Software Architecture Reconstruction Through Clustering: Finding the Right Similarity Metric
نویسنده
چکیده
Clustering is very often used for the purpose of architectural reconstruction. This article proposes an approach of improving the quality of automatic software architecture reconstruction results. This work investigates the importance of taking into account the right factors for the similarity metric: the strength of direct coupling/cohesion between classes, indirect coupling as computed from the topology of the dependency graph, and global architectural layering resulting from the orientation of dependencies. These factors are considered individually or combined as similarity metrics and used within a set of clustering algorithms.
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