Distributing the Challenge of Model Checking Interlocking Control Tables

Fantechi, Alessandro

doi:10.1007/978-3-642-34032-1_26

Cited by 18 publications

(8 citation statements)

References 10 publications

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“…In [25] Winter pushes the applicability bounds of symbolic model checking (NUSMV) by optimizing the ordering strategies for variables and transitions using domain knowledge about the track layout. Fantechi suggests in [10] to exploit a distributed modelling of geographical interlocking systems and break the verification task into smaller tasks that can be distributed to multiple processors such that they can be verified in parallel. In [20], it is suggested to reduce the state space using abstraction techniques reducing the number of track sections and the number of trains.…”

Section: Related Workmentioning

confidence: 99%

Applied Bounded Model Checking for Interlocking System Designs

Haxthausen

Peleskã

Pinger

2014

Lecture Notes in Computer Science

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Abstract. In this paper the verification and validation of interlocking systems is investigated. Reviewing both geographical and route-related interlocking, the verification objectives can be structured from a perspective of computer science into (1) verification of static semantics, and (2) verification of behavioural (operational) semantics. The former checks that the plant model -that is, the software components reflecting the physical components of the interlocking system -has been set up in an adequate way. The latter investigates trains moving through the network, with the objective to uncover potential safety violations. From a formal methods perspective, these verification objectives can be approached by theorem proving, global, or bounded model checking. This paper explains the techniques for application of bounded model checking techniques, and discusses their advantages in comparison to the alternative approaches.

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Section: Related Workmentioning

confidence: 99%

Applied Bounded Model Checking for Interlocking System Designs

Haxthausen

Peleskã

Pinger

2014

Lecture Notes in Computer Science

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“…The contributions to this special issue are further elaborations of the ones presented at the conference track [15][16][17][18][19][20][21] and they focus on the application of formal reasoning to the development of safety-critical, computer-based railway signalling systems. Indeed, these contributions are representative of two challenging industrial research directions in the domain of railway signalling software development.…”

Section: Formal Methods: From the Conference Session On Intelligent Tmentioning

confidence: 99%

Formal methods for railway control systems

Fantechi

Flammini

Gnesi

2014

Int J Softw Tools Technol Transfer

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We wish to model railway control systems in a formally precise way so that product lines can be adapted to specific customer requirements. Typically a customer is a railway operator with national conventions leading to different variation points based on a common core principle. A formal model of the core product must be precise and manipulatable so that different feature variations can be specified and verified without disrupting important properties that have already been established in the core product. Cyber-physical systems such as railway interlocking, are characterised by the combination of device behaviours resulting in an overall safe system behaviour. Hence there is a strong need for correct sequential operation with safety "interlocks" making up a process. We utilise diagrammatic modelling tools to make the core product more accessible to systems engineers. The RailGround example used to discuss these techniques is an open source model of a railway control system that has been made available by Thales Austria GmbH for research purpose, which demonstrates some fundamental modelling challenges.

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“…Formula (2) states that if there is a train on Track T_01BC, the direction on Point P_02AC cannot change at the next state. Formula (3) states that if there is a train moving from Track T_092 to Track T_01BC, Point P_01BC must be set and stay to left. Such equations are related to the safety, the next ones ensure the availability of the system.…”

Section: Definition Of Propertiesmentioning

confidence: 99%

“…Until now, most of the research targeting the verification of the application data is based on model checking ( [2], [3], [4]) even if other approaches based on formal methods exist [5]. First, the signalling principles and the application data are translated into a model.…”

Section: Introductionmentioning

confidence: 99%

Verification of Interlocking Systems Using Statistical Model Checking

Cappart

Limbrée

Schaus

et al. 2017

2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE)

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Abstract-1 In the railway domain, an interlocking is the system ensuring safe train traffic inside a station by controlling its active elements such as the signals or points. Modern interlockings are configured using particular data, called application data, reflecting the track layout and defining the actions that the interlocking can take. The safety of the train traffic relies thereby on application data correctness, errors inside them can cause safety issues such as derailments or collisions. Given the high level of safety required by such a system, its verification is a critical concern. In addition to the safety, an interlocking must also ensure that availability properties, stating that no train would be stopped forever in a station, are satisfied. Most of the research dealing with this verification relies on model checking. However, due to the state space explosion problem, this approach does not scale for large stations. More recently, a discrete event simulation approach limiting the verification to a set of likely scenarios, was proposed. The simulation enables the verification of larger stations, but with no proof that all the interesting scenarios are covered by the simulation. In this paper, we apply an intermediate statistical model checking approach, offering both the advantages of model checking and simulation. Even if exhaustiveness is not obtained, statistical model checking evaluates with a parametrizable confidence the reliability and the availability of the entire system.

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Distributing the Challenge of Model Checking Interlocking Control Tables

Cited by 18 publications

References 10 publications

Applied Bounded Model Checking for Interlocking System Designs

Applied Bounded Model Checking for Interlocking System Designs

Formal methods for railway control systems

Verification of Interlocking Systems Using Statistical Model Checking

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