基于聚类的方面挖掘

2008 4th International Conference on Intelligent Computer Communication and Processing Pub Date : 2008-10-10 DOI:10.1109/ICCP.2008.4648364

G. Cojocar, G. Czibula

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引用次数: 13

摘要

聚类是将数据分成相似对象的组。方面挖掘是一个试图识别现有软件系统中横切关注点的过程。我们的目标是重构现有的系统，以使用面向方面的编程，从而使它们更容易维护和发展。本文的目的是对方面挖掘中不同聚类算法得到的结果进行比较分析和评价。评估是在一个开源案例研究中使用四个度量来执行的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On clustering based aspect mining

Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify crosscutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming in order to make them easier to maintain and to evolve. The aim of this paper is to comparatively analyze and evaluate the results obtained by different clustering algorithms in aspect mining. The evaluation is performed on an open source case study using four measures.

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2008 4th International Conference on Intelligent Computer Communication and Processing

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