  Cyber-physical systems (CPSes), such as autonomous vehicles, use
sophisticated components like ML-based controllers. It is difficult to provide
evidence about the safe functioning of such components. To overcome this
problem, Runtime Assurance Architecture (RTA) solutions have been proposed. The
\RAP's decision component evaluates the system's safety risk and whenever the
risk is higher than acceptable the RTA switches to a safety mode that, for
example, activates a controller with strong evidence for its safe functioning.
In this way, RTAs increase CPS runtime safety and resilience by recovering the
system from higher to lower risk levels. The goal of this paper is to automate
recovery proofs of CPSes using RTAs. We first formalize the key verification
problems, namely, the decision sampling-time adequacy problem and the
time-bounded recoverability problem. We then demonstrate how to automatically
generate proofs for the proposed verification problems using symbolic rewriting
modulo SMT. Automation is enabled by integrating the rewriting logic tool
(Maude), which generates sets of non-linear constraints, with an SMT-solver
(Z3) to produce proofs
