面向对象程序的调用图构造算法对自动聚类的影响

Derek Rayside, Steve Reuss, Erik Hedges, K. Kontogiannis
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引用次数: 36

摘要

调用图通常用作自动聚类算法的输入,其目标是提取所研究程序的高级结构。确定过程程序的调用图是相当简单的。然而,由于多态的原因,用面向对象语言编写的程序就不是这样了。近年来,编译器优化文献中出现了许多面向对象程序调用图的静态构造算法。我们研究了这三种算法对Java专家系统外壳(JESS)自动聚类的影响。面向对象的程序比用过程语言编写的程序具有更丰富的结构,因此即使是中等规模的程序(如JESS)也会生成大型图形。我们所知道的现有工具无法处理这样的图形。因此,我们开发了自己的自动聚类算法,可扩展到大型图。该算法还通过使用“加权”弧线来支持用户指定的约束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The effect of call graph construction algorithms for object-oriented programs on automatic clustering
Call graphs are commonly used as input for automatic clustering algorithms, the goal of which is to extract the high level structure of the program under study. Determining the call graph for a procedural program is fairly simple. However this is not the case for programs written in object oriented languages, due to polymorphism. A number of algorithms for the static construction of an object oriented program's call graph have been developed in the compiler optimization literature in recent years. We investigate the effect of three such algorithms on the automatic clustering of the Java Expert System Shell (JESS). Object oriented programs have an inherently richer structure than those written in procedural languages, and so even medium sized programs such as JESS produce large graphs. Existing tools that we are aware of are not able to process such graphs. Consequently, we have developed our own algorithm for automatic clustering that is scalable to large graphs. This algorithm also supports user specified constraints through the use of 'weighted' arcs.
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