  Black-box checking (BBC)} is a testing method for cyber-physical systems
(CPSs) as well as software systems. BBC consists of active automata learning
and model checking; a Mealy machine is learned from the system under test
(SUT), and the learned Mealy machine is verified against a specification using
model checking. When the Mealy machine violates the specification, the model
checker returns an input witnessing the specification violation of the Mealy
machine. We use it to refine the Mealy machine or conclude that the SUT
violates the specification. Otherwise, we conduct equivalence testing to find
an input witnessing the difference between the Mealy machine and the SUT. In
the BBC for CPSs, equivalence testing tends to be time-consuming due to the
time for the system execution. In this paper, we enhance the BBC utilizing
model checking with strengthened specifications. By model checking with a
strengthened specification, we have more chance to obtain an input witnessing
the specification violation than model checking with the original
specification. The refinement of the Mealy machine with such an input tends to
reduce the number of equivalence testing, which improves the efficiency. We
conducted experiments with an automotive benchmark. Our experiment results
demonstrate the merit of our method.
