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 @cite_43 David Harel and Amir Pnueli distinguish between ''transformational'' and ''reactive'' systems. They define: "A transformational system accepts input, performs transformation on them and produces outputs'' - which is consistent with the definition of a system. They further define ''Reactive systems ... are repeatedly prompted by the outside world and their role is to continuously respond to external inputs ... A reactive system, in general, does not compute or perform a function, but is supposed to maintain a certain ongoing relationship, so to speak, with its environment.''
@cite_43
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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. The role of Temporal Logic as a feasible approach to the specification and verification of concurrent systems is now widely accepted. A companion paper in this volume ([HP]) defines more precisely the area of applicability of Temporal Logic as that of reactive systems. In this paper we present an extension of logic programming (LP) that is suitable not only for the “rational” component of a single agent but also for the “reactive” component and that can encompass multidagent systems. We modify an earlier abductive proof procedure and embed it within an agent cycle. The proof procedure incorporates abduction, definitions and integrity constraints within a dynamic environment, where changes can be observed as inputs. The definitions allow rational planning behaviour and the integrity constraints allow reactive, conditiondaction type behaviour. The agent cycle provides a resourcedbounded mechanism that allows the agent’s thinking to be interrupted for the agent to record and assimilate observations as input and execute actions as output, before resuming further thinking. We argue that these extensions of LP, accommodating multidtheories embedded in a shared environment, provide the necessary multidagent functionality. We argue also that our work extends Shoham’s Agent0 and the BDI architecture. This paper presents the TGV tool, which allows for the automatic synthesis of conformance test cases from a formal specification of a (non-deterministic) reactive system. TGV was developed by Irisa Rennes and Verimag Grenoble, with the support of the Vasy team of Inria Rhones-Alpes. The paper describes the main elements of the underlying testing theory, which is based on a model of transitions system which distinguishes inputs, outputs and internal actions, and is based on the concept of conformance relation. The principles of the test synthesis process, as well as the main algorithms, are explained. We then describe the main characteristics of the TGV tool and refer to some industrial experiments that have been conducted to validate the approach. As a conclusion, we describe some ongoing work on test synthesis.