  This survey presents an overview of verification techniques for autonomous
systems, with a focus on safety-critical autonomous cyber-physical systems
(CPS) and subcomponents thereof. Autonomy in CPS is enabling by recent advances
in artificial intelligence (AI) and machine learning (ML) through approaches
such as deep neural networks (DNNs), embedded in so-called learning enabled
components (LECs) that accomplish tasks from classification to control.
Recently, the formal methods and formal verification community has developed
methods to characterize behaviors in these LECs with eventual goals of formally
verifying specifications for LECs, and this article presents a survey of many
of these recent approaches.
