Abstract
The target of this research is to develop an automatic and quantitative methodology and tool combination using text analyses, data mining and machine learning for the analyses of process oriented international quality approaches and documented quality systems of organizations in the field of software development. Such comparisons require at the moment lots of engineering work by experts thus resulting in inefficient human resource utilization. Our long-term goal is to have a tool that enables the auditors and other stakeholders in a software organization to perform quantitative and automatic pre-assessment about the conformance of the organizations’ documented quality systems compared to international quality approach(es) with efficient human resource utilization. This article is presenting the results of searching for the optimal methodology via comparing CMMI-DEV 1.3 and HiS Scope of Automotive Spice 2.5 standards and creating similarity maps.
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Karaffy, Z., Balla, K. (2015). Applying Text Analyses and Data Mining to Support Process Oriented Multimodel Approaches. In: O’Connor, R., Umay Akkaya, M., Kemaneci, K., Yilmaz, M., Poth, A., Messnarz, R. (eds) Systems, Software and Services Process Improvement. EuroSPI 2015. Communications in Computer and Information Science, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-319-24647-5_15
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DOI: https://doi.org/10.1007/978-3-319-24647-5_15
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