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CRAFT: a framework for evaluating software clustering results in the absence of benchmark decompositions [Clustering Results Analysis Framework and Tools]
Conference proceeding

CRAFT: a framework for evaluating software clustering results in the absence of benchmark decompositions [Clustering Results Analysis Framework and Tools]

B.S Mitchell and S Mancoridis
Proceedings Eighth Working Conference on Reverse Engineering
2001

Abstract

Algorithm design and analysis Clustering algorithms Computer science Documentation Mathematics Software algorithms Software maintenance Software quality Software systems Software tools
Software clustering algorithms are used to create high-level views of a system's structure using source code-level artifacts. Software clustering is an active area of research that has produced many clustering algorithms. However, we have so far seen very little work that investigates how the results of these algorithms can be evaluated objectively in the absence of a benchmark decomposition or without the active participation of the original designers of the system. Ideally, for a given system, art agreed upon reference (benchmark) decomposition of the system's structure would exist, allowing the results of various clustering algorithms to be compared against it. Since such benchmarks seldom exist, we seek alternative methods to gain confidence in the quality of results produced by software clustering algorithms. In this paper, we present a tool that supports the evaluation of software clustering results in the absence of a benchmark decomposition.

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Computer Science, Theory & Methods
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