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Resource Tableaux

Identifieur interne : 003B22 ( Istex/Corpus ); précédent : 003B21; suivant : 003B23

Resource Tableaux

Auteurs : Didier Galmiche ; Daniel Méry ; David Pym

Source :

RBID : ISTEX:F71E0B68369621B1437F3428CF7C75CDD1007685

Abstract

Abstract: The logic of bunched implications, BI, provides a logical analysis of a basic notion of resource rich enough to provide a “pointer logic” semantics for programs which manipulate mutable data structures. We develop a theory of semantic tableaux for BI, so providing an elegant basis for efficient theorem proving tools for BI. It is based on the use of an algebra of labels for BI’s tableaux to solve the resource-distribution problem, the labels being the elements of resource models. For BI with inconsistency, ⊥, the challenge consists in dealing with BI’s Grothendieck topological models within such a proof-search method, based on labels. We prove soundness and completeness theorems for a resource tableaux method TBI with respect to this semantics and provide a way to build countermodels from so-called dependency graphs. As consequences, we have two strong new results for BI: the decidability of propositional BI and the finite model property with respect to Grothendieck topological semantics. In addition, we propose, by considering partially defined monoids, a new semantics which generalizes the semantics of BI’s pointer logic and for which BI is complete

Url:
DOI: 10.1007/3-540-45793-3_13

Links to Exploration step

ISTEX:F71E0B68369621B1437F3428CF7C75CDD1007685

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<PartTitle>Linear and Resource Logics</PartTitle>
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<ChapterTitle Language="En">Resource Tableaux</ChapterTitle>
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<Para>The logic of bunched implications,
<Emphasis Type="Bold">BI</Emphasis>
, provides a logical analysis of a basic notion of resource rich enough to provide a “pointer logic” semantics for programs which manipulate mutable data structures. We develop a theory of semantic tableaux for
<Emphasis Type="Bold">BI</Emphasis>
, so providing an elegant basis for efficient theorem proving tools for
<Emphasis Type="Bold">BI</Emphasis>
. It is based on the use of an algebra of labels for
<Emphasis Type="Bold">BI</Emphasis>
’s tableaux to solve the resource-distribution problem, the labels being the elements of resource models. For
<Emphasis Type="Bold">BI</Emphasis>
with inconsistency, ⊥, the challenge consists in dealing with
<Emphasis Type="Bold">BI</Emphasis>
’s Grothendieck topological models within such a proof-search method, based on labels. We prove soundness and completeness theorems for a resource tableaux method
<Emphasis Type="Bold">TBI</Emphasis>
with respect to this semantics and provide a way to build countermodels from so-called dependency graphs. As consequences, we have two strong new results for
<Emphasis Type="Bold">BI</Emphasis>
: the decidability of propositional
<Emphasis Type="Bold">BI</Emphasis>
and the finite model property with respect to Grothendieck topological semantics. In addition, we propose, by considering partially defined monoids, a new semantics which generalizes the semantics of
<Emphasis Type="Bold">BI</Emphasis>
’s pointer logic and for which
<Emphasis Type="Bold">BI</Emphasis>
is complete</Para>
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<Keyword>semantics</Keyword>
<Keyword>tableaux</Keyword>
<Keyword>decidability</Keyword>
<Keyword>finite model property</Keyword>
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<abstract lang="en">Abstract: The logic of bunched implications, BI, provides a logical analysis of a basic notion of resource rich enough to provide a “pointer logic” semantics for programs which manipulate mutable data structures. We develop a theory of semantic tableaux for BI, so providing an elegant basis for efficient theorem proving tools for BI. It is based on the use of an algebra of labels for BI’s tableaux to solve the resource-distribution problem, the labels being the elements of resource models. For BI with inconsistency, ⊥, the challenge consists in dealing with BI’s Grothendieck topological models within such a proof-search method, based on labels. We prove soundness and completeness theorems for a resource tableaux method TBI with respect to this semantics and provide a way to build countermodels from so-called dependency graphs. As consequences, we have two strong new results for BI: the decidability of propositional BI and the finite model property with respect to Grothendieck topological semantics. In addition, we propose, by considering partially defined monoids, a new semantics which generalizes the semantics of BI’s pointer logic and for which BI is complete</abstract>
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