An Integer Static Analysis for Better Extrapolation in Uppaal

Sebastian Lund, Jesper van Diepen, Kim G. Larsen, Marco Muñiz*, Tobias Ringholm Jørgensen, Tobias Skaarup Daa Andersen

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

1 Citationer (Scopus)

Abstract

Extended Timed Automata (XTA) is a widely used formalism to show the correctness of industrial applications. The decidability results and current extrapolations for XTA are based on constants in the automaton. However, in the case of XTA such bounds depend on integer variables or variable expressions. Since computing such bounds can be as expensive as the verification task, tools such as Uppaal over-approximate the bounds by values given in the type definitions. These values are excessively large and can yield huge state spaces. In this paper we outline a targeted static analysis to efficiently over-approximate location based invariants (and thereby ranges) of integer variables. We have implemented our analysis in Uppaal where the new tighter bounds are available to all currently implemented extrapolation operations. Our experiments show an exponential reduction in the state space of several models. In addition, the computation overhead introduced by the integer static analysis is negligible.

OriginalsprogEngelsk
TitelFormal Modeling and Analysis of Timed Systems - 19th International Conference, FORMATS 2021, Proceedings
RedaktørerCatalin Dima, Mahsa Shirmohammadi
Antal sider16
ForlagSpringer
Publikationsdato2021
Sider84-99
ISBN (Trykt)9783030850364
DOI
StatusUdgivet - 2021
Begivenhed19th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2021 - Virtual, Online
Varighed: 24 aug. 202126 aug. 2021

Konference

Konference19th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2021
ByVirtual, Online
Periode24/08/202126/08/2021
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind12860 LNCS
ISSN0302-9743

Bibliografisk note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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