计算机科学 ›› 2017, Vol. 44 ›› Issue (4): 75-78.doi: 10.11896/j.issn.1002-137X.2017.04.016

• NASAC 2015 • 上一篇    下一篇

一种基于层次聚类的软件架构恢复方法

李寒,佟宁,陈峰   

  1. 北方工业大学计算机学院 北京100144;大规模流数据集成与分析技术北京市重点实验室 北京100144,大连交通大学软件学院 大连116052,德蒙特福德大学计算机与信息工程学院 莱斯特LE1 9BH
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受北京市教委科技计划面上项目(KM2015_10009007),北京市优秀人才培养资助

Hierarchical Clustering Based Software Architecture Recovery Approach

LI Han, TONG Ning and CHEN Feng   

  • Online:2018-11-13 Published:2018-11-13

摘要: 针对软件聚类侧重相似度测度而欠缺考虑实体和特征的特性的问题,提出一种基于层次聚类的软件架构恢复方法(HCSAR)。该方法有针对性地选取实体和特征,提出特征的多重加权策略,采用信息丢失度作为相似度测度,选取和设计软件聚类的客观和主观评估准则。与目前效果较好的软件聚类方法相比,HCSAR在聚类中期能生成更多的簇,主观判定数更低,能够通过调整关注点获得不同的聚类结果,使用设计的评估准则分析聚类结果还能有效辅助系统划分。

关键词: 层次聚类,架构恢复,面向对象,面向过程,系统划分

Abstract: To solve the problem of the lack of consideration of the characteristics of entities and features,a hierarchical clustering based software architecture recovery approach was proposed.Targeted entities and features were selected,weight scheme was proposed to generate feature vectors,information loss was considered as the similarity metric,and objective and subjective evaluation measures were respectively chosen and given.Compared with superior agglomerative software clustering approaches,HCSAR is more cohesive,requires less arbitrary decisions,is flexible to adjust the focus of software clustering,and is able to assist to generate more accurate system partition.

Key words: Hierarchical clustering,Architecture recovery,Object orientation,Procedure orientation,System partition

[1] BIBI M,MAQBOOL O.Version information support for software architecture recovery[C]∥Proceedings of the 7th International Conference on Emerging Technologies,2011.Islamabad:IEEE,2011:1-6.
[2] LI Q S,CHEN P.Implementing architecture recovery by using improved genetic Algorithm[J].Journal of Software,2003,4(7):1221-1228.(in Chinese) 李青山,陈平.用改进的遗传算法实现架构恢复[J].软件学报,2003,14(7):1221-1228.
[3] YANG Q,ZHANG L P.The research on software architecture recovery based on pattern matching[J].Computer Application and Software,2006,3(4):27-29.(in Chinese) 杨清,张礼平.基于模式匹配的软件架构恢复的研究[J].计算机应用与软件,2006,3(4):27-29.
[4] SIDDIQUE F,MAQBOOL O.Enhancing comprehensibility of software clustering results[J].Software,IET,2012,6(4):283-295.
[5] MAQBOOL O,BABRI H.Hierarchical clustering for softwarearchitecture recovery[J].IEEE Transactions on Software Engineering,2007,33(11):759-780.
[6] CHOT S,CHA S,TAPPERT C.A survey of binary similarity distance measures[J].Journal of Systemics,Cybernetics and Informatics,2010,8(1):43-48.
[7] SAEED M,MAQBOOL O,BABRI H,et al.Software clustering techniques and the use of the combined algorithm[J].Journal of Software Maintenance and Evolution:Research and Practice,2003,6(4-5):301-306.
[8] MAQBOOL O,BABRI H.The weighted combined algorithm:a linkage algorithm for software clustering[C]∥Proceedings of the 8th European Conference on Software Maintenance and Reen-gineering,2004.Los Alamitos,Calif.:IEEE Computer Society,2004:15-24.
[9] ANDRITSOS P,TZPERPOS V.Information theoretic software clustering[J].IEEE Transactions on Software Engineering,2005,31(2):150-165.
[10] NASEEM R,BIN M,MAQBOOL O.Software modulariza-tion using combination of multiple clustering[C]∥Proceedings of IEEE 17th International Conference on Multi-Topic Confe-rence,2004.Karachi:IEEE,2014:277-281.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!