Date of Award
Winter 2011
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computational Modeling & Simulation Engineering
Program/Concentration
Modeling and Simulation
Committee Director
Andreas Tolk
Committee Member
Frederic D. McKenzie
Committee Member
Charles Keating
Committee Member
Thomas Pawlowski
Abstract
The objective of this dissertation study is to conduct a holistic investigation into the elements of executable architectures. Current research in the field of Executable Architectures has provided valuable solution-specific demonstrations and has also shown the value derived from such an endeavor. However, a common theory underlying their applications has been missing.
This dissertation develops and explores a method for holistically developing an Executable Architecture Specification (EAS), i.e., a meta-model containing both semantic and syntactic information, using a conceptual framework for guiding data coding, analysis, and validation. Utilization of this method resulted in the description of the elements of executable architecture in terms of a set of nine information interrogatives: an executable architecture information ontology. Once the detail-rich EAS was constructed with this ontology, it became possible to define the potential elements of executable architecture through an intermediate level meta-model. The intermediate level meta-model was further refined into an interrogative level meta-model using only the nine information interrogatives, at a very high level of abstraction.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
DOI
10.25777/v5k3-0128
ISBN
9781267112620
Recommended Citation
Shuman, Edwin A..
"Understanding the Elements of Executable Architectures Through a Multi-Dimensional Analysis Framework"
(2011). Doctor of Philosophy (PhD), Dissertation, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/v5k3-0128
https://digitalcommons.odu.edu/msve_etds/40