A Method for Choosing Software Assessment Measures Using Bayesian Networks and Diagnosis

Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, but the monetary aspects of the modeling of software systems are not equally well acknowledged. The present paper describes a method using Bayesian networks for optimizing modeling strategies, perceived as a trade-off between these two aspects. Using GeNIe, a graphical tool with the proper Bayesian algorithms implemented, decision support can thus be provided to the modeling process. Specifically, an informed trade-off can be made, based on the modeler’s prior knowledge of the predictive power of certain models, combined with his projection of their costs. It is argued that this method might enhance modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling...

• Type: Conference
• Year: 2009
• Where: CSMR
• Authors: Ulrik Franke, Pontus Johnson, Robert Lagerström, Johan Ullberg, David Höök, Mathias Ekstedt, Johan König
• Keywords: CSMR 2009, Modeling Strategies, Proper Bayesian Algorithms, Software Systems