  We present VERIFAI, a software toolkit for the formal design and analysis of
systems that include artificial intelligence (AI) and machine learning (ML)
components. VERIFAI particularly seeks to address challenges with applying
formal methods to perception and ML components, including those based on neural
networks, and to model and analyze system behavior in the presence of
environment uncertainty. We describe the initial version of VERIFAI which
centers on simulation guided by formal models and specifications. Several use
cases are illustrated with examples, including temporal-logic falsification,
model-based systematic fuzz testing, parameter synthesis, counterexample
analysis, and data set augmentation.
