Discovering and Assessing Enterprise Architecture Debts

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Abstract

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.

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Daoudi, S., Larsson, M., Hacks, S., & Jung, J. (2023). Discovering and Assessing Enterprise Architecture Debts. Complex Systems Informatics and Modeling Quarterly, 2023(35), 1–29. https://doi.org/10.7250/csimq.2023-35.01

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