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Titlebook: Business Modeling and Software Design; 10th International S Boris Shishkov Conference proceedings 2020 Springer Nature Switzerland AG 2020

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Making Enterprise Information Systems Resilient Against Disruptive Events: A Conceptual ViewQUENCE-BASED RISK MANAGEMENT rather than traditional .. We augment this approach with the .-. paradigm, delivering a contribution that is two-fold: (i) We propose .-. and .-., to address .; (ii) We reflect this in a . .-. . . . ..
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1865-1348 ch took place in Berlin, Germany, in July 2020. ..BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Mo
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Gianluca Iazzolino,Nicole Stremlaurst conceptual model view is built using a literature review. The next model views include the details found by analysis of existing SLA’s. The novelty of our models is that they compose an SLA from service level objectives (SLO’s), explain the meaning of SLO’s monitoring, support execution of an SLA and expose the monitoring logics.
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https://doi.org/10.1007/978-3-030-53563-6ely for vulnerabilities as early as possible. We developed a pattern recognition framework (PRF) that enables the definition of design patterns and anti-patterns. These patterns are used for a holistic and automated identification of flaws in IoT models during design phase and enable a design optimization.
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Mediation – nicht einfach nur ein Verfahren! existing business process, where the concepts for comparison are found inside the model of the existing system and compared with the concepts used in the model of the modified system. These cases identify two ways of selecting concepts for comparison that help to make the key decision to implement or not implement a proposed system model.
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Design Optimization of IoT Models: Structured Safety and Security Flaw Identificationely for vulnerabilities as early as possible. We developed a pattern recognition framework (PRF) that enables the definition of design patterns and anti-patterns. These patterns are used for a holistic and automated identification of flaws in IoT models during design phase and enable a design optimization.
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