SlowGuess/NeurIPS_2023_OCR huggingface dataset:
Such an automaton is challenging for black-box analysis tools because they always have to explore all transitions. For instance, when we evaluated the reachability tool on the cart-pole system, the tool can analyze the first four control periods (out of 25) in 22 seconds, but then gets stuck in the fifth control period when the bisection starts, and prints errors about numerical instability. By knowing the problem structure, our approach only explores the feasible paths of the decision tree (often there is just one), for which it only has to evaluate  $d$  predicates, where  $d$  is the depth of the tree. Furthermore, given the periodic control policy, we only have to perform these checks at specific time points. For general hybrid automata, this has to be found out via intersections with invariants and guards. These structural insights make our analysis not only more efficient but also more precise in practice because general hybrid-automata tools would typically approximate these operations.