Multiple Objective Functions for Falsification of Cyber-Physical Systems

Paper i proceeding, 2020

Cyber-physical systems are typically safety-critical, thus it is crucial to guarantee that they conform to
given specifications, that are the properties that the system must fulfill. Optimization-based falsification
is a model-based testing method to find counterexamples of the specifications. The main idea is to
measure how far away a specification is from being broken, and to use an optimization procedure to guide
the testing towards falsification. The efficiency of the falsification is affected by the objective function
used to evaluate the test results; different objective functions are differently efficient for different types
of problems. However, the efficiency of various objective functions is not easily determined beforehand.
This paper evaluates the efficiency of using multiple objective functions in the falsification process. The
hypothesis is that this will, in general, be more efficient, meaning that it falsifies a system in fewer
iterations, than just applying a single objective function to a specific problem. Two objective functions
are evaluated, Max, Additive, on a set of benchmark problems. The evaluation shows that using multiple
objective functions can reduce the number of iterations necessary to falsify a property.