Security policy refinement and enforcement for the design of multi-level secure systems
Journal of Computer Security - Privacy, Security and Trust (PST) Technologies: Evolution and Challenges
Architecture-based refinements for secure computer systems design
Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services
A framework for automated generation of architectural feedback from software performance analysis
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
A model-based framework for software performance feedback
MODELS'10 Proceedings of the 2010 international conference on Models in software engineering
Software performance antipatterns: modeling and analysis
SFM'12 Proceedings of the 12th international conference on Formal Methods for the Design of Computer, Communication, and Software Systems: formal methods for model-driven engineering
Using enterprise architecture analysis and interview data to estimate service response time
The Journal of Strategic Information Systems
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The structure of a software architecture strongly influences the architecture's ability to prescribe systems satisfying functional requirements, non-functional requirements, and overall qualities such as maintainability, reusability, and performance. Achieving an acceptable architecture requires an iterative derivation and evaluation process that allows refinementbased on a series of tradeoffs. Researchers at the University of Texas at Austin are developing a suite of processes and supporting tools to guide architecture derivation from requirements acquisition through system design. The various types of decisions needed forconcurrent derivation and evaluation demand a synthesis of evaluation techniques, because no single technique is suitable for all concerns of interest. Two tools in this suite, RARE and ARCADE, cooperate to enable iterative architecture derivation and architecture propertyevaluation. RARE guides derivation by employing a heuristics knowledge base, and evaluates the resulting architecture by applying static property evaluation based on structural metrics. ARCADE provides dynamic property evaluation leveraging simulation and model-checking.This paper presents a study whereby RARE and ARCADE were employed in the early stages of an industrial project to derive a Domain Reference Architecture (DRA), a high-level architecture capturing domain functionality, data, and timing. The discussion emphasizes early evaluation of performance qualities, and illustrates how ARCADE and RARE cooperate toenable iterative derivation and evaluation. These evaluations influenced DRA refinement as well as subsequent design decisions involving application implementation and computing platform selection.