Abstract
A methodology is presented to quantitatively model the expected relationships between investments in process improvements and improvements in business measures. Such a predictive model can be used as an auxiliary in process improvement planning in addition to established models like CMMI. Different from a generic model like CMMI, the proposed methodology allows for creating a fully customized model focusing on the context or product at hand. To manage the inherent parameter uncertainty of quantitative modelling of software processes a novel approach in this context is used by explicitly handling the parameter variations using interval arithmetic. The paper outlines the methodology and presents results from a study at Siemens.
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Birkhölzer, T., Dickmann, C., Klein, H., Vaupel, J., Ast, S., Meyer, L. (2008). Customized Predictive Models for Process Improvement Projects. In: Jedlitschka, A., Salo, O. (eds) Product-Focused Software Process Improvement. PROFES 2008. Lecture Notes in Computer Science, vol 5089. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69566-0_25
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DOI: https://doi.org/10.1007/978-3-540-69566-0_25
Publisher Name: Springer, Berlin, Heidelberg
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