Emergent Mind

Relational Differential Dynamic Logic

(1903.00153)
Published Mar 1, 2019 in cs.LO

Abstract

In the field of quality assurance of hybrid systems (that combine continuous physical dynamics and discrete digital control), Platzer's differential dynamic logic (dL) is widely recognized as a deductive verification method with solid mathematical foundations and sophisticated tool support. Motivated by benchmarks provided by our industry partner, we study a relational extension of dL, aiming to formally prove statements such as "an earlier deployment of the emergency brake decreases the collision speed." A main technical challenge here is to relate two states of two dynamics at different time points. Our main contribution is a theory of suitable simulations (a relational extension of differential invariants that are central proof methods in dL), and a derived technique of time stretching. The latter features particularly high applicability, since the user does not have to synthesize a simulation out of the air. We derive new inference rules for dL from these notions, and demonstrate their use over a couple of automotive case studies.

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