A program that takes models as input and generates the target models as output and meanwhile keeps the information consistent. The aim of using a model transformation is to save effort and reduce errors by automating the building and modification of models where possible.
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Prover will be at Train & Rail, meet us in our booth located at A06:31.
Discover how reachability analysis enhances formal verification by ensuring realistic scenarios and validating safety requirements in railway signaling systems. Learn about key techniques, including proof coverage, constraints softening, and early-stage validation, and explore how our tools make this process more efficient.
Explore how Prover is revolutionizing railway signaling with AI and formal methods. Discover Prover Labs: a hub for innovation, collaboration, and shaping AI-driven automation for enhanced safety, efficiency, and precision in signaling design.
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