Metric First-Order Temporal Logic with Complex Data Types


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Date

2023

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Temporal logics are widely used in runtime verification as they enable the creation of declarative and compositional specifications. However, their ability to model complex data is limited. One must resort to complicated encoding schemes to express properties involving basic structures such as lists or trees. To avoid this drawback, we extend metric first-order temporal logic with a minimalistic, yet expressive, functional programming language. The extension features an expressive collection of types including function, record, variant, and inductive types, as well as support for type inference and monitoring. Our monitor implementation directly parses traces in the JSON format, based on the user’s type specification, which avoids a separate pre-processing step. We compare our approach to existing shallow embeddings of temporal properties in general-purpose host languages and to encodings into simple temporal logics. Specifically, our language benefits from a precise semantics and a good support for monitoring-specific static analysis.

Publication status

published

Book title

Runtime Verification

Volume

14245

Pages / Article No.

126 - 147

Publisher

Springer

Event

23th International Conference on Runtime Verification (RV 2023)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Monitoring; Temporal logic; Data types

Organisational unit

03634 - Basin, David / Basin, David check_circle
02150 - Dep. Informatik / Dep. of Computer Science

Notes

Funding

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