Modeling Ontological Structures with Type Classes in Coq

Dapoigny, Richard; Barlatier, Patrick

doi:10.1007/978-3-642-35786-2_11

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…In [21], the authors present a two-layered language ground on higher-order logic of Coq formal system as a lower layer, and ontology language as upper layer for expressing and specifying contexts. Indeed, the higher-order KDTL language [8,20] supports the definition of new contextual categories and facts on the basis of low-order context. The language provides means to support comparability of diverse and non-countable information as well as numeric data.…”

Section: Related Workmentioning

confidence: 92%

Leveraging Event-B Theories for Handling Domain Knowledge in Design Models

Mendil¹,

Aït‐Ameur²,

Singh³

et al. 2021

Dependable Software Engineering. Theories, Tools, and Applications

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Formal system modelling languages lack explicit constructs to model domain knowledge, hindering clear separation of this knowledge from system design models. Indeed, in many cases, this knowledge is hardcoded in the system formal specification or is simply overlooked. Providing explicit domain knowledge constructs and properties would yield a significant improvement in the robustness and confidence of the system design models. Therefore, it speeds up formal verification of safety properties and advances system certification since certification standards and requirements rely on domain knowledge models. The purpose of this paper is to show how formal system design models can benefit from explicit handling of domain knowledge, represented as ontologies. To this end, state-based Event-B modelling language and theories are used to model system models and domain knowledge ontologies, respectively. Our proposition is exemplified by the TCAS (Traffic Collision Avoidance System) system, a critical airborne avionic component. Finally, we provide an assessment highlighting the overall approach.

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Section: Related Workmentioning

confidence: 92%

Leveraging Event-B Theories for Handling Domain Knowledge in Design Models

Mendil¹,

Aït‐Ameur²,

Singh³

et al. 2021

Dependable Software Engineering. Theories, Tools, and Applications

View full text Add to dashboard Cite

show abstract

“…Other reasoning technique more commonly used by formal methods have also been set up to handle proof of properties in ontologies. These approaches, which proved scalable, use of theorem provers like COQ with [52,53] or Event-B [24] to infer ontologies properties.…”

Section: Ontology Modelsmentioning

confidence: 99%

Making explicit domain knowledge in formal system development

Aït‐Ameur

Méry

2016

Science of Computer Programming

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Constraints description constructs are offered by the ontology modeling language to define constraints on classes, properties or on whole ontology. In the engineering domain, the more the constraint description language is rich, the more the expressed concepts of the ontologies are precisely described. Checking these constraints depend on the used constraint solving techniques associated to the ontology modeling language.

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Formalizing Context for Domain Ontologies in Coq

Dapoigny

Barlatier

2014

Context in Computing

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International audienceWhile context is crucial for reasoning about ontologies as well as for conceptual modeling, its formal definition is often imprecise and its implementation in standard classical logic-based theories suffers from a lack of expressiveness and leads to ambiguities. In this chapter, it is shown that a two-layered language using the Calculus of Inductive Constructions (i.e., the Coq language) as a lower layer, and an ontological upper layer for giving types their meaning is able to support a clear and expressive semantics for context specification

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Modeling Ontological Structures with Type Classes in Coq

Cited by 6 publications

References 28 publications

Leveraging Event-B Theories for Handling Domain Knowledge in Design Models

Leveraging Event-B Theories for Handling Domain Knowledge in Design Models

Making explicit domain knowledge in formal system development

Formalizing Context for Domain Ontologies in Coq

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