Hybrid Probabilistic Relational Models for System Quality Analysis

The formalism Probabilistic Relational Models (PRM) couples discrete Bayesian Networks with a modeling formalism similar to UML class diagrams and has been used for architecture analysis. PRMs are well-suited to perform architecture analysis with respect to system qualities since they support both modeling and analysis within the same formalism. A particular strength of PRMs is the ability to perform meaningful analysis of domains where there is a high level of uncertainty, as is often the case when performing system quality analysis. However, the use of discrete Bayesian networks in PRMs complicates the analysis of continuous phenomena. The main contribution of this paper is the Hybrid Probabilistic Relational Models (HPRM) formalism which extends PRMs to enable continuous analysis thus extending the applicability for architecture analysis and especially for trade-off analysis of system qualities. HPRMs use hybrid Bayesian networks which allow combinations of discrete and continuous variables. In addition to presenting the HPRM formalism, the paper contains an example which details the use of HPRMs for architecture trade-off analysis.