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Leveraging domain expertise in architectural exploration
conference contributionposted on 2015-11-17, 09:32 authored by Henry Broodny, Michael Masin, Evgeny Shindin, Uri Shani, Roy KalawskyRoy Kalawsky, Demetrios Joannou, Yingchun Tian, Antara Bhatt, Imad Sanduka
Domain experience is a key driver behind design quality, especially during the early design phases of a product or service. Currently, the only practical way to bring such experience into a project is to directly engage subject matter experts, which means there is the potential for a resource availability bottleneck because the experts are not available when required. Whilst many domain specific tools have attempted to capture expert knowledge in embedded analytics thus allowing less experienced engineers to perform complex tasks, this is certainly not the case for highly complex systems of systems where their architectures can go far beyond what a single human being can comprehend. This paper proposes a new approach to leveraging design expertise in a manner that facilitates architectural exploration and architecture optimization by using pre-defined architecture patterns. In addition, we propose a means to streamline such a process by delineating the knowledge creation process and architectural exploration analytics with the means to facilitate information flow from the former to the latter through a carefuly designed integration framework.
This work is partially funded by the FP7 DANSE project (grant number 287716), and the SPRINT project (grant number 257909).
- Mechanical, Electrical and Manufacturing Engineering
Published inComplex Systems Design & Management
Pages87 - 103
CitationBROODNY, H. ...et al., 2014. Leveraging Domain Expertise in Architectural Exploration. IN: Boulanger, F. ... et al.(eds.) Complex Systems Design & Management: Proceedings of the Fifth International Conference on Complex Systems Design & Management CSD&M 2014, Paris, pp. 87-103.
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Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThis paper is in closed access.