On the stability of software clustering algorithms

Abstract

A crucial step in understanding a large legacy software system is to decompose it into meaningful subsystems, which can be separately studied. This decomposition can be done either manually or automatically by a software clustering algorithm (SCA). Similar versions of a software system can be expected to have similar decompositions. We say an SCA is stable if small changes in its input (the software system) produce small changes in its output (the decomposition). The paper defines stability formally, explains why it is an essential property for an SCA, and gives experimental results from evaluating the stability of various decomposition algorithms suggested in the literature.