P2AMF: Predictive, Probabilistic Architecture Modeling Framework - Enterprise Interoperability Access content directly
Conference Papers Year : 2013

P2AMF: Predictive, Probabilistic Architecture Modeling Framework

Abstract

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 (P2AMF), 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.
Fichier principal
Vignette du fichier
978-3-642-36796-0_10_Chapter.pdf (407.27 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01474204 , version 1 (22-02-2017)

Licence

Attribution

Identifiers

Cite

Pontus Johnson, Johan Ullberg, Markus Buschle, Ulrik Franke, Khurram Shahzad. P2AMF: Predictive, Probabilistic Architecture Modeling Framework. 5th International Working Conference on Enterprise Interoperability (IWEI), Mar 2013, Enschede, Netherlands. pp.104-117, ⟨10.1007/978-3-642-36796-0_10⟩. ⟨hal-01474204⟩
72 View
151 Download

Altmetric

Share

Gmail Facebook X LinkedIn More