Using sensitivity analysis to create simplified economic models for regression testing
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
On the effectiveness of early life cycle defect prediction with Bayesian Nets
Empirical Software Engineering
Exact scalable sensitivity analysis for the next release problem
ACM Transactions on Software Engineering and Methodology (TOSEM)
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There are various models in software engineering that are used to predict quality-related aspects of the process or artefacts. The use of these models involves elaborate data collection in order to estimate the input parameters. Hence, an interesting question is which of these input factors are most important. More specifically, which factors need to be estimated best and which might be removed from the model? This paper describes an approach based on global sensitivity analysis to answer these questions and shows its applicability in a case study on the COCOMO application at NASA.