About: Automated Generation of Consistent Graph Models with First-Order Logic Theorem Provers

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Automated Generation of Consistent Graph Models with First-Order Logic Theorem Provers
Creator	Babikian, Aren Semeráth, Oszkár Varró, Dániel
Source	PMC
abstract	The automated generation of graph models has become an enabler in several testing scenarios, including the testing of modeling environments used in the design of critical systems, or the synthesis of test contexts for autonomous vehicles. Those approaches rely on the automated construction of consistent graph models, where each model satisfies complex structural properties of the target domain captured in first-order logic predicates. In this paper, we propose a transformation technique to map such graph generation tasks to a problem consisting of first-order logic formulae, which can be solved by state-of-the-art TPTP-compliant theorem provers, producing valid graph models as outputs. We conducted performance measurements over all 73 theorem provers available in the TPTP library, and compared our approach with other solver-based approaches like Alloy and VIATRA Solver.
has issue date	2020-03-13(xsd:dateTime)
bibo:doi	10.1007/978-3-030-45234-6_22
has license	cc-by
sha1sum (hex)	4ac16c2d4da1993271a539431d90dd4c441087ac
schema:url	https://doi.org/10.1007/978-3-030-45234-6_22
resource representing a document's title	Automated Generation of Consistent Graph Models with First-Order Logic Theorem Provers
has PubMed Central identifier	PMC7418127
schema:publication	Fundamental Approaches to Software Engineering
resource representing a document's body	covid:4ac16c2d4da1993271a539431d90dd4c441087ac#body_text
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