边缘集中:一种聚类有向图的方法

F. J. Newbery
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引用次数: 34

摘要

有向图的显示是一种常用的表示关系的视觉辅助工具。然而,有些图包含太多的边,传统的图布局算法几乎不可能显示它们,因为交叉点太多了。表示大型软件系统及其配置的图形特别容易出现这个问题。此类图的示例包括:描述系统配置的图、调用图、描述模块之间导入和导出关系的图,以及描述系统源文件之间“包含”关系的图。本文提出用一个称为边集中节点的特殊节点替换具有相同源节点和目标节点集的边集,从而消除一些边。减少边的数量通常具有减少交叉次数的理想副作用。本文提出了一种算法,该算法在图中每个级别的&Ogr;(n4)操作中确定图的合理边缘集中集,其中n为该级别的节点数。软件配置管理领域的几个例子展示了使用边缘集中的有效性。
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Edge concentration: a method for clustering directed graphs
The display of a directed graph is a commonly used visual aid for representing relationships. However, some graphs contain so many edges that their display by traditional graph layout algorithms is virtually impossible because of the overwhelming number of crossings. Graphs representing large software systems and their configurations are particularly prone to this problem. Examples of such graphs include: graphs depicting a system's configuration, call graphs, graphs depicting import and export relationships between modules, and graphs depicting the “includes” relation among a system's source files. This paper proposes the elimination of some edges by replacing sets of edges that have the same set of source and target nodes by a special node called an edge concentration node. Reducing the number of edges often has the desirable side effect of reducing the number of crossings. An algorithm that determines a reasonable set of edge concentrations of a graph in &Ogr;(n4) operations for each level in the graph is presented where n is the number of nodes in that level. Several examples from the area of software configuration management are shown to demonstrate the effectiveness of using edge concentrations.
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