A model learning based testing approach for spiking neural P systems

•This paper proposes a testing method for spiking neural P systems.•The underlying test generation strategy is based on a variant of the W-method.•It alleviates the state explosion problem by constructing a series of approximations.•These are based on the Ll algorithm for learning a finite cover automaton.•It also investigates the concept of identifiability of spiking neural P systems.