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Validation of Metrics as Error Predictors

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Metrics for Process Models

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 6))

Abstract

In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

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© 2008 Springer-Verlag Berlin Heidelberg

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Mendling, J. (2008). Validation of Metrics as Error Predictors. In: Metrics for Process Models. Lecture Notes in Business Information Processing, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89224-3_5

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  • DOI: https://doi.org/10.1007/978-3-540-89224-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89223-6

  • Online ISBN: 978-3-540-89224-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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