  The prolific rise in autonomous systems has led to questions regarding their
safe instantiation in real-world scenarios. Failures in safety-critical
contexts such as human-robot interactions or even autonomous driving can
ultimately lead to loss of life. In this context, this paper aims to provide a
method by which one can algorithmically test and evaluate an autonomous system.
Given a black-box autonomous system with some operational specifications, we
construct a minimax problem based on control barrier functions to generate a
family of test parameters designed to optimally evaluate whether the system can
satisfy the specifications. To illustrate our results, we utilize the
Robotarium as a case study for an autonomous system that claims to satisfy
waypoint navigation and obstacle avoidance simultaneously. We demonstrate that
the proposed test synthesis framework systematically finds those sequences of
events (tests) that identify points of system failure.
