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.

International audienceWe propose a operational model for describing non-deterministic reactive systems, together with a mechanism for expressing probability issues. Some models have already been proposed for this purposes, but they are generally intended to allow global reasoning on systems (e.g. stockastic analysis, formal proofs). Our goal is somehow less ambitious, sinve we are mainly interested in executing such models, which can be useful for testing, prototyping. On the other hand, the proposed model is not strongly restricted because of decidability concerns, so it is likely to be more expressive: in particular, we are not restricted to finite-state models. 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 high-level, 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

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