Community Detection in Directed Weighted Function-call Networks

Abstract

Complex network is being considered as a key approach to representing complex systems. We have focused on the static analyses of software systems with the function-call graph and empirically found them to reveal small-world, scale-free features similar to those identified in sociological and technological systems. Another crucial step when studying the structure of networks is to identify communities. Most existing approach to this problem in the previous literature simply ignored the edge direction and applied methods for community detecting in undirected networks. In this paper, we consider the problem of finding communities in directed weighted networks and develop a new community detection algorithm for the networks. Our method regards communities as groups of links rather than nodes in contrast to the existing detection algorithms. This algorithm is tested on function-call graph of artificial system and our experiment is shown to finding communities on the test directed weighted network successfully.