We present a bounded model checking algorithm for signal temporal logic (STL) that exploits mixed-integer linear programming (MILP). A key technical element is our novel MILP encoding of the STL semantics; it follows the idea of stable partitioning from the recent work on SMT-based STL model checking. Assuming that our (continuous-time) system models can be encoded to MILP – typical examples are rectangular hybrid automata (precisely) and hybrid dynamics with closed-form solutions (approximately) – our MILP encoding yields an optimization-based model checking algorithm that is scalable, is anytime/interruptible, and accommodates parameter mining. Experimental evaluation shows our algorithm’s performance advantages especially for complex STL formulas, demonstrating its practical relevance e.g. in the automotive domain.

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