Abstract
To validate a treatment is to justify that it would contribute to stakeholder goals when implemented in the problem context. If the requirements for the treatment are specified and justified, then we can validate a treatment by showing that it satisfies its requirements. The central problem of treatment validation is that no real-world implementation is available to investigate whether the treatment contributes to stakeholder goals. Still, we want to predict what will happen if the treatment is implemented. This problem is explained in Sect. 7.1. To solve it, design researchers build validation models of the artifact in context and investigate these models (Sect. 7.2). Based on these modeling studies, researchers develop a design theory of the artifact in context and use this theory to predict the effects of an implemented artifact in the real world (Sect. 7.3). We review some of the research methods to develop and test design theories in Sect. 7.4. These methods play a role in the process of scaling up an artifact from the idealized conditions of the laboratory to the real-world conditions of practice. This is explained in Sect. 7.5.
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References
I. Alexander, L. Beus-Dukic, Discovering Requirements: How to Specify Products and Services (Wiley, Hoboken, 2009)
L. Apostel, Towards a formal study of models in the non-formal sciences, in The Concept and Role of the Model in the Mathematical and the Natural and Social Sciences, ed. by H. Freudenthal (Reidel, Dordrecht, 1961), pp. 1–37
W. Engelsman, R.J. Wieringa, Goal-oriented requirements engineering and enterprise architecture: Two case studies and some lessons learned, in Requirements Engineering: Foundation for Software Quality (REFSQ 2012), Essen, Germany. Lecture Notes in Computer Science, vol. 7195 (Springer, Heidelberg, 2012), pp. 306–320
R.L. Glass, V. Ramesh, I. Vessey, An analysis of research in the computing disciplines. Commun. ACM 47(6), 89–94 (2004)
R.L. Glass, I. Vessey, V. Ramesh, Research in software engineering: an empirical study. Technical Report TR105-1, Information Systems Department, Indiana University, September 2001
T. Gorschek, C. Wohlin, P. Garre, S. Larsson, A model for technology transfer in practice. IEEE Softw. 23(6), 88–95 (2006)
M.A. Jackson, Problem Frames: Analysing and Structuring Software Development Problems (Addison-Wesley, Boston, 2000)
A. Kaplan, The Conduct of Inquiry. Methodology for Behavioral Science (Transaction Publishers, Piscataway, 1998); First edition 1964 by Chandler Publishers
L.P.W. Land, C. Sauer, R. Jeffrey, The use of procedural roles in code inspections: An experimental study. Empir. Softw. Eng. 5(1), 11–34 (2000)
S. Lauesen, Software Requirements: Styles and Techniques (Addison-Wesley, Reading, 2002)
M.S. Morgan, M. Morrison, Models as mediating instruments, in Models as Mediators. Perspectives on Natural and Social Science, ed. by M.S. Morgan, M. Morrison (Cambridge university Press, Cambridge, 1999)
R. Müller, The notion of a model: A historical overview, in Philosophy of Technology and Engineering Sciences, ed. by A. Meijers (Elsevier, Amsterdam, 2009), pp. 637–664
L. Prechelt, B. Unger-Lamprecht, M. Philippsen, W.F. Tichy, Two controlled experiments assessing the usefulness of design pattern documentation in program maintenance. IEEE Trans. Softw. Eng. 28(6), 595–606 (2002)
J.D. Vrielink, Phased array processing: Direction of arrival estimation on reconfigurable hardware. Master’s thesis, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, January 2009. http://essay.utwente.nl/62065/
R. Wieringa, Empirical research methods for technology validation: Scaling up to practice. J. Syst. Softw. (2013). http://dx.doi.org/10.1016/j.jss.2013.11.1097
P. Willner, Methods for assessing the validity of animal models of human psychopathology, in Animal Models in Psychiatry I, ed. by A. Boultin, G. Baker, M. Martin-Iverson. Neuromethods, vol.18 (The Humana Press, New York, 1991), pp. 1–23
M.V. Zelkowitz, D. Wallace, Experimental models for validating technology. Computer 31(5), 23–31 (1998)
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Wieringa, R.J. (2014). Treatment Validation. In: Design Science Methodology for Information Systems and Software Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43839-8_7
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DOI: https://doi.org/10.1007/978-3-662-43839-8_7
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