Table 1.

Overview of major features available in NNV. Links refer to relevant files/classes in the NNV codebase. BN refers to batch normalization layers, FC to fully-connected layers, AvgPool to average pooling layers, Conv to convolutional layers, and MaxPool to max pooling layers.

Feature	Exact analysis	Over-approximate analysis
Components	FFNN, CNN, NNCS	FFNN, CNN, NNCS
Plant dynamics (for NNCS)	Linear ODE	Linear ODE, Nonlinear ODE
Discrete/Continuous (for NNCS)	Discrete Time	Discrete Time, Continuous Time
Activation functions	ReLU, Satlin	ReLU, Satlin, Sigmoid, Tanh
CNN Layers	MaxPool, Conv, BN, AvgPool, FC	MaxPool, Conv, BN, AvgPool, FC
Reachability methods	Star, Polyhedron, ImageStar	Star, Zonotope, Abstract-domain, ImageStar
Reachable set/Flow-pipe Visualization	Yes	Yes
Parallel computing	Yes	Partially supported
Safety verification	Yes	Yes
Falsification	Yes	Yes
Robustness verification (for FFNN/CNN)	Yes	Yes
Counterexample generation	Yes	Yes