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Abstract. We present a fully automatic approach for counterexample guided abstraction refinement of real-time systems modelled in a subset of timed automata. Our approach is implemented in the MOBY/RT tool environment, which is a CASE tool for embedded system specifications. Verification in MOBY/RT is done by constructing abstractions of the semantics in terms of timed automata which are fed into the model checker UPPAAL. Since the abstractions are overapproximations, absence of abstract counterexamples implies a valid result for the full model. Our new approach deals with the situation in which an abstract counterexample is found by UPPAAL. The generated abstract counterexample is used to construct either a concrete counterexample for the full model or to identify a slightly refined abstraction in which the found spurious counterexample cannot occur anymore. Hence, the approach allows for a fully automatic abstraction refinement loop starting from the coarsest abstraction towards an abstraction for which a valid verification result is found. Nontrivial case studies demonstrate that this approach computes small abstractions fast without any user interaction.

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Directed model checking aims at speeding up the search for bugs in a system through the use of heuristic functions. Such a function maps states to integers, estimating the state's distance to the nearest error state. The search gives a preference to states with lower estimates. The key issue is how to generate good heuristic functions, i. e., functions that guide the search quickly to an error state. An arsenal of heuristic functions has been developed in recent years. Significant progress was made, but many problems still prove to be notoriously hard. In particular, a body of work describes heuristic functions for model checking timed automata in UPPAAL, and tested them on a certain set of benchmarks. Into this arsenal we add another heuristic function. With previous heuristics, for the largest of the benchmarks it was only just possible to find some (unnecessarily long) error path. With the new heuristic, we can find provably shortest error paths for these benchmarks in a matter of seconds. The heuristic function is based on a kind of Russian Doll principle, where the heuristic for a given problem arises through using UPPAAL itself for the complete exploration of a simplified instance of the same problem. The simplification consists in removing those parts from the problem that are distant from the error property. As our empirical results confirm, this simplification often preserves the characteristic structure leading to the error.

It is probably very hard to develop a new model checker that is faster than UPPAAL for verifying (correct) timed automata. In fact, our tool MCTA does not even try to compete with UPPAAL in this (i. e., UPPAAL's) arena. Instead, MCTA is geared towards analyzing incorrect specifications of timed automata. It returns (shorter) error traces faster.