Mining composite crosscutting concerns based on graph clustering

被引：0

作者：

Huang, Jin ^{[1
]}

Zhu, Jianlin ^{[2
]}

Lu, Yansheng ^{[3
]}

机构：

[1] 709 Research Institute, China Shipbuilding Industry Corporation, Wuhan

[2] School of Computer Science and Technology, South-Central University for Nationalities, Wuhan

[3] School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan

来源：

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2015年 / 43卷 / 04期

关键词：

Aspect mining; Composite crosscutting concern; Directed graph; Graph clustering; Software module; Software system;

D O I：

10.13245/j.hust.150424

中图分类号：

学科分类号：

摘要：

A graph clustering technique was adopted to obtain composite crosscutting concerns consisting of several program elements. Our graph clustering technique considers not only the connectivity between program elements, but also the similarity between them. A composite crosscutting concern is still a software module, which consists of strongly connected program elements and similar ones. Taking advantage of both connectivity and similarity, a directed graph clustering approach was proposed based on authority-shift approach for finding software modules. Fan-in technique was adopted to identify composite crosscutting concerns. Comparing with various clustering methods through experiments, our approach is more effective in identifying crosscutting concerns. ©, 2015, Huazhong University of Science and Technology. All right reserved.

引用

页码：118 / 122

页数：4

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