Formal Veriftcation of Aircraft, Uboat and Electric Car Control Systems using SPARK ADA

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Research ID 1D008

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Abstract

The control systems of safety-critical transportation vehicles such as railways, submarines, and electric cars must bedesignedandver ifiedri gorously to ensure their safe and reliable operation. In this paper, we present a formal verification approach using the SPARK ADA programming language to verify the correctness of control systems for these vehicles. SPARK ADA is language that enforces strong static typing, and provides formal verification support through contracts and proof obligations. We demonstrate the effectiveness of our approach by applying it to three case studies: a railway control system, a submarine control system, and an electric car control system. For each case study, we first specify the system requirements and design the control system using SPARK ADA. We then perform formal verification by generating and proving proof obligations using the SPARK toolset.
Our results show that our approach is effective in detecting and preventing potential errors and vulnerabilities in the control systems. In particular, we found several subtle errors in the case studies that were not detected by traditional testing or manual inspection. Furthermore, our approach enables us to prove that the control systems satisfy their specified requirements, which is crucial for ensuring their safety and reliability.
In conclusion, our approach using SPARK ADA provides a rigorous and efficient method for formal verification of control systems for safety-critical transportation vehicles. It can help designers and engineers to ensure the correctness and reliability of their control systems, and reduce the risk of accidents and incidents.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

Not applicable

Data Availability

The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

Funding

This work did not receive any external funding.

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  • Classification

    NLM Code: WB 103

  • Version of record

    v1.0

  • Issue date

    22 September 2023

  • Language

    English

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LJRCST Volume 23 LJRCST Volume 23 Issue 4, Pg. 19-28
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