A system model is developed where the criterion to partition the world into a system and a rest is based on the functional relation between its states. This approach implies that the gestalt of systems becomes very dynamic. Especially interactions between systems may create temporary super systems "on the fly". The reference to the function notion establishes the link to computation. Based on the distinction between the intended determinism versus nondeterminism of the interaction, two classes of system interactions are distinguished: composition and cooperation. Composition means that by interaction super systems are created and the interacting systems become subsystems. Cooperation means that systems sensibly interact loosely without creating any identifiable super system function and therefore without super system creation from the perspective of the interacting systems. Cooperative system interactions are described with the help of the protocol notion based on shared states, interpreted as the stateful exchange of characters via Shannon channels between roles - the projection of systems onto the interaction channels. It is shown that roles can be internally coordinated by a set of rules, leading to a very flexible process notion which unfolds its full potential only in a new type of execution environment capable of executing spontaneous transitions. The system model has immediate implications for componentization which can be viewed as an attempt to either hide functional recursion and provide only functionality whose composition behavior is easy to understand, or to provide loosely coupled interactions via protocols. To be complete, component models should therefore at least support three general classes of components: one for loose coupling, one for hierarchical composition, and one for pipes.
BIP stands for Behavior, Interaction, and Priority @cite_54 @cite_16 @cite_57 . It is a general framework to describe reactive systems from certain parts with a set of rules. In my view, BIP is a way to describe computational systems in the sense of this article: a BIP-component provides states and a transition function. By its priority mechanism, together with a given port, there is supposed to be a unique transition to be selected.
@cite_57 @cite_54 @cite_16
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An autonomous robot case study illustrates the use of the behavior, interaction, priority (BIP) component framework as a unifying semantic model to ensure correctness of essential system design properties. We present a methodology for modeling heterogeneous real-time components. Components are obtained as the superposition of three layers : Behavior, specified as a set of transitions; Interactions between transitions of the behavior; Priorities, used to choose amongst possible interactions. A parameterized binary composition operator is used to compose components layer by layer. We present the BIP language for the description and composition of layered components as well as associated tools for executing and analyzing components on a dedicated platform. The language provides a powerful mechanism for structuring interactions involving rendezvous and broadcast. We show that synchronous and timed systems are particular classes of components. Finally, we provide examples showing the utility of the BIP framework in heterogeneous component modeling. We present a methodology for modeling heterogeneous real-time components. Components are obtained as the superposition of three layers : Behavior, specified as a set of transitions; Interactions between transitions of the behavior; Priorities, used to choose amongst possible interactions. A parameterized binary composition operator is used to compose components layer by layer. We present the BIP language for the description and composition of layered components as well as associated tools for executing and analyzing components on a dedicated platform. The language provides a powerful mechanism for structuring interactions involving rendezvous and broadcast. We show that synchronous and timed systems are particular classes of components. Finally, we provide examples and compare the BIP framework to existing ones for heterogeneous component-based modeling. Functional Reactive Programming , or FRP , is a general framework for programming hybrid systems in a high-level, declarative manner. The key ideas in FRP are its notions of behaviors and events . Behaviors are time-varying, reactive values, while events are time-ordered sequences of discrete-time event occurrences. FRP is the essence of Fran , a domain-specific language embedded in Haskell for programming reactive animations, but FRP is now also being used in vision, robotics and other control systems applications. In this paper we explore the formal semantics of FRP and how itrelates to an implementation based on streams that represent (and therefore only approximate) continuous behaviors. We show that, in the limit as the sampling interval goes to zero, the implementation is faithful to the formal, continuous semantics, but only when certain constraints on behaviors are observed. We explore the nature of these constraints, which vary amongst the FRP primitives. Our results show both the power and limitations of this approach to language design and implementation. As an example of a limitation, we show that streams are incapable of representing instantaneous predicate events over behaviors.