Mining open source software (OSS) data using association rules network

Authors:
Sanjay Chawla;Bavani Arunasalam;Joseph Davis
Affiliations:
Knowledge Management Research Group, School of Information Technologies, University of Sydney, NSW, Australia;Knowledge Management Research Group, School of Information Technologies, University of Sydney, NSW, Australia;Knowledge Management Research Group, School of Information Technologies, University of Sydney, NSW, Australia
Venue:
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2003

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Abstract

The Open Source Software(OSS) movement has attracted considerable attention in the last few years. In this paper we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we introduce Association Rules Network(ARN), a (hyper)graphical model to represent a special class of association rules. Using ARNs we discover important relationships between the attributes of successful OSS projects. We verify and validate these relationships using Factor Analysis, a classical statistical technique related to Singular Value Decomposition(SVD).