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The QDAcity-RE method for structural domain modeling using qualitative data analysis

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Abstract

The creation of domain models from qualitative input relies heavily on experience. An uncodified ad-hoc modeling process is still common and leads to poor documentation of the analysis. In this article we present a new method for domain analysis based on qualitative data analysis. The method helps identify inconsistencies, ensures a high degree of completeness, and inherently provides traceability from analysis results back to stakeholder input. These traces do not have to be documented after the fact. We evaluate our approach using four exploratory studies.

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Notes

  1. http://www.maxqda.com.

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Acknowledgements

We would like to thank Katharina Kunz, Florian Schmitt and Benjamin Mempel for their valuable contributions executing the exploratory studies. We would also like to thank all anonymous interview partners as well as Siemens Healthcare, Deutsche Bahn and the openETCS project for participating in our studies and providing valuable feedback to improve our method. Finally, thanks to Hannes Dohrn, Maximilian Capraro, Michael Dorner, Nikolay Harutyunyan and Daniel Knogl for workshopping this paper to improve its presentation, and to Ann Barcomb for proofreading.

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  1. Department of Computer Science, Friedrich-Alexander-University Erlangen Nürnberg, Martensstr. 3, 91052, Erlangen, Germany

    Andreas Kaufmann & Dirk Riehle

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  1. Andreas Kaufmann
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Correspondence to Andreas Kaufmann.

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Kaufmann, A., Riehle, D. The QDAcity-RE method for structural domain modeling using qualitative data analysis. Requirements Eng 24, 85–102 (2019). https://doi.org/10.1007/s00766-017-0284-8

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