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This paper presents a novel approach for developing simulation metamodels using Gaussian radial basis functions. This approach is based on some recently developed mathematical results for radial basis functions. It is systematic, explicitly controls the underfitting and overfitting tradeoff, and uses a fast computational algorithm that requires minimal(More)
This paper presents an analysis of actual software error data from a large-scale software project using the imperfect debugging model proposed by Goel and Okumoto [1]. The model parameters are estimated from the actual data and the values predicted from the model are compared with the observed values. Joint confidence regions for the parameters are also(More)
—Modeling to predict fault­proneness of software modules is an important area of research in software engineering. Most such models employ a large number of basic and derived metrics as predictors. This paper presents modeling results based on only two metrics, lines of code and cyclomatic complexity, using radial basis functions with Gaussian kernels as(More)