Abstract. Verification and simulation have always been complementary, if not competing, approaches to system design. In this paper, we present a novel method for so-called metric transition systems that bridges the gap between verification and simulation, enabling system verification using a finite number of simulations. The existence of metrics on the system state and observation spaces, which is natural for continuous systems, allows us to capitalize on the recently developed framework of approximate bisimulations, and infer the behavior of neighborhood of system trajectories around a simulated trajectory. For nondeterministic linear systems that are robustly safe or robustly unsafe, we provide not only a completeness result but also an upper bound on the number of simulations required as a function of the distance between the reachable set and the unsafe set. Our framework is the first simulation-based verification method that enjoys completeness for infinite-state systems. The complexity is low for robustly safe or robustly unsafe systems, and increases for nonrobust problems. This provides strong evidence that robustness dramatically impacts the complexity of system verification and design. 1

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Abstract. Timed concurrent systems are widely used in concurrent and distributed real-time software, modeling of hybrid systems, design of hardware systems (using hardware description languages), discrete-event simulation, and modeling of communication networks. They consist of concurrent components that communicate using timed signals, that is, sets of (semantically) time-stamped events. The denotational semantics of such systems is traditionally formulated in a metric space, wherein causal components are modeled as contracting functions. We show that this formulation excessively restricts the models of time that can be used. In particular, it cannot handle super-dense time, commonly used in hardware description languages and hybrid systems modeling, finite time lines, and time with no origin. Moreover, if we admit continuoustime and mixed signals (essential for hybrid systems modeling) or certain Zeno signals, then causality is no longer equivalent to its formalization in terms of contracting functions. In this paper, we offer an alternative semantic framework using a generalized ultrametric that overcomes these limitations. 1

In this paper, we consider concurrent models of computation where ”actors” (components that are in charge of their own actions) communicate by exchanging messages. The interfaces of actors principally consist of “ports,” which mediate the exchange of messages. Actor-oriented architectures contrast with and complement object-oriented models by emphasizing the exchange of data between concurrent components rather than transfer of control. Examples of such models of computation include the classical actor model, synchronous languages, dataflow models, and discrete-event models. Many of these models of computation benefit considerably from having access to causality information about the components. This paper augments the interfaces of such components to include such causality information. It shows how this causality information can be algebraically composed so that compositions of components acquire causality interfaces that are inferred from their components and the interconnections. We illustrate the use of these causality interfaces to statically analyze discrete-event models for uniqueness of behaviors, synchronous models for causality loops, and dataflow models for schedulability.

Abstract — Deterministic timed systems can be modeled as fixed point problems [15], [16], [4]. In particular, any connected network of timed systems can be modeled as a single system with feedback, and the system behavior is the fixed point of the corresponding system equation, when it exists. For delta-causal systems, we can use the Cantor metric to measure the distance between signals and the Banach fixed-point theorem to prove the existence and uniqueness of a system behavior. Moreover, the Banach fixed-point theorem is constructive: it provides a method to construct the unique fixed point through iteration. In this paper, we extend this result to systems modeled with the superdense model of time [7], [8] used in hybrid systems. We call the systems we consider eventually delta-causal, a strict generalization of delta-causal in which multiple events may be generated on a signal in zero time. With this model of time, we can use a generalized ultrametric [14] instead of a metric to model the distance between signals. The existence and uniqueness of behaviors for such systems comes from the fixedpoint theorem of [13], but this theorem gives no constructive method to compute the fixed point. This leads us to define petrics, a generalization of metrics, which we use to generalize the Banach fixed-point theorem to provide a constructive fixed-point theorem. This new fixedpoint theorem allows us to construct the unique behavior of eventually delta-causal systems. I.

Abstract. In this paper we propose a technique to extend the simulation of a Zeno hybrid system beyond its Zeno time point. A Zeno hybrid system model is a hybrid system with an execution that takes an infinite number of discrete transitions during a finite time interval. We argue that the presence of Zeno behavior indicates that the hybrid system model is incomplete by considering some classical Zeno models that incompletely describe the dynamics of the system being modeled. This motivates the systematic development of a method for completing hybrid system models through the introduction of new post-Zeno states, where the completed hybrid system transitions to these post-Zeno states at the Zeno time point. In practice, simulating a Zeno hybrid system is challenging in that simulation effectively halts near the Zeno time point. Moreover, due to unavoidable numerical errors, it is not practical to exactly simulate a Zeno hybrid system. Therefore, we propose a method for constructing approximations of Zeno models by leveraging the completed hybrid system model. Using these approximation, we can simulate a Zeno hybrid system model beyond its Zeno point and reveal the complete dynamics of the system being modeled. 1

Ptolemy is an open-source and extensible modeling and simulation framework. It offers heterogeneous modeling capabilities by allowing different models of computation to be composed hierarchically in an arbitrary fashion. This paper describes modal models, which allow to hierarchically compose finite-state machines with other models of computation, both untimed and timed. The semantics of modal models in Ptolemy are defined in a modular manner.

Abstract Hybrid systems combine continuous-time and discrete behaviours. Simulation is one of the tools to obtain insight in dynamical systems behaviour. Simulation results provide information on performance of system and are helpful in detecting potential weaknesses and errors. Moreover, the results are handy in choosing adequate control strategies and parameters. In our contribution we report a work in progress, a technique for simulation of Behavioural Hybrid Process Calculus, an extension of process algebra that is suitable for the modelling and analysis of hybrid systems. 1

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