Architecture-Aware Adaptive Clustering of OO Systems

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Architecture-Aware Adaptive Clustering of OO Systems
The recovery of software architecture is a first important step towards re-engineering a software system. Architecture recovery usually involves clustering. The problem with current clustering techniques is that they decide exclusively based on syntactic dependencies instead of looking at higher-level semantic information. As a result, the recovered architecture is not always meaningful to a human software engineer. In this paper, we propose an approach that combines clustering with pattern-matching techniques to recover meaningful decompositions. Pattern-matching is used to identify architectural clues -- small structural patterns that provide semantic information to allow for a rating of the dependencies found between a system's entities. These clues are used to compute an adaptive inter-class similarity measure which is then used by a clustering algorithm to produce the final system decomposition.
Markus Bauer, Mircea Trifu
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where CSMR
Authors Markus Bauer, Mircea Trifu
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