242,734 research outputs found

    Specifying and analysing reputation systems with coordination languages

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    Reputation systems are nowadays widely used to support decision making in networked systems. Parties in such systems rate each other and use shared ratings to compute reputation scores that drive their interactions. The existence of reputation systems with remarkable differences calls for formal approaches to their analysis. We present a verification methodology for reputation systems that is based on the use of the coordination language Klaim and related analysis tools. First, we define a parametric Klaim specification of a reputation system that can be instantiated with different reputation models. Then, we consider stochastic specification obtained by considering actions with random (exponentially distributed) duration. The resulting specification enables quantitative analysis of properties of the considered system. Feasibility and effectiveness of our proposal is demonstrated by reporting on the analysis of two reputation models

    Fuzzy specification in software engineering

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    Judging quality of any decision making procedure is a key problem whenever there is no possibility of developing a sequence of experiments allowing some kind of ratio relative to good results. It may be the case that we have only chances for a unique experiment or no similar experiences are available, but it may be also the case that no standard experiment allows the observation of such a good behavior, simply because such good behavior can not be properly defined. This situation is quite often associated to complex decision making problems. Then the only support we can find for our decision is the decision process itself, the consistency of the arguments leading to such a decision. Checking the quality of such a procedure is therefore a key issue. In this paper we postulate that the design and formal specification of algorithms and processes require a fuzzy approach, since quite often specification is being poorly dened

    Reactive system verification case study: Fault-tolerant transputer communication

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    A reactive program is one which engages in an ongoing interaction with its environment. A system which is controlled by an embedded reactive program is called a reactive system. Examples of reactive systems are aircraft flight management systems, bank automatic teller machine (ATM) networks, airline reservation systems, and computer operating systems. Reactive systems are often naturally modeled (for logical design purposes) as a composition of autonomous processes which progress concurrently and which communicate to share information and/or to coordinate activities. Formal (i.e., mathematical) frameworks for system verification are tools used to increase the users' confidence that a system design satisfies its specification. A framework for reactive system verification includes formal languages for system modeling and for behavior specification and decision procedures and/or proof-systems for verifying that the system model satisfies the system specifications. Using the Ostroff framework for reactive system verification, an approach to achieving fault-tolerant communication between transputers was shown to be effective. The key components of the design, the decoupler processes, may be viewed as discrete-event-controllers introduced to constrain system behavior such that system specifications are satisfied. The Ostroff framework was also effective. The expressiveness of the modeling language permitted construction of a faithful model of the transputer network. The relevant specifications were readily expressed in the specification language. The set of decision procedures provided was adequate to verify the specifications of interest. The need for improved support for system behavior visualization is emphasized

    Toward a decision support system for the clinical pathways assessment

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    This paper presents a decision support system to be used in hospital management taskswhich is based on the clinical pathways. We propose a very simple graphical modeling lan-guage based on a small number of primitive elements through which the medical doctorscould introduce a clinical pathway for a specific disease. Three essential aspects relatedto a clinical pathway can be specified in this language: (1) patient flow; (2) resource uti-lization; and (3) information interchange. This high-level language is a domain specificmodeling language calledHealthcare System Specification (HSS), and it is defined as anUnified Modeling Language (UML) profile. A model to model transformation is also pro-posed in order to obtain, from the pathways HSS specification, a Stochastic Well-formedNet (SWN) model that enables a formal analysis of the modeled system and, if needed, toapply synthesis methods enforcing specified requirements. The transformation is based onthe application of local rules. The clinical pathway of hip fracture from the “Lozano Blesa”University hospital in Zaragoza is taken as an example

