摘要
现有的方面挖掘技术一般是类的方法级的挖掘,侧重于软件系统的结构改造,不能直接解决面向方面编程所关注的语句级代码纠缠和代码分散问题.针对这种情况,本文提出了一种基于形式概念分析的语句级自动化方面挖掘方法.该方法使用形式概念分析识别源代码中的关注点,实现语句级的自动化方面挖掘.该方法具有自动化、语句级和效率高等特点,可以用来快速实现对遗留系统的面向方面的改造.
Current aspect mining technologies usually focus on mining of method eodes in classes. They make great efforts to restructure software systems. However, they cannot directly solve the two statement-level problems that are important in aspect-oriented programming named ＂code tangling＂ and ＂ceode spreading＂. In order to solve these problems, this paper presents a formal concept analysis--based statement-level automatic aspect mining method. The method uses formal concept analysis to identify concerns and achieves a statement-level automatic aspect mining. This method has many features, such as automation, statement-level and high efficiency. It can be used in rapid reconstruction of legacy systems in an aspect-oriented style.
出处
《小型微型计算机系统》
CSCD
北大核心
2006年第4期677-680,共4页
Journal of Chinese Computer Systems
基金
吉林省科技发展计划项目(20050527)资助
关键词
方面挖掘
形式慨念分析
面向方面编程
aspect mining
formal concept analysis
aspect-oriented programming
