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zbMATH Open
Article . 2023
Data sources: zbMATH Open
DBLP
Article . 2023
Data sources: DBLP
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Compositional Verification of Railway Interlocking Systems

Compositional verification of railway interlocking systems
Authors: Haxthausen, AE; Fantechi, A;

Compositional Verification of Railway Interlocking Systems

Abstract

Model checking techniques have often been applied to the verification of railway interlocking systems, responsible for guiding trains safely through a given railway network. However, these techniques fail to scale to the interlocking systems controlling large stations, composed of hundreds and even thousands of controlled entities, due to the state space explosion problem. Indeed, interlocking systems exhibit a certain degree of locality that allows some reasoning only on the mere set of entities that regard the train movements, but safe routing through a complex station layout requires a global reservation policy, which can require global state conditions to be taken into account. In this article, we present a compositional approach aimed at chopping the verification of a large interlocking system into that of smaller fragments, exploiting in each fragment a proper abstraction of the global information on routing state. A proof is given of the thesis that verifying the safety of the smaller fragments is sufficient to verify the safety of the whole network. Experiments using this compositional approach have shown important gains in performance of the verification, as well as in the size of affordable station layouts.

Countries
Italy, Denmark
Keywords

safety, interlocking systems, formal methods, Formal methods, Interlocking systems, compositional verification, Computer science, Formal methods; compositional verification; railways; interlocking systems; safety, Compositional veriication,, railways, Railways

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    12
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
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!
12
Top 10%
Top 10%
Top 10%
Green