5 research outputs found

    A Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic

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    The Bernays-Sch\"onfinkel first-order logic fragment over simple linear real arithmetic constraints BS(SLR) is known to be decidable. We prove that BS(SLR) clause sets with both universally and existentially quantified verification conditions (conjectures) can be translated into BS(SLR) clause sets over a finite set of first-order constants. For the Horn case, we provide a Datalog hammer preserving validity and satisfiability. A toolchain from the BS(LRA) prover SPASS-SPL to the Datalog reasoner VLog establishes an effective way of deciding verification conditions in the Horn fragment. This is exemplified by the verification of supervisor code for a lane change assistant in a car and of an electronic control unit for a supercharged combustion engine.Comment: 26 page

    A Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic

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    International audienceThe Bernays-Schönfinkel first-order logic fragment over simple linear real arithmetic constraints BS(SLR) is known to be decidable. We prove that BS(SLR) clause sets with both universally and existentially quantified verification conditions (conjectures) can be translated into BS(SLR) clause sets over a finite set of first-order constants. For the Horn case, we provide a Datalog hammer preserving validity and satisfiability. A toolchain from the BS(LRA) prover SPASS-SPL to the Datalog reasoner VLog establishes an effective way of deciding verification conditions in the Horn fragment. This is exemplified by the verification of supervisor code for a lane change assistant in a car and of an electronic control unit for a supercharged combustion engine

    VLog: A Rule Engine for Knowledge Graphs

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    Knowledge graphs are crucial assets for tasks like query answering or data integration. These tasks can be viewed as reasoning problems, which in turn require efficient reasoning systems to be implemented. To this end, we present VLog, a rule-based reasoner designed to satisfy the requirements of modern use cases, with a focus on performance and adaptability to different scenarios. We address the former with a novel vertical storage layout, and the latter by abstracting the access to data sources and providing a platform-independent Java API. Features of VLog include fast Datalog materialisation, support for reasoning with existential rules, stratified negation, and data integration from a variety of sources, such as high-performance RDF stores, relational databases, CSV files, OWL ontologies, and remote SPARQL endpoints
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