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.
In my opinion it is false to conclude from the non-functional relation of the reactive systems to their interaction partners to their somehow non-functional functioning - or ''mode of operation''. Even reactive systems work in a step wise mode and at least for technical systems the simple fact holds that for being constructable, there has to be a function to be implemented - the system function. The main difference between ''transformational'' and ''reactive'' systems in the sense of David Harel and Amir Pnueli is not their functioning but - as they correctly point out - their relation to their environment. For ''transformational'' systems their interfaces towards the interaction provides access to the full system function and thereby provides deterministic interactions. ''transformational'' systems are composed hierarchically by composition according to the definition of sub super systems . By contrast, as I proposed already in @cite_3 , the interfaces of ''reactive'' systems provide access to at least two different projections of the systems, which I call ''roles'' and thereby only provide nondeterministic interactions.
@cite_3
2099640060
Algorithmic Debugging is a theory of debugging that uses queries on the compositional semantics of a program in order to localize bugs. It uses the following principle: if a computation of a program's component gives an incorrect result, while all the subcomputations it invokes compute correct results, then the code of this component is erroneous. Algorithmic Debugging is applied, in this work, to reactive systems, in particular to programs written in Flat Concurrent Prolog (FCP). Debugging reactive systems is known to be more difficult than the debugging of functional systems. A functional system is fully described by the relation between its initial input and final output; this context-freedom is used in debugging. A reactive system continuously responds to external inputs, thus its debugging cannot make use of context-free input output relations. Given a compositional semantic model for a concurrent programming language, we demonstrate how one can directly apply the ideas of Algorithmic Debugging to obtain a theory of program debugging for the considered language. The conflict between the context-freedom of input output relations and the reactive nature of concurrent systems is resolved by using semantic objects which record the reactive nature of the system's components. In functional algorithmic debugging the queries relate to input output relations; in concurrent algorithmic debugging the queries refer to semantic objects called processes which capture the reactive nature of FCP computations. A diagnosis algorithm for incorrect FCP programs is proposed. The algorithm gets an erroneous computation and using queries isolates an erroneous clause or an incomplete procedure. An FCP implementation of the diagnosis algorithm demonstrates the usefulness as well as the difficulties of Algorithmic Debugging of FCP programs. We propose a vision of a grasp-based interaction system where users' intentions are inferred by the way they hold and interact with a device. In this paper we specifically discuss the Bar of Soap, a multi-function handheld prototype that uses grasp-based interactions to switch between modes. This prototype relies on the hypothesis that users share a set of stereotyped grasps associated with common multi-function modes. We show that using common machine learning techniques our device can reliably distinguish five separate classes based on the users' grasps. While this interaction is currently implemented in a multi-function handheld, we anticipate the existence of many scenarios where grasp recognition could provide a more intuitive or useful interface. Established system relationships for discrete systems, such as language inclusion, simulation, and bisimulation, require system observations to be identical. When interacting with the physical world, modeled by continuous or hybrid systems, exact relationships are restrictive and not robust. In this paper, we develop the first framework of system approximation that applies to both discrete and continuous systems by developing notions of approximate language inclusion, approximate simulation, and approximate bisimulation relations. We define a hierarchy of approximation pseudo-metrics between two systems that quantify the quality of the approximation, and capture the established exact relationships as zero sections. Our approximation framework is compositional for a synchronous composition operator. Algorithms are developed for computing the proposed pseudo-metrics, both exactly and approximately. The exact algorithms require the generalization of the fixed point algorithms for computing simulation and bisimulation relations, or dually, the solution of a static game whose cost is the so-called branching distance between the systems. Approximations for the pseudo-metrics can be obtained by considering Lyapunov-like functions called simulation and bisimulation functions. We illustrate our approximation framework in reducing the complexity of safety verification problems for both deterministic and nondeterministic continuous systems Reactive transport modeling is often used in support of bioremediation and chemicaltreatment planning and design. There remains a pressing need for practical andefficient models that do not require (or assume attainable) the high level ofcharacterization needed by complex numerical models. We focus on a linear systems ortransfer function approach to the problem of reactive tracer transport in a heterogeneoussaprolite aquifer. Transfer functions are obtained through the Bayesian geostatisticalinverse method applied to tracer injection histories and breakthrough curves. We employnonparametric transfer functions, which require minimal assumptions about shape andstructure. The resulting flexibility empowers the data to determine the nature of thetransfer function with minimal prior assumptions. Nonnegativity is enforced through areflected Brownian motion stochastic model. The inverse method enables us to quantifyuncertainty and to generate conditional realizations of the transfer function. Complexinformation about a hydrogeologic system is distilled into a relatively simple butrigorously obtained function that describes the transport behavior of the system betweentwo wells. The resulting transfer functions are valuable in reactive transport models basedon traveltime and streamline methods. The information contained in the data,particularly in the case of strong heterogeneity, is not overextended but is fully used. Thisis the first application of Bayesian geostatistical inversion to transfer functions inhydrogeology but the methodology can be extended to any linear system.