Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies
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 a...
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| Format: | Article |
| Language: | English |
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Riga Technical University Press
2017-07-01
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| Series: | Complex Systems Informatics and Modeling Quarterly |
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| Online Access: | https://csimq-journals.rtu.lv/article/view/1784 |
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| _version_ | 1832542978050097152 |
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| author | Robert Lagerström Pontus Johnson Mathias Ekstedt Ulrik Franke Khurram Shahzad |
| author_facet | Robert Lagerström Pontus Johnson Mathias Ekstedt Ulrik Franke Khurram Shahzad |
| author_sort | Robert Lagerström |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c89bbef7ccd84715baa7e96c41962f67 |
| institution | Kabale University |
| issn | 2255-9922 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Riga Technical University Press |
| record_format | Article |
| series | Complex Systems Informatics and Modeling Quarterly |
| spelling | doaj-art-c89bbef7ccd84715baa7e96c41962f672025-02-03T12:03:19ZengRiga Technical University PressComplex Systems Informatics and Modeling Quarterly2255-99222017-07-01011386810.7250/csimq.2017-11.031016Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case StudiesRobert Lagerström0Pontus Johnson1Mathias Ekstedt2Ulrik Franke3Khurram Shahzad4KTH Royal Institute of Technology, Osquldas väg 12, 100 44 StockholmKTH Royal Institute of Technology, Osquldas väg 12, 100 44 StockholmKTH Royal Institute of Technology, Osquldas väg 12, 100 44 StockholmRISE Research Institutes of Sweden, SICS Swedish Institute of Computer Science, KistaKTH Royal Institute of Technology, Osquldas väg 12, 100 44 StockholmThe 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.https://csimq-journals.rtu.lv/article/view/1784System architecturearchitecture analysissystem modelingprobabilistic analysis. |
| spellingShingle | Robert Lagerström Pontus Johnson Mathias Ekstedt Ulrik Franke Khurram Shahzad Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies Complex Systems Informatics and Modeling Quarterly System architecture architecture analysis system modeling probabilistic analysis. |
| title | Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies |
| title_full | Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies |
| title_fullStr | Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies |
| title_full_unstemmed | Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies |
| title_short | Automated Probabilistic System Architecture Analysis in the Multi-Attribute Prediction Language (MAPL): Iteratively Developed using Multiple Case Studies |
| title_sort | automated probabilistic system architecture analysis in the multi attribute prediction language mapl iteratively developed using multiple case studies |
| topic | System architecture architecture analysis system modeling probabilistic analysis. |
| url | https://csimq-journals.rtu.lv/article/view/1784 |
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