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Using Machine Learning Techniques for Evaluating the Similarity of Enterprise Architecture Models

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Advanced Information Systems Engineering (CAiSE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11483))

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Abstract

Enterprises Architectures (EA) are facilitated to coordinate enterprise’s business visions and strategies successfully and effectively. The practitioners of EA (architects) communicate the architecture to other stakeholders via architecture models. We investigate the scenario where accepted architecture models are stored in a repository. We identified the problem of unnecessary repository expansion by adding model components with similar properties or behavior as already existing repository components. The proposed solution aims to find those similar components and to notify the architect about their existence.

We present two approaches for defining and combining similarities between EA model components. The similarity measures are calculated upon the properties of the components and on the context of their usage. We further investigate the behavior of similar architecture models and search for associations in order to obtain components that might be of interest. At the end, we provide a prototype tool for both generating requests and obtaining a result.

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Notes

  1. 1.

    https://www.cs.waikato.ac.nz/ml/weka.

  2. 2.

    https://cran.r-project.org/web/packages/arules/index.html.

  3. 3.

    https://www.archimatetool.com.

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Authors and Affiliations

  1. Research Group Software Construction, RWTH Aachen University, Aachen, Germany

    Vasil Borozanov & Simon Hacks

  2. Department of Computer Science and Engineering, Technical University of Lisbon, Lisbon, Portugal

    Nuno Silva

Authors
  1. Vasil Borozanov
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  2. Simon Hacks
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  3. Nuno Silva
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Corresponding author

Correspondence to Simon Hacks .

Editor information

Editors and Affiliations

  1. University of Trento, Trento, Italy

    Paolo Giorgini

  2. University of St. Gallen, St. Gallen, Switzerland

    Barbara Weber

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Borozanov, V., Hacks, S., Silva, N. (2019). Using Machine Learning Techniques for Evaluating the Similarity of Enterprise Architecture Models. In: Giorgini, P., Weber, B. (eds) Advanced Information Systems Engineering. CAiSE 2019. Lecture Notes in Computer Science(), vol 11483. Springer, Cham. https://doi.org/10.1007/978-3-030-21290-2_35

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  • DOI: https://doi.org/10.1007/978-3-030-21290-2_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21289-6

  • Online ISBN: 978-3-030-21290-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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