In particular we compare collision checking techniques, sampling techniques, and node adding techniques.
The COMPASS toolset utilizes state-of-the-art model checking techniques, both qualitative and probabilistic, for the analysis of requirements related to functional correctness, safety, dependability and performance.
Accordingly, some model checking techniques have been tailored and used for solving distinguishability problems at the EFSM level using appropriate product machines (Wang et al. 1994; Cho et al. 1991; Clatin et al. 1995; Fernandez et al. 1996; Okun et al. 2002).
The porcine eyes were usually used for checking techniques because of similar anatomy of human and easy availability [ 20– 20].
The goal is to use the Simulink model, high-level requirements and test specifications to apply model checking techniques for the generation of test data.
First, symbolic model checking techniques, Binary Decision Diagrams in particular, can be used to represent and expand the search space, and to provide an efficient computational platform.
Verifying correctness and safety of such systems amounts to model checking the underlying system model, where model checking techniques not only need to be correct but since system sizes increase also scalable and efficient.
The model checking techniques not only need to be correct (since system sizes increase), but also scalable and efficient.
In order to generate and optimize the test data, the approach focus is on model checking techniques.
