DocumentCode :
3164522
Title :
Hierarchical clustering for adaptive refactorings identification
Author :
Czibula, Istvan Gergely ; Czibula, Gabriela
Author_Institution :
Babes-Bolyai Univ., Cluj-Napoca, Romania
Volume :
3
fYear :
2010
fDate :
28-30 May 2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper studies an adaptive refactoring problem. It is well-known that improving the software systems design through refactoring is one of the most important issues during the evolution of object oriented software systems. We focus on identifying the refactorings needed in order to improve the class structure of a software systems, in an adaptive manner, when new application classes are added to the system. We propose an adaptive clustering method based on an hierarchical agglomerative approach, that adjusts the structure of the system that was established by applying a hierarchical agglomerative clustering algorithm before the application classes set changed. The adaptive method identifies, more efficiently, the refactorings that would improve the structure of the extended software system, without decreasing the accuracy of the obtained results. An experiment testing the method´s efficiency is also reported.
Keywords :
object-oriented programming; pattern clustering; software maintenance; adaptive refactorings identification; application classes set; hierarchical agglomerative clustering algorithm; object oriented software systems; software systems design; Adaptive systems; Application software; Clustering algorithms; Clustering methods; Production; Programming; Software algorithms; Software design; Software systems; Software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Quality and Testing Robotics (AQTR), 2010 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4244-6724-2
Type :
conf
DOI :
10.1109/AQTR.2010.5520668
Filename :
5520668
Link To Document :
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