This paper presents the language Lutin and its operational semantics. This language specifically targets the domain of reactive systems, where an execution is a (virtually) infinite sequence of input/output reactions. More precisely, it is dedicated to the description and the execution of constrained random scenarios. Its first use is for test sequence specification and generation. It can also be useful for early simulation of huge systems, where Lutin programs can be used to describe and simulate modules that are not yet fully developed. The programming style mixes relational and imperative features. Basic statements are input/output relations, expressing constraints on a single reaction. Those constraints are then combined to describe non deterministic sequences of reactions. The language constructs are inspired by regular expressions, and process algebra (sequence, choice, loop, concurrency). Moreover, the set of statements can be enriched with user defined operators. A notion of stochastic directive is also provided, in order to finely influence the selection of a particular class of scenarios.

This paper presents the language Lutin and its operational semantics. This language specifically targets the domain of reactive systems, where an execution is a (virtually) infinite sequence of input/output reactions. More precisely, it is dedicated to the description and the execution of constrained random scenarios. Its first use is for test sequence specification and generation. It can also be useful for early simulation of huge systems, where Lutin programs can be used to describe and simulate modules that are not yet fully developed. Basic statements are input/output relations expressing constraints on a single reaction. Those constraints are then combined to describe non deterministic sequences of reactions. The language constructs are inspired by regular expressions and process algebra (sequence, choice, loop, concurrency). Moreover, the set of statements can be enriched with user-defined operators. A notion of stochastic directives is also provided in order to finely influence the selection of a particular class of scenarios.

We present an operational model for describing random reactive systems. Some models have already been proposed for this purpose, but they generally aim at performing global reasoning on systems, such as stochastic analysis, or formal proofs. Our goal is somehow less ambitious, since we are rather interested in executing such models, for testing or prototyping. But on the other hand, the proposed model is not restricted by decidability issues. Therefore it can be more expressive: in particular, our model is not restricted to finite-state descriptions. The proposed model is rather general: systems are described as implicit state/transition machines, possibly infinite, where probabilities are expressed by means of relative weights. The model itself is more an abstract machine than a programming language. The idea is then to propose highlevel, user-friendly languages that can be compiled into the model. We present such a language, based on regular expressions, together with its translation into the model.

This paper presents a language based on regular expressions for describing non-deterministic reactive systems. It also presents some ideas on how to build (or adapt) tools for exploiting such a language (recognizers, generators and provers).