Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

Evaluating relationship categories for clustering object-oriented software systems

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 $31
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)
Muhammad, S. ; Dept. of Comput. Sci., Shaheed Benazir Bhutto Univ., Sheringle, Pakistan ; Maqbool, O. ; Abbasi, A.Q.

Various techniques have been proposed for the automatic modularisation and architecture recovery of software systems. These techniques usually employ an algorithm to form clusters of similar entities. Similarity between entities is based on their characteristics, and is often determined by the relationships that exist between them. When using automatic techniques, selecting a suitable algorithm and appropriate relationships are challenging issues, and have a significant influence on the quality of results. Although researchers have employed different algorithms for modularising object-oriented software systems, there has been relatively little work to determine which relationships produce better modularisation results. The authors evaluate in this study a large number of relationships that may exist between entities in an object-oriented system, by dividing the relationships into different categories. For modularisation, experiments are conducted using multiple hierarchical clustering algorithms. The experimental results indicate the relationships that improve the quality of results for the algorithms, and thus may be considered more important for software clustering.

Published in:

Software, IET  (Volume:6 ,  Issue: 3 )