P2AMF: Predictive, probabilistic architecture modeling framework
2013 (English)In: Lecture Notes in Business Information Processing, 2013, 104-117 p.Conference paper (Refereed)
In the design phase of business and software system development, it is desirable to predict the properties of the system-to-be. Existing prediction systems do, however, not allow the modeler to express uncertainty with respect to the design of the considered system. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P 2AMF), capable of advanced and probabilistically sound reasoning about architecture models given in the form of UML class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P2AMF adds a probabilistic inference mechanism. The paper introduces P2AMF, describes its use for system property prediction and assessment, and proposes an algorithm for probabilistic inference.
Place, publisher, year, edition, pages
2013. 104-117 p.
, Lecture Notes in Business Information Processing, ISSN 1865-1348 ; 144
class diagram, Object Constraint Language, object diagram, prediction, probabilistic inference, system properties, UML, Class diagrams, Object diagrams, System property, Forecasting, Industry, Interoperability, Markup languages, Inference engines
IdentifiersURN: urn:nbn:se:kth:diva-134654DOI: 10.1007/978-3-642-36796-0-10ISI: 000345294000010ScopusID: 2-s2.0-84875673907ISBN: 9783642367953ISBN: 978-3-642-36796-0OAI: oai:DiVA.org:kth-134654DiVA: diva2:678126
5th International IFIP Working Conference on Enterprise Interoperability, IWEI 2013, 27 March 2013 through 28 March 2013, Enschede
QC 201312112013-12-112013-11-272015-01-15Bibliographically approved