423 research outputs found

    Soundness analytics of composed logical workflow nets

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    Cooperative systems with passing value indeterminacy and batch processing can be well modeled by composed logical workflow nets. Soundness guarantees no deadlock and livelock and each activity has potential to be executed. The soundness of composed logical workflow nets can be judged by reachability graphs. But reachability graphs can cause state space explosion. Path nets, single line nets, composed path nets and composed single line nets are proposed in the paper. They are used to determine soundness of logical workflow nets and composed logical workflow nets based on net structures and logical expressions avoiding reachability graphs. The presented concepts and techniques are applied to judge soundness of e-commerce transaction processes modeled by composed logical workflow nets, and they are illustrated by an example

    Property Analysis of Composable Web services

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    Web services are basic components constructing a flexible business process software. By composing multiple Web services, a complicated business process across organization and departments can be formed. This paper present a formal model of composable Web services: composed service process nets (CSPNs). Properties of Composable Web services are analyzed based on CSPNs. The relation between a CSPN and its corresponding Web service process subnets are discussed. The property analysis methods of CSPNs are come up with. A dynamic property of CSPNs can be determined based on static net structures by means of the proposed methods

    Formalization and Model Checking of BPMN Collaboration Diagrams with DD-LOTOS

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    Business Process Model and Notation (BPMN) is a standard graphical notation for modeling complex business processes. Given the importance of business processes, the modeling analysis and validation stage for BPMN is essential. In recent years, BPMN notation has become a widespread practice in business process modeling because of these intuitive diagrams. BPMN diagrams are built from basic elements. The major challenge of BPMN diagrams is the lack of formal semantics, which leads to several interpretations of the concerned diagrams. Hence, this work aims to propose an approach for checking BPMN collaboration diagrams to guarantee some properties of smooth functioning of systems modeled by BPMN notation. The verification approach used in this work is based on model checking techniques. The approach proposes as a first step a formal semantics of the collaboration diagrams in terms of the formal language DD-LOTOS, i.e., a phase of the transformation of collaboration diagrams into DD-LOTOS. This transformation is guided by applying the inference rules of the formal semantics of the DD-LOTOS formal language, and we then use the UPPAAL model checker to check the absence of deadlock, safety properties, and liveness properties

    Formalization of BPMN Gateways using the DD-LOTOS Formal Language

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    Business Process Model and Notation (BPMN), is a standardized graphical language used for the graphical modeling of business processes. A BPMN model is composed of several small graphs called elements; these elements make it possible to describe the activities, the events, and the interactions between the components of a business process. Among the essential elements of BPMN are gateways, which control the flow of data. However, the big challenge of these gateways is the existence of several interpretations of the same BPMN model containing gateways; this is due to the informal and ambiguous definition. Several works have proposed the formalization of gateways using formal languages such as process algebras, Petri nets, etc. The purpose of this article is to propose a formalization of BPMN gateways using the formal language DD-LOTOS. DDLOTOS is defined on a semantics of true parallelism called maximality semantics and allows to support distribution and temporal constraints. We then propose the verification of certain properties using the UPPAAL model checker. Our approach has been validated through a case study representing the online purchasing process

    Obstructions in Security-Aware Business Processes

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    This Open Access book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software

    Scalable discovery of hybrid process models in a cloud computing environment

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    Process descriptions are used to create products and deliver services. To lead better processes and services, the first step is to learn a process model. Process discovery is such a technique which can automatically extract process models from event logs. Although various discovery techniques have been proposed, they focus on either constructing formal models which are very powerful but complex, or creating informal models which are intuitive but lack semantics. In this work, we introduce a novel method that returns hybrid process models to bridge this gap. Moreover, to cope with today’s big event logs, we propose an efficient method, called f-HMD, aims at scalable hybrid model discovery in a cloud computing environment. We present the detailed implementation of our approach over the Spark framework, and our experimental results demonstrate that the proposed method is efficient and scalabl

