By Topic

Software quality knowledge discovery: a rough set approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ramanna, S. ; Dept. of Bus. Comput., Manitoba Univ., Winnipeg, Man., Canada ; Peters, J.F. ; Taechon Ahn

This paper presents a practical knowledge discovery approach to software quality and resource allocation that incorporated recent advances in rough set theory, parameterized approximation spaces and rough neural computing. In addition, this research utilizes the results of recent studies of software quality measurement and prediction. A software quality measure quantifies the extent, to which some specific attribute is present in a system. Such measurements are considered in the context of rough sets. This research provides a framework for making resource allocation decisions based on evaluation of various measurements of the complexity of software. Knowledge about software quality is gained when preprocessing during which, software measurements are analyzed using discretization techniques, genetic algorithms in deriving reducts, and in the derivation of training and testing sets, especially in the context of the rough sets exploration system (RSES) developed by the logic group at the Institute of Mathematics at Warsaw University. Experiments show that both RSES and rough neural network models are effective in classifying software modules.

Published in:

Computer Software and Applications Conference, 2002. COMPSAC 2002. Proceedings. 26th Annual International

Date of Conference:

2002