On Computing the Canonical Features of Software Systems

Abstract

Software applications typically have many features that vary in their similarity. We define a measurement of similarity between pairs of features based on their underlying implementations and use this measurement to compute a set of canonical features. The canonical features set (CFS) consists of a small number of features that are as dissimilar as possible to each other, yet are most representative of the features that are not in the CFS. The members of the CFS are distinguishing features and understanding their implementation provides the engineer with an overview of the system undergoing scrutiny. The members of the CFS can also be used as cluster centroids to partition the entire set of features. Partitioning the set of features can simplify the understanding of large and complex software systems. Additionally, when a specific feature must undergo maintenance, it is helpful to know which features are most closely related to it. We demonstrate the utility of our method through the analysis of the Jext, Firefox, and Gaim software systems