Participatory Verification of Railway Infrastructure by Representing Regulations in RailCNL

Luteberget, Bjørnar; Camilleri, John J.; Johansen, Christian; Schneider, Gerardo

doi:10.1007/978-3-319-66197-1_6

Cited by 12 publications

(11 citation statements)

References 19 publications

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“…Textual representations can be understood easily even by non-experts [6] in formal methods. However, only 17 of the primary studies (15% of all primary studies) use such a representation to provide statements for error notification or highlighting the error in a provided textual input system such as Controlled/-Constrained Natural Language (CNL) [51,52], Structured English [53][54][55][56][57], or error localization as known from programming languages [58][59][60][61][62].…”

Section: Textual Representationmentioning

confidence: 99%

A systematic literature review on counterexample explanation

Kaleeswaran,

Nordmann,

Vogel

et al. 2022

Preprint

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Context: Safety is of paramount importance for cyber-physical systems in domains such as automotive, robotics, and avionics. Formal methods such as model checking are one way to ensure the safety of cyber-physical systems. However, adoption of formal methods in industry is hindered by usability issues, particularly the difficulty of understanding model checking results. Objective: We want to provide an overview of the state of the art for counterexample explanation by investigating the contexts, techniques, and evaluation of research approaches in this field. This overview shall provide an understanding of current and guide future research. Method: To provide this overview, we conducted a systematic literature review. The survey comprises 116 publications that address counterexample explanations for model checking. Results: Most primary studies provide counterexample explanations graphically or as traces, minimize counterexamples to reduce complexity, localize errors in the models expressed in the input formats of model checkers, support linear temporal logic or computation tree logic specifications, and use model checkers of the Smybolic Model Verifier family. Several studies evaluate their approaches in safety-critical domains with industrial applications. Conclusion: We notably see a lack of research on counterexample explanation that targets probabilistic and real-time systems, leverages the explanations to domain-specific models, and evaluates approaches in user studies. We conclude by discussing the adequacy of different types of explanations for users with varying domain and formal methods expertise, showing the need to support laypersons in understanding model checking results to increase adoption of formal methods in industry.

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Section: Textual Representationmentioning

confidence: 99%

A systematic literature review on counterexample explanation

Kaleeswaran,

Nordmann,

Vogel

et al. 2022

Preprint

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“…The tool is complementary to other verification techniques in railway design, such as static layout verification [31,33,34], static interlocking verification [22,33], interlocking program verification [5], and timetable analysis [21].…”

Section: Sat Modulo Des Tool-chain For Capacity Analysis In Railway Designsmentioning

confidence: 99%

SAT modulo discrete event simulation applied to railway design capacity analysis

Luteberget

Claessen

Johansen

et al. 2021

Form Methods Syst Des

Self Cite

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This paper proposes a new method of combining SAT with discrete event simulation. This new integration proved useful for designing a solver for capacity analysis in early phase railway construction design. Railway capacity is complex to define and analyze, and existing tools and methods used in practice require comprehensive models of the railway network and its timetables. Design engineers working within the limited scope of construction projects report that only ad-hoc, experience-based methods of capacity analysis are available to them. Designs often have subtle capacity pitfalls which are discovered too late, only when network-wide timetables are made—there is a mismatch between the scope of construction projects and the scope of capacity analysis, as currently practiced. We suggest a language for capacity specifications suited for construction projects, expressing properties such as running time, train frequency, overtaking and crossing. Such specifications can be used as contracts in the interface between construction projects and network-wide capacity analysis. We show how these properties can be verified fully automatically by building a special-purpose solver which splits the problem into two: an abstracted SAT-based dispatch planning, and a continuous-domain dynamics with timing constraints evaluated using discrete event simulation. The two components communicate in a CEGAR loop (counterexample-guided abstraction refinement). This architecture is beneficial because it clearly distinguishes the combinatorial choices on the one hand from continuous calculations on the other, so that the simulation can be extended by relevant details as needed. We describe how loops in the infrastructure can be handled to eliminate repeating dispatch plans, and use case studies based on data from existing infrastructure and ongoing construction projects to show that our method is fast enough at relevant scales to provide agile verification in a design setting. Similar SAT modulo discrete event simulation combinations could also be useful elsewhere where one or both of these methods are already applicable such as in bioinformatics or hardware/software verification.

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“…Related Work Luteberget et al [24] use traces to link errors raised during verification to the responsible part of the model and the original document. These traces roughly resemble the annotations in messages generated by VisualisierbaR during simulation, but are not used to validate the model itself.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Tool Support for Validation of Formal System Models: Interactive Visualization and Requirements Traceability

Kamburjan

Stromberg

2019

Electron. Proc. Theor. Comput. Sci.

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Development processes in various engineering disciplines are incorporating formal models to ensure safety properties of critical systems. The use of these formal models requires to reason about their adequacy, i.e., to validate that a model mirrors the structure of the system sufficiently that properties established for the model indeed carry over to the real system. Model validation itself is non-formal, as adequacy is not a formal (i.e., mathematical) property. Instead it must be carried out by the modeler to justify the modeling to the certification agency or other stakeholders. In this paper we argue that model validation can be seen as a special form of requirements engineering, and that interactive visualization and concepts from requirements traceability can help to advance tool support for formal modeling by lowering the cognitive burden needed for validation. We present the VisualisierbaR tool, which supports the formal modeling of railway operations and describe how it uses interactive visualization and requirements traceability concepts to validate a formal model.

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Participatory Verification of Railway Infrastructure by Representing Regulations in RailCNL

Cited by 12 publications

References 19 publications

A systematic literature review on counterexample explanation

A systematic literature review on counterexample explanation

SAT modulo discrete event simulation applied to railway design capacity analysis

Tool Support for Validation of Formal System Models: Interactive Visualization and Requirements Traceability

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