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The GRADE taxonomy for supporting decision making asset selection in software-intensive system development
Swedish Institute of Computer Science, SWE.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Mälardalens högskola, SWE.
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2018 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 100, p. 1-17Article in journal (Refereed) Published
Abstract [en]

Context: The development of software-intensive systems includes many decisions involving various stakeholders with often conflicting interests and viewpoints. Objective: Decisions are rarely systematically documented and sporadically explored. This limits the opportunity for learning and improving on important decisions made in the development of software-intensive systems. Method: In this work, we enable support for the systematic documentation of decisions, improve their traceability and contribute to potentially improved decision-making in strategic, tactical and operational contexts. Results: We constructed a taxonomy for documentation supporting decision-making, called GRADE. GRADE was developed in a research project that required composition of a common dedicated language to make feasible the identification of new opportunities for better decision support and evaluation of multiple decision alternatives. The use of the taxonomy has been validated through thirty three decision cases from industry. Conclusion: This paper occupies this important yet greatly unexplored research gap by developing the GRADE taxonomy that serves as a common vocabulary to describe and classify decision-making with respect to architectural assets. © 2018 Elsevier B.V.

Place, publisher, year, edition, pages
Elsevier B.V. , 2018. Vol. 100, p. 1-17
Keywords [en]
Decision-making, Knowledge management, Software engineering, Taxonomy, Decision support systems, Software design, Taxonomies, Classify decision makings, Decision supports, Software intensive systems, Decision making
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-16171DOI: 10.1016/j.infsof.2018.02.007ISI: 000435056100001Scopus ID: 2-s2.0-85046163169OAI: oai:DiVA.org:bth-16171DiVA, id: diva2:1205150
Available from: 2018-05-11 Created: 2018-05-11 Last updated: 2018-07-05Bibliographically approved

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Wnuk, KrzysztofPetersen, KaiGorschek, Tony

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  • apa
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