    Tackling Dierent Business Process Perspectives

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    Business Process Management (BPM) has emerged as a discipline to design, control, analyze, and optimize business operations. Conceptual models lie at the core of BPM. In particular, business process models have been taken up by organizations as a means to describe the main activities that are performed to achieve a specific business goal. Process models generally cover different perspectives that underlie separate yet interrelated representations for analyzing and presenting process information. Being primarily driven by process improvement objectives, traditional business process modeling languages focus on capturing the control flow perspective of business processes, that is, the temporal and logical coordination of activities. Such approaches are usually characterized as \u201cactivity-centric\u201d. Nowadays, activity-centric process modeling languages, such as the Business Process Model and Notation (BPMN) standard, are still the most used in practice and benefit from industrial tool support. Nevertheless, evidence shows that such process modeling languages still lack of support for modeling non-control-flow perspectives, such as the temporal, informational, and decision perspectives, among others. This thesis centres on the BPMN standard and addresses the modeling the temporal, informational, and decision perspectives of process models, with particular attention to processes enacted in healthcare domains. Despite being partially interrelated, the main contributions of this thesis may be partitioned according to the modeling perspective they concern. The temporal perspective deals with the specification, management, and formal verification of temporal constraints. In this thesis, we address the specification and run-time management of temporal constraints in BPMN, by taking advantage of process modularity and of event handling mechanisms included in the standard. Then, we propose three different mappings from BPMN to formal models, to validate the behavior of the proposed process models and to check whether they are dynamically controllable. The informational perspective represents the information entities consumed, produced or manipulated by a process. This thesis focuses on the conceptual connection between processes and data, borrowing concepts from the database domain to enable the representation of which part of a database schema is accessed by a certain process activity. This novel conceptual view is then employed to detect potential data inconsistencies arising when the same data are accessed erroneously by different process activities. The decision perspective encompasses the modeling of the decision-making related to a process, considering where decisions are made in the process and how decision outcomes affect process execution. In this thesis, we investigate the use of the Decision Model and Notation (DMN) standard in conjunction with BPMN starting from a pattern-based approach to ease the derivation of DMN decision models from the data represented in BPMN processes. Besides, we propose a methodology that focuses on the integrated use of BPMN and DMN for modeling decision-intensive care pathways in a real-world application domain

    Knowledge engineering with semantic web technologies for decision support systems based on psychological models of expertise

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    Machines that provide decision support have traditionally used either a representation of human expertise or used mathematical algorithms. Each approach has its own limitations. This study helps to combine both types of decision support system for a single system. However, the focus is on how the machines can formalise and manipulate the human representation of expertise rather than on data processing or machine learning algorithms. It will be based on a system that represents human expertise in a psychological format. The particular decision support system for testing the approach is based on a psychological model of classification that is called the Galatean model of classification. The simple classification problems only require one XML structure to represent each class and the objects to be assigned to it. However, when the classification system is implemented as a decision support system within more complex realworld domains, there may be many variations of the class specification for different types of object to be assigned to the class in different circumstances and by different types of user making the classification decision. All these XML structures will be related to each other in formal ways, based on the original class specification, but managing their relationships and evolution becomes very difficult when the specifications for the XML variants are text-based documents. For dealing with these complexities a knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. The aim is to explore how semantic web technologies can be employed to help the knowledge engineering process for decision support systems based on human expertise, but deployed in complex domains with variable circumstances. The research evaluated OWL as a suitable vehicle for representing psychological expertise. The task was to see how well it can provide a machine formalism for the knowledge without losing its psychological validity or transparency: that is, the ability of end users to understand the knowledge representation intuitively despite its OWL format. The OWL Galatea model is designed in this study to help in automatic knowledge maintenance, reducing the replication of knowledge with variant uncertainties and support in knowledge engineering processes. The OWL-based approaches used in this model also aid in the adaptive knowledge management. An adaptive assessment questionnaire is an example of it, which is dynamically derived using the users age as the seed for creating the alternative questionnaires. The credibility of the OWL Galatea model is tested by applying it on two extremely different assessment domains (i.e. GRiST and ADVANCE). The conclusions are that OWLbased specifications provide the complementary structures for managing complex knowledge based on human expertise without impeding the end users’ understanding of the knowledgebase. The generic classification model is applicable to many domains and the accompanying OWL specification facilitates its implementations

    An Object Oriented and Axiomatic Theory of Warehouse Design

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    Despite the conceptual simplicity of warehousing, the development of integrated computational tools for warehouse design has remained an elusive goal. In recent years, there has been some progress toward this goal, with a growing body of research addressing topics as diverse as the design process itself, decision support for specific design decisions, warehouse representation, integrating warehouse representation and analysis, and conceptual approaches for developing integrated warehouse design tool chains. Until now, however, there has not been a suitable warehouse design theory that would provide an integrating framework for all these disparate efforts. This paper presents an object-oriented and axiomatic warehouse design theory. Key assumptions about the warehouse to be designed are stated as axioms, with appropriate formalisms. Using the axioms and the associated notation, a formal specification of warehouse requirements can be stated, a formal description for a warehouse design can be given, and methods can be developed for testing the warehouse design against the requirements. Moreover, the axioms provide the foundation for identifying essential warehouse design decisions, and formally stating both the criteria for evaluating those decisions and the constraints limiting those decisions. The paper provides a conceptual and rigorous bridge between the process-oriented research on warehouse design process or workflow, and the mathematically oriented approach to warehouse design reflected in the vast literature on mathematical models and algorithms for specific warehouse design and/or operating decision
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