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- Title
An architecture modeling framework for probabilistic prediction.
- Authors
Johnson, Pontus; Ullberg, Johan; Buschle, Markus; Franke, Ulrik; Shahzad, Khurram
- Abstract
In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (PAMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, PAMF adds a probabilistic inference mechanism. The paper introduces PAMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.
- Subjects
PROBABILISTIC inference; UNIFIED modeling language; PROGRAMMING languages; COMPUTER architecture; ARCHITECTURE Analysis &; Design Language
- Publication
Information Systems & e-Business Management, 2014, Vol 12, Issue 4, p595
- ISSN
1617-9846
- Publication type
Article
- DOI
10.1007/s10257-014-0241-8