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.
Manfred Broy describes his component model in several articles (e.g. @cite_4 @cite_12 @cite_24 ). The behavior of a system is given by a set of ''input'' and ''output'' processes, whereby a process in his sense is a finite or infinite set of discrete events. The event concept is not entirely clear, as on the one hand, an event may represent (among others) a state change or some action, but on the other hand he states that an event represents a point in time and thus has no time duration. Also, it remains unclear, whether event sequences like @math and @math are semantically equivalent or not.
@cite_24 @cite_4 @cite_12
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We consider the scenario where the executions of different business processes are traced into a log, where each trace describes a process instance as a sequence of low-level events representing basic kinds of operations. In this context, we address a novel problem: given a description of the processes' behaviors in terms of high-level activities instead of low-level events, and in the presence of uncertainty in the mapping between events and activities, find all the interpretations of each trace @math . Specifically, an interpretation is a pair @math that provides a two-level "explanation" for @math : @math is a sequence of activities that may have triggered the events in @math , and W is a process whose model admits @math . To solve this problem, we propose a probabilistic framework representing "consistent" @math 's interpretations, where each interpretation is associated with a probability score. The paper concerns the synthesis of supervisory controllers for a class of continuous-time hybrid systems with discrete-valued input signals that select differential inclusions for continuous-valued state trajectories and event-valued output signals generated by threshold crossings in the continuous state space, the supervisor is allowed to switch the input signal value when threshold events are observed. The objective is to synthesize a nonblocking supervisor such that the set of possible sequences of control and threshold event pairs for the closed-loop system lies between given upper and lower bounds in the sense of set containment. We show how this problem can be converted into a supervisor synthesis problem for a standard controlled discrete-event system (DES). A finite representation may not exist for the exact DES model of the hybrid system, however. To circumvent this difficulty, we present an algorithm for constructing finite-state Muller automata that accept outer approximations to the exact controlled threshold-event language, and we demonstrate that supervisors that solve the synthesis problem for the approximating automata achieve the control specifications when applied to the original hybrid system. In this paper, we present a framework and a system that extracts events relevant to a query from a collection C of documents, and places such events along a timeline. Each event is represented by a sentence extracted from C, based on the assumption that "important" events are widely cited in many documents for a period of time within which these events are of interest. In our experiments, we used queries that are event types ("earthquake") and person names (e.g. "George Bush"). Evaluation was performed using G8 leader names as queries: comparison made by human evaluators between manually and system generated timelines showed that although manually generated timelines are on average more preferable, system generated timelines are sometimes judged to be better than manually constructed ones. In this paper we recast the classical Darondeau---Degano's causal semantics of concurrency in a coalgebraic setting, where we derive a compact model. Our construction is inspired by the one of Montanari and Pistore yielding causal automata, but we show that it is instance of an existing categorical framework for modeling the semantics of nominal calculi, whose relevance is further demonstrated. The key idea is to represent events as names, and the occurrence of a new event as name generation. We model causal semantics as a coalgebra over a presheaf, along the lines of the Fiore---Turi approach to the semantics of nominal calculi. More specifically, we take a suitable category of finite posets, representing causal relations over events, and we equip it with an endofunctor that allocates new events and relates them to their causes. Presheaves over this category express the relationship between processes and causal relations among the processes' events. We use the allocation operator to define a category of well-behaved coalgebras: it models the occurrence of a new event along each transition. Then we turn the causal transition relation into a coalgebra in this category, where labels only exhibit maximal events with respect to the source states' poset, and we show that its bisimilarity is essentially Darondeau---Degano's strong causal bisimilarity. This coalgebra is still infinite-state, but we exploit the equivalence between coalgebras over a class of presheaves and History Dependent automata to derive a compact representation, where states only retain the poset of the most recent events for each atomic subprocess, and are isomorphic up to order-preserving permutations. Remarkably, this reduction of states is automatically performed along the equivalence.