Extending dynamic aspect mining with static information

S. Breu
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引用次数: 25

Abstract

Aspect mining tries to identify crosscutting concerns in legacy systems and thus supports the refactoring into an aspect-oriented design. We briefly introduce DynAMiT, a dynamic aspect mining tool that detects crosscutting concerns based on tracing method executions. While the approach is generally fairly precise, further analysis revealed that some false positives were systematically caused by dynamic binding. Furthermore, some aspect candidates were blurred or not detected due to not-sufficient tracing mechanisms of method executions when using AspectJ's execution pointcuts for the trace generation. We enhanced the mining capabilities of DynAMiT by taking additional static type information into account and generating the traces using call pointcuts instead. In an initial case study with AnChoVis, a 1300 LOC Java program, the number of mined aspect candidates increased by a factor of three, while the number of false positives remained zero.
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用静态信息扩展动态方面挖掘
方面挖掘试图识别遗留系统中的横切关注点,从而支持重构为面向方面的设计。我们简要介绍DynAMiT,这是一种动态方面挖掘工具,可以根据跟踪方法执行来检测横切关注点。虽然这种方法通常相当精确,但进一步的分析表明,一些误报是由动态绑定系统地引起的。此外,在使用AspectJ的执行切入点进行跟踪生成时,由于方法执行的跟踪机制不充分,一些方面候选被模糊或未被检测到。通过考虑额外的静态类型信息并使用调用切入点生成跟踪,我们增强了DynAMiT的挖掘能力。在使用anchvis(一个1300 LOC的Java程序)的初始案例研究中,挖掘的方面候选数增加了三倍,而假阳性数保持为零。
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