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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Active Mining of Document Type Definitions
verfasst von : Markus Frohme, Bernhard Steffen
Erschienen in: Formal Methods for Industrial Critical Systems
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Abstract
In this paper, we present the application of our active learning algorithm for Systems of Procedural Automata (SPAs) for inferring Document Type Definitions (DTDs) via testing of corresponding document validators. The point of this specification mining approach is to reveal unknown (lost or hidden) syntactic document constraints that are automatically imposed by document validators in order to support document writers or to validate whether a certain validator implementation does indeed satisfy its specification. This is particularly interesting in the context of today’s General Data Protection Regulation (GDPR) as their violation might lead to substantial penalties. The practicality of this approach is supported by the fact that for inferred complex DTDs, context-free model checking may be used to automatically validate whether business-critical rules are enforced by a validator and therefore automatically prohibited by a corresponding documentation process once and for all.