By Topic

Predicting C++ program quality by using Bayesian belief networks

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)
Masoud, F.A.M. ; Comput. Inf. Syst. Dept., Univ. of Jordan, Amman, Jordan ; Shaikh, M.U. ; Rabab'ah, O.M.A.

There have been many attempts to build models for predicting the software quality. Such models are used to measure the quality of software systems. The key variables in these models are either size or complexity metrics. There are, however, serious statistical and theoretical difficulties with these approaches. By using Bayesian belief network, we can overcome some of the more serious problems by taking more quality factors, which have direct or indirect impact on the software quality. In this paper, we have suggested a model to predicting the computer program quality by using Bayesian belief network. We found that the implementation of all quality factors were not feasible. Therefore, we have selected 14 quality factors to be implemented on an average size of two C++ programs. The selection criteria were based on the reviewer's opinions. Each node on the given Bayesian believe network represents one quality factor. We have drawn the BBN for the two C++ programs considering 14 nodes. The BBN has been constructed. The model has been executed and the results have been discussed.

Published in:

Information and Communication Technologies: From Theory to Applications, 2004. Proceedings. 2004 International Conference on

Date of Conference:

19-23 April 2004