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基于动态行为和模糊识别的Aspect挖掘方法

Aspect Mining Method Based on Dynamic Behavior and Fuzzy Recognition
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摘要 横切关注点是指分布在多个单元模块的功能代码,面向方面的编程是解决传统编程过程中横切问题的重要方法之一,其中一个重要问题是如何从现有系统中发现横切关注点。该文提出一种基于动态行为和模糊模式识别的Aspect挖掘方法,通过引入Aspect获取运行时方法调用的信息,使程序具有自动收集动态信息的能力,并利用模糊理论识别系统中的横切关注点。实验验证了该方法的有效性和实现的简洁性。 Crosscutting concerns are functionalities that distribute in many modular units, and Aspect-oriented Programming（AOP） is one of the most effective methods to solve this problem. An important question in AOP is how to identify crosscutting concerns from object oriented legacy system. A method based on dynamic behavior and fuzzy pattern recognition for Aspect mining is presented. The method uses Aspect to capture the runtime method for calling information and providing the ability of auto-collecting dynamic information. It uses fuzzy pattern recognition to identify the crosscutting concerns. An experiment is conducted in order to verify the validity of the method. The implementation of this method is simple and succinct.
作者 刘引 曾一 洪媛 王海波 李强 陈传超 吴光金 王健
机构地区 重庆大学计算机学院
出处 《计算机工程》 CAS CSCD 北大核心 2009年第6期52-54,共3页 Computer Engineering
关键词 面向方面编程 ASPECT挖掘 模糊模式识别 Aspect-oriented Programming（AOP） Aspect mining fuzzy pattern recognition
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献6

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共引文献36

计算机工程
2009年 第6期

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