Abstract
Recent work in fault localization crosschecks traces of correct and failing execution traces. The implicit underlying technique is to search for association rules which indicate that executing a particular source line will cause the whole execution to fail. This technique, however, has limitations. In this article, we first propose to consider more expressive association rules where several lines imply failure. We then propose to use Formal Concept Analysis (FCA) to analyze the resulting numerous rules in order to improve the readability of the information contained in the rules. The main contribution of this article is to show that applying two data mining techniques, association rules and FCA, produces better results than existing fault localization techniques.
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Cellier, P., Ducassé, M., Ferré, S., Ridoux, O. (2008). Formal Concept Analysis Enhances Fault Localization in Software. In: Medina, R., Obiedkov, S. (eds) Formal Concept Analysis. ICFCA 2008. Lecture Notes in Computer Science(), vol 4933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78137-0_20
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DOI: https://doi.org/10.1007/978-3-540-78137-0_20
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