    Third Workshop on Modelling of Objects, Components, and Agents

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    This booklet contains the proceedings of the Third International Workshop on Modelling of Objects, Components, and Agents (MOCA'04), October 11-13, 2004. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark and the "Theoretical Foundations of Computer Science" group at the University of Hamburg. The home page of the workshop is: http://www.daimi.au.dk/CPnets/workshop0

    Verification of soundness and other properties of business processes

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    In this thesis we focus on improving current modeling and verification techniques for complex business processes. The objective of the thesis is to consider several aspects of real-life business processes and give specific solutions to cope with their complexity. In particular, we address verification of a proper termination property for workflows, called generalized soundness. We give a new decision procedure for generalized soundness that improves the original decision procedure. The new decision procedure reports on the decidability status of generalized soundness and returns a counterexample in case the workflow net is not generalized sound. We report on experimental results obtained with the prototype implementation we made and describe how to verify large workflows compositionally, using reduction rules. Next, we concentrate on modeling and verification of adaptive workflows — workflows that are able to change their structure at runtime, for instance when some exceptional events occur. In order to model the exception handling properly and allow structural changes of the system in a modular way, we introduce a new class of nets, called adaptive workflow nets. Adaptive workflow nets are a special type of Nets in Nets and they allow for creation, deletion and transformation of net tokens at runtime and for two types of synchronizations: synchronization on proper termination and synchronization on exception. We define some behavioral properties of adaptive workflow nets: soundness and circumspectness and employ an abstraction to reduce the verification of these properties to the verification of behavioral properties of a finite state abstraction. Further, we study how formal methods can help in understanding and designing business processes. We investigate this for the extended event-driven process chains (eEPCs), a popular industrial business process language used in the ARIS Toolset. Several semantics have been proposed for EPCs. However, most of them concentrated solely on the control flow. We argue that other aspects of business processes must also be taken into account in order to analyze eEPCs and propose a semantics that takes data and time information from eEPCs into account. Moreover, we provide a translation of eEPCs to Timed Colored Petri nets in order to facilitate verification of eEPCs. Finally, we discuss modeling issues for business processes whose behavior may depend on the previous behavior of the process, history which is recorded by workflow management systems as a log. To increase the precision of models with respect to modeling choices depending on the process history, we introduce history-dependent guards. The obtained business processes are called historydependent processes.We introduce a logic, called LogLogics for the specification of guards based on a log of a current running process and give an evaluation algorithm for such guards. Moreover, we show how these guards can be used in practice and define LogLogics patterns for properties that occur most commonly in practice

    Workflow models for heterogeneous distributed systems

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    The role of data in modern scientific workflows becomes more and more crucial. The unprecedented amount of data available in the digital era, combined with the recent advancements in Machine Learning and High-Performance Computing (HPC), let computers surpass human performances in a wide range of fields, such as Computer Vision, Natural Language Processing and Bioinformatics. However, a solid data management strategy becomes crucial for key aspects like performance optimisation, privacy preservation and security. Most modern programming paradigms for Big Data analysis adhere to the principle of data locality: moving computation closer to the data to remove transfer-related overheads and risks. Still, there are scenarios in which it is worth, or even unavoidable, to transfer data between different steps of a complex workflow. The contribution of this dissertation is twofold. First, it defines a novel methodology for distributed modular applications, allowing topology-aware scheduling and data management while separating business logic, data dependencies, parallel patterns and execution environments. In addition, it introduces computational notebooks as a high-level and user-friendly interface to this new kind of workflow, aiming to flatten the learning curve and improve the adoption of such methodology. Each of these contributions is accompanied by a full-fledged, Open Source implementation, which has been used for evaluation purposes and allows the interested reader to experience the related methodology first-hand. The validity of the proposed approaches has been demonstrated on a total of five real scientific applications in the domains of Deep Learning, Bioinformatics and Molecular Dynamics Simulation, executing them on large-scale mixed cloud-High-Performance Computing (HPC) infrastructures
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