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https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
Data sources: Datacite
https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
Data sources: Datacite
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Sequent Calculi for Data-Aware Modal Logics

Authors: Areces, Carlos; Cassano, Valentin; Dutto, Danae; Fervari, Raul;

Sequent Calculi for Data-Aware Modal Logics

Abstract

Data-aware modal logics offer a powerful formalism for reasoning about semi-structured queries in languages such as DataGL, XPath, and GQL. In brief, these logics can be viewed as modal systems capable of expressing both reachability statements and data-aware properties, such as value comparisons. One particularly expressive logic in this landscape is HXpathD, a hybrid modal logic that captures not only the navigational core of XPath but also data comparisons, node labels (keys), and key-based navigation operators. While previous work on HXpathD has primarily focused on its model-theoretic properties, in this paper we approach HXpathD from a proof-theoretic perspective. Concretely, we present a sound and complete Gentzen-style sequent calculus for HXpathD. Moreover, we show all rules in this calculus are invertible, and that it enjoys cut elimination. Our work contributes to the proof-theoretic foundations of data-aware modal logics, and enables a deeper logical analysis of query languages over graph-structured data. Moreover, our results lay the groundwork for extending proof-theoretic techniques to a broader class of modal systems.

In Proceedings LSFA 2025, arXiv:2509.23739. Full technical details and omitted proofs can be found in arXiv:2505.17240

Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Logic in Computer Science, Logic in Computer Science (cs.LO)

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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