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Abstract. In complex systems, like robot plants, applications are built on top of a set of components, or devices. Each of them has particular individual constraints, and there are also logical constraints on their interactions, related to e.g., mechanical characteristics or access to shared resources. Managing these constraints may be separated from the application, and performed by an intermediate layer.We show how to build such property-enforcing layers, in a mixed imperative/declarative style: 1) the constraints intrinsic to one component are modeled by an automaton; the product of these automata is a first approximation of the set of constraints that should be respected; 2) the constraints that involve several components are expressed as temporal logic properties of this product; 3) we use general controller synthesis techniques and tools in order to combine the set of communicating parallel automata with the global constraint.

In this paper we study to what extent implementation of timed automata can be achieved using the standard semantics and appropriate modeling, instead of introducing new semantics. We propose an implementation methodology which allows to transform a timed automaton into a program and to check whether the execution of this program on a given platform satisfies a desired property. This is done by modeling the program and the execution platform, respectively, as an untimed automaton and a collection of timed automata. We also study the problem of property preservation, in particular when moving to a "better" execution platform. We show that some subtleties arise regarding the definition of "better", in particular for digital clocks. The fundamental issue is that faster clocks result in better "sampling" and therefore can introduce more behaviors.

We present novel techniques for efficient controller synthesis for untimed and timed systems with respect to invariance and reachability properties. In the untimed case, we give algorithms for controller synthesis in the context of finite graphs with controllable and uncontrollable edges, distinguishing between the actions of the system and its environment, respectively. The algorithms are on-the-fly, since they return a controller as soon as one is found, which avoids the generation of the whole state space. In the timed case, we use the model of timed automata extended with controllable and uncontrollable discrete transitions. Our controller-synthesis method here is only half on-the-fly, since it relies on the a-priori generation of a finite model (graph) of the timed automaton, as quotient of the time-abstracting bisimulation. The quotient graph is essentially an untimed graph, upon which we can apply the untimed on-the-fly algorithms to compute a timed controller.

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Abstract-We present an approach to connect the Real-Time Calculus (RTC) method to the synchronous data-flow language Lustre, and its associated tool-chain, allowing the use of techniques like SMT-solving and abstract interpretation which were not previously available for use with RTC. The approach is supported by a tool called ac2lus. It allows to model the system to be analyzed as general Lustre programs with inputs specified by arrival curves; the tool can compute output arrival curves or evaluate upper and lower bounds on any variable of the components, like buffer sizes. Compared to existing approaches to connect RTC to other formalisms, we believe that the use of Lustre, a real programming language, and the synchronous hypothesis make the task easier to write models, and we show that it allows a great flexibility of the tool itself, with many variants to fine-tune the performances.

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To analyze complex and heterogeneous real-time embedded systems, recent works have proposed interface techniques between real-time calculus (RTC) and timed automata (TA), in order to take advantage of the strengths of each technique for analyzing various components. But the time to analyze a state-based component modeled by TA may be prohibitively high, due to the state space explosion problem. In this paper, we propose a framework of granularity-based interfacing to speed up the analysis of a TA modeled component. First, we abstract fine models to work with event streams at coarse granularity. We perform analysis of the component at multiple coarse granularities and then based on RTC theory, we derive lower and upper bounds on arrival patterns of the fine output streams using the causality closure algorithm of [2]. Our framework can help to achieve tradeoffs between precision and analysis time.