Reasoning About Quality in Hyperproperties

Hyperproperties allow one to specify properties of systems that inherently involve not single executions of the system, but several of them at once: observational determinism and non-inference are two examples of such properties used to study the security of systems. Logics like HyperLTL have been studied in the past to model check hyperproperties of systems. However, most of the time, requiring strict security properties is actually ineffective as systems do not meet such requirements. To overcome this issue, we introduce qualitative reasoning in HyperLTL, inspired by a similar work on LTL by Almagor, Boker and Kupferman where a formula has a value in the interval [0, 1], obtained by considering either a propositional quality (how much the specification is satisfied), or a temporal quality (when the specification is satisfied). We show decidability of the approximated model checking problem, as well as the model checking of large fragments.

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Publication Details

Journal
ArXiv.org
Published
2025-11-29
DOI
https://doi.org/10.4230/lipics.csl.2026.45
Primary Topic
Formal Methods in Verification
Type
article
Field-Weighted Citation Impact
0.00

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article

Reasoning About Quality in Hyperproperties

Benjamin Monmege, Jennifer P.VE Talbot, Samuel Graepler
ArXiv.org
Formal Methods in Verification
article

Reasoning About Quality in Hyperproperties

Benjamin Monmege, Jennifer P.VE Talbot, Samuel Graepler
article en

Abstract

Hyperproperties allow one to specify properties of systems that inherently involve not single executions of the system, but several of them at once: observational determinism and non-inference are two examples of such properties used to study the security of systems. Logics like HyperLTL have been studied in the past to model check hyperproperties of systems. However, most of the time, requiring strict security properties is actually ineffective as systems do not meet such requirements. To overcome this issue, we introduce qualitative reasoning in HyperLTL, inspired by a similar work on LTL by Almagor, Boker and Kupferman where a formula has a value in the interval [0, 1], obtained by considering either a propositional quality (how much the specification is satisfied), or a temporal quality (when the specification is satisfied). We show decidability of the approximated model checking problem, as well as the model checking of large fragments.

ArXiv.org
Aix-Marseille Université, Agence Nationale de la Recherche
Openalex Percentile: Top 62%
Formal Methods in Verification
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