We present an open framework for visual mining of CVS software repositories. We address three aspects: data extraction, analysis and visualization. We first discuss the challenges of CVS data extraction and storage, and propose a flexible way to deal with CVS implementation inconsistencies. We next present a new technique to enrich the raw data with information about artifacts showing similar evolution. Finally, we propose a visualization backend and show its applicability on industry-size repositories.
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