An architecture for distributing the computation of software clustering algorithms

Abstract

Collections of general purpose networked workstations offer processing capability that often rivals or exceeds supercomputers. Since networked workstations are readily available in most organizations, they provide an economic and scalable alternative to parallel machines. The authors discuss how individual nodes in a computer network can be used as a collection of connected processing elements to improve the performance of a software engineering tool that we developed. Our tool, called Bunch, automatically clusters the structure of software systems into a hierarchy of subsystems. Clustering helps developers understand complex systems by providing them with high-level abstract (clustered) views of the software structure. The algorithms used by Bunch are computationally intensive and, hence, we would like to improve our tool's performance in order to cluster very large systems. The paper describes how we designed and implemented a distributed version of Bunch, which is useful for clustering large systems.