Family-Based Model Checking Without a Family-Based Model Checker

Abstract

Many software systems are variational: they can be configured to meet diverse sets of requirements. Variability is found in both communication protocols and discrete controllers of embedded systems. In these areas, model checking is an important verification technique. For variational models (systems with variability), specialized family-based model checking algorithms allow efficient verification of multiple variants, simultaneously. These algorithms scale much better than “brute force” verification of individual systems, one-by-one. Nevertheless, they can deal with only very small variational models.

We address two key problems of family-based model checking. First, we improve scalability by introducing abstractions that simplify variability. Second, we reduce the burden of maintaining specialized family-based model checkers, by showing how the presented variability abstractions can be used to model-check variational models using the standard version of (single system) SPIN. The abstractions are first defined as Galois connections on semantic domains. We then show how to translate them into syntactic source-to-source transformations on variational models. This allows the use of SPIN with all its accumulated optimizations for efficient verification of variational models without any knowledge about variability. We demonstrate the practicality of this method on several examples using both the $\overline{\text {SNIP}}$ (family based) and SPIN (single system) model checkers.

Danish Council for Independent Research, Sapere Aude grant no. 0602-02327B.