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Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies
KTH Royal Institute of Technology, Sweden.
KTH Royal Institute of Technology, Sweden.
KTH Royal Institute of Technology, Sweden.
RISE - Research Institutes of Sweden, ICT, SICS. (Software and Systems Engineering Laboratory)ORCID iD: 0000-0003-2017-7914
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2017 (English)In: Complex Systems Informatics and Modeling, ISSN 2255-9922, Vol. 11, p. 38-68Article in journal (Refereed) Published
Abstract [en]

The Multi-Attribute Prediction Language (MAPL), an analysis metamodel for non-functional qualities of system architectures, is introduced. MAPL features automate analysis in five non-functional areas: service cost, service availability, data accuracy, application coupling, and application size. In addition, MAPL explicitly includes utility modeling to make trade-offs between the qualities. The article introduces how each of the five non-functional qualities are modeled and quantitatively analyzed based on the ArchiMate standard for enterprise architecture modeling and the previously published Predictive, Probabilistic Architecture Modeling Framework, building on the well-known UML and OCL formalisms. The main contribution of MAPL lies in the probabilistic use of multi-attribute utility theory for the trade-off analysis of the non-functional properties. Additionally, MAPL proposes novel model-based analyses of several non-functional attributes. We also report how MAPL has iteratively been developed using multiple case studies.

Place, publisher, year, edition, pages
2017. Vol. 11, p. 38-68
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-32988DOI: 10.7250/csimq.2017-11.03OAI: oai:DiVA.org:ri-32988DiVA, id: diva2:1170497
Available from: 2018-01-03 Created: 2018-01-03 Last updated: 2018-08-16Bibliographically approved

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Publisher's full texthttp://dx.doi.org/10.7250/csimq.2017-11.03

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Franke, Ulrik

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