Towards Automatic Generation of Ontology-based Antipattern Bayesian Network Models

D. Settas, A. Cerone, S. Fenz:
"Towards Automatic Generation of Ontology-based Antipattern Bayesian Network Models";
Vortrag: 9th International Conference on Software Engineering Research, Management and Applications (SERA 2011), Baltimore, Maryland USA; 10.08.2011 - 12.08.2011; in:"Proceedings of the 9th International Conference on Software Engineering Research, Management and Applications (SERA 2011)", (2011), S. 46 - 53.

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Abstract:


Previous work has proposed the ontology-based
semi-automatic generation of antipattern Bayesian Network
(BN) models. The generated BN model can be used to illustrate
the effects of uncertainty on antipatterns using Bayesian
propagation. This can guide users in detecting particular
antipattern attributes of importance based on uncertain onto-
logical information. However, the proposed approach has been
implemented in the Protege ontology editor environment and
requires human intervention to specify how the BN model will
be generated. The fully automated generation of ontology-based
antipattern BN models still remains an open issue. SPARSE
is an OWL ontology based intelligent system that assists
software project managers in the antipattern detection process.
In this paper, we propose the use of the resulting detected
antipatterns of SPARSE, their attributes (i.e. causes, symptoms,
consequences) and the ontological relationships between these
attributes, in order to automatically generate BN models of the
detected antipatterns. We illustrate how this approach can be
implemented using an example of 8 antipattern attributes of 6
inter-related antipatterns detected using SPARSE.