Author: Robert J. Allen
Ph.D. Thesis, Carnegie Mellon University,CMU Technical Report CMU-CS-97-144, May 1997
As software systems become more complex, the overall system structure---or software architecture---becomes a central design problem. A system's architecture provides a model of the system that suppresses implementation detail, allowing the architect to concentrate on the analyses and decisions that are most crucial to structuring the system to satisfy its requirements.
Unfortunately, current representations of software architecture are informal and ad hoc. While architