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Uncertainty Modeling and Evaluation for Dependable IoT Cloud Systems Design

Aktivität: Vortrag oder PräsentationVortrag nach Bewerbung und AuswahlScience-to-science

Beschreibung

Developing dependable complex applications using IoT and cloud services is very challenging. Using service APIs and client libraries the developer can glue various software capabilities to build complex IoT Cloud applications but the developer also needs to arbitrarily extend and model functional and quality aspects of new components, connectors, and their interactions. Hence, knowledge about existing IoT Cloud and modeling is crucial. However, due to the lack of knowledge and the complexity of IoT Cloud Systems, the developer might introduce or might not be able to detect various types of uncertainties, which strongly influence the application. In this talk we aim at detecting such uncertainties and recommend software design to deal with such uncertainties as early as possible. We model and evaluate potential uncertainties on design artifacts representing structural and/or behavioral information about the system under study. We propose a rule-based Uncertainty Modeling and Evaluation methodology (UME) and tool (T4UME) to help users in detecting potential uncertainties on design artifacts and to decide whether or not refactoring strategies should be applied to uncertain system design artifacts. In particular, our framework deals with uncertainty as a crosscutting, multidisciplinary concept by providing proper extension and customisation mechanism to suitably tailor its adoption to different domains.
Zeitraum19 Juli 2020
EreignistitelUncertainty Modeling and Evaluation for Dependable IoT Cloud Systems Design, ISSTA July 16, 2020
VeranstaltungstypKonferenz
OrtÖsterreichAuf Karte anzeigen

Wissenschaftszweige

  • 202017 Embedded Systems
  • 102006 Computer Supported Cooperative Work (CSCW)
  • 201132 Computational Engineering
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  • 102002 Augmented Reality
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  • 102015 Informationssysteme
  • 102040 Quantencomputing
  • 509026 Digitalisierungsforschung
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  • 102016 IT-Sicherheit

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  • Digital Transformation