识别、分配和量化横切关注点

M. Eaddy, A. Aho, G. Murphy
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引用次数: 91

摘要

横切关注点会降低软件质量。在我们能够模块化程序中的横切关注点以提高软件质量之前,我们必须首先能够找到它们。不幸的是,准确定位与关注点相关的代码是很困难的,而且没有适当的度量,确定关注点横切的程度是不可能的。我们提出了一种系统的方法,用于识别哪个代码与哪个关注点相关,以及一套用于量化横切代码数量的度量。我们的关注识别和分配指南解决了其他研究者遇到的一些模棱两可的问题。我们应用这种方法系统地识别13531行程序中的所有需求。我们发现95%的关注点是横切的——这表明了改进模块化的巨大潜力——并且我们的度量能够更好地确定哪些关注点将从重构中获益最多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying, Assigning, and Quantifying Crosscutting Concerns
Crosscutting concerns degrade software quality. Before we can modularize the crosscutting concerns in our programs to increase software quality, we must first be able to find them. Unfortunately, accurately locating the code related to a concern is difficult, and without proper metrics, determining how much the concern is crosscutting is impossible. We propose a systematic methodology for identifying which code is related to which concern, and a suite of metrics for quantifying the amount of crosscutting code. Our concern identification and assignment guidelines resolve some of the ambiguity issues encountered by other researchers. We applied this approach to systematically identify all the requirement concerns in a 13,531 line program. We found that 95% of the concerns were crosscutting - indicating a significant potential for improving modularity - and that our metrics were better able to determine which concerns would benefit the most from reengineering.
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