There exists a need for tools to help identify the authorship of source code. This includes situations in which the

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.

No abstract

Managers are often unable to explain objectively why or when effort was misplaced during the development process. In this paper, we present a formal technique to depict the expended effort during the life-cycle of a software feature using feature development manifolds (FDMs). Using the FDMs we can compute the preferred development path for a given feature. This development path includes the versions of a software feature that contributed to the final version of the feature in a positive way. The preferred development path excludes versions of the software feature that should have been skipped. Once the preferred development path is computed the amount of wasted effort can be quantified using the metric that we have developed. We demonstrate the effectiveness of our approach to compute wasted software feature development by applying our technique to two large open source software systems, Gaim and Firefox.