SOFTWARE ARCHITECTURE DECOMPOSITION USING ADAPTIVE K-NEAREST NEIGHBOR ALGORITHM

被引：0
|
作者：
Alkhalid, Abdulaziz [1 ]
Lung, Chung-Horng [1 ]
Ajila, Samuel [1 ]
机构：
[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
来源：
2013 26TH ANNUAL IEEE CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE) | 2013年
关键词：
Design; Software Architecture; Clustering; Pattern Recognition; Algorithms; CLUSTERING-TECHNIQUES;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Software architecture decomposition plays an important role in software design cascading effect on various development phases. Software designer decomposes software based on his/her experience. Though it may work well for some, in reality many systems failed to meet the requirements as a result of poor design. Software architecture decomposition using clustering techniques has been investigated in software engineering research. This paper presents an enhanced approach for software architecture decomposition. We used two hierarchical agglomerative clustering methods and adaptive K-nearest neighbor algorithm in this enhanced approach and applied it on two industrial software systems. Results show that the approach provides objective and insightful information for software designer.
引用
收藏
页码：676 / 679
页数：4
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