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Discovering and Assessing Enterprise Architecture Debts
Frankfurt University of Applied Sciences, Frankfurt am Main, Germany.
KTH Royal Institute of Technology, Stockholm, Sweden.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.ORCID iD: 0000-0003-0478-9347
Frankfurt University of Applied Sciences, Frankfurt am Main, Germany.
Number of Authors: 42023 (English)In: Complex Systems Informatics and Modeling Quarterly, E-ISSN 2255-9922, Vol. 2023, no 35, p. 1-29Article in journal (Refereed) Published
Abstract [en]

The term Enterprise Architecture (EA) Debts has been coined to grasp the difference between the actual state of the EA and its hypothetical, optimal state. So far, different methods have been proposed to identify such EA Debts in organizations. However, these methods either are based on the transfer of known concepts from other domains to EA or are time and resource intensive. To overcome these shortcomings, we propose an approach that uses an interview format to identify EA Debts in enterprises and a method that allows a qualitative assessment of identified EA Debts. The proposed approach is supported by the designed framework that consists of an interview format and a process for determining thresholds of certain EA Smells.

Place, publisher, year, edition, pages
2023. Vol. 2023, no 35, p. 1-29
Keywords [en]
Enterprise Architecture, Quality Assessment, EA, Debts, Determination
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-219838DOI: 10.7250/csimq.2023-35.01Scopus ID: 2-s2.0-85167973146OAI: oai:DiVA.org:su-219838DiVA, id: diva2:1785620
Available from: 2023-08-03 Created: 2023-08-03 Last updated: 2024-10-16Bibliographically approved

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Hacks, Simon

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