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For many crucial applications, establishing important properties of Simulink models by testing is either extremely resource intensive or impossible, and proof of the properties is highly desirable. Many Simulink models rely upon discrete-valued functions for which the function values are defined as a lookup table of correspondences between values in the domain and range, with linear interpolation used to evaluate intermediate values in the domain. Such discrete-valued functions arise in applications for which no known closed-form algebraic definition exists. In general, the proof of a property for a model that includes a discrete-valued function has to be by case analysis. For a single function and with mechanical support, case analysis is manageable. However, for models that include multiple discrete-valued functions, the number of cases can be the product of the cardinalities of the domains of the individual functions.

Software verification is a critical component of software development. Software verification techniques include different forms of testing, inspection, static analysis, and formal verification. Formal verification offers the advantage that it corresponds, at least informally, to testing all possible paths through the software. There are two primary approaches to using formal verification to establish properties of software: (a) proving properties of a formal specification, and (b) proving an implementation is a refinement of its specification. The first approach allows inference of the proven properties of the implementation provided the implementation is correct. The second approach allows inference of the correctness of the implementation. Proving properties of a specification provides a means for detecting critical design flaws early in the development process. In model-based development, the model (e.g., a set of SIMULINK diagrams) is a formal specification of the desired system.