Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic inference and influence diagrams
Operations Research
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Automatic Synthesis of Dynamic Fault Trees from UML System Models
ISSRE '02 Proceedings of the 13th International Symposium on Software Reliability Engineering
Learning Bayesian Networks
Enterprise architecture analysis with extended influence diagrams
Information Systems Frontiers
Combining Defense Graphs and Enterprise Architecture Models for Security Analysis
EDOC '08 Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference
A Framework for Service Interoperability Analysis using Enterprise Architecture Models
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 2
Using Architectural Models to Predict the Maintainability of Enterprise Systems
CSMR '08 Proceedings of the 2008 12th European Conference on Software Maintenance and Reengineering
Automatic fault tree derivation from Little-JIL process definitions
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
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Analysis of dependencies between technical systems and business processes is an important part of the discipline of Enterprise Architecture (EA). However, EA models typically provide only visual and qualitative decision support. This paper shows how EA frameworks for dependency analysis can be extended into the realm of quantitative methods by use of the Fault Tree Analysis (FTA) and Bayesian networks (BN) techniques. Using DoDAF -- the Department of Defense Architecture Framework -- as an example, we provide a method for how these EA models can be adapted for use of FTA and BN. Furthermore, we use this method to perform dependency analysis and scenario evaluation on a sample DoDAF model.