Component rank: relative significance rank for software component search

Abstract

Collections of already developed programs are important resources for efficient development of reliable software systems. In this paper, we propose a novel method of ranking software components, called Component Rank, based on analyzing actual use relations among the components and propagating the significance through the use relations. We have developed a component-rank computation system, and applied it to various Java programs. The result is promising such that non-specific and generic components are ranked high. Using the Component Rank system as a core part, we are currently developing Software Product Archiving, analyzing, and Retrieving System named SPARS.