Mining Patterns and Violations Using Concept Analysis
Christian Lindig** Testfabrik AG, Saarbrücken, Germany
Large programs develop patterns in their implementation and behavior that can be used for defect mining. Previous work used frequent itemset mining to detect such patterns and their violations, which correlate with defects. However, frequent itemset mining gives much more attention to patterns than to the instances of these patterns. We propose a more general framework to understand and mine purely structural patterns and violations. By combining patterns and their instances into blocks, we gain access to the rich theory of formal concepts. This results in a novel geometric interpretation, which helps to understand ...
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