Abstract
The evaluation of a system’s architecture is an essential process within the systems engineering lifecycle. Commercially available model-based systems engineering (MBSE) tools, when combined with standards-based architecture modeling languages, provide a means through which architecture information can be expressed graphically and formally in a machine-readable format; this format can be leveraged in order to improve the system architecture evaluation process. The authors propose an automated, repeatable method for detecting patterns of interest embedded within an MBSE model. This novel method uses a heuristically guided set of similarity measures that depend on textual and graphical content of a model. The proposed method has been implemented for architectures developed in IBM’s Rational Rhapsody, and No Magic Inc.’s MagicDraw, and has proven to be able to identify six well-established patterns: Adapter, Bridge, Composite, Façade, Observer, and Proxy. This automation has the potential to produce cost and time savings for the evaluation process and to add an additional degree of rigor and completeness to an architecture evaluation.
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Acknowledgments
\The authors would like to acknowledge Sanith Wijesinghe and Tom Wheeler for the continuous support, advocacy, and guidance throughout the course of this research. The authors would also like to thank our collaborators, Huy Tran and Karl Thomson (University of Illinois), without whom this research, and the complimentary technical products, would not have been successful. Finally, the authors thank all reviewers of this publication for their thoughtful, thorough, and detailed feedback.
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Cotter, M., Hadjimichael, M., Markina-Khusid, A., York, B. (2022). Automated Detection of Architecture Patterns in MBSE Models. In: Madni, A.M., Boehm, B., Erwin, D., Moghaddam, M., Sievers, M., Wheaton, M. (eds) Recent Trends and Advances in Model Based Systems Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-82083-1_8
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DOI: https://doi.org/10.1007/978-3-030-82083-1_8
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