzy cluster analysis of software quality data extracted from the Mozilla open-source Web browser. This is a new dataset that combines object-oriented software quality metrics with the number of defects per code unit. We undertake a fuzzy cluster analysis of this dataset, which for the first time addresses the use of both hyperspherical and hyperellipsoidal fuzzy clusters (using the Gath-Geva algorithm) in software quality analysis. Using a Pareto analysis based on the fuzzy clusters, we were able to identify groups of modules having higher defect densities than would be found by merely ranking modules based on any single software metric.
Keywords :
Pareto analysis; object-oriented programming; online front-ends; pattern clustering; public domain software; software metrics; software quality; Mozilla open-source Web browser; Pareto analysis; fuzzy cluster analysis; object-oriented software quality metrics; open-source software quality data; Algorithm design and analysis; Computer aided software engineering; Computer bugs; Data mining; Open source software; Pareto analysis; Quality management; Software engineering; Software metrics; Software quality; Data mining; Fuzzy clustering; Object-oriented software; Software metrics; Software quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246954
Filename :
1716663
Link To Document :
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