On Input Generators for Cyber-Physical Systems Falsification

Falsification is a testing method that aims to increase confidence in the correctness of cyber-physical systems by guiding the search for counterexamples with some optimization algorithm. This method generates input signals for a simulation of the system under test and employs quantitative semantics, which serves as objective functions, to minimize the distance needed to falsify a specification. Various implementations based on different optimization strategies and semantics have been proposed and evaluated in the past. Generally, they assume that an input generator is given. However, this is often not the case in practice and different choices can lead to vastly different outcomes. Therefore, this article introduces and evaluates various parameterizations of input generators, including pulse, sinusoidal, and piecewise signals with different interpolation techniques. These input generators are compared based on their performance on benchmark examples, as well as coverage measures in the space-time and frequency domains. Input generators facilitate the exploration of numerous different input signals within a single falsification problem, making them especially valuable for industrial practitioners seeking to incorporate falsification into their daily development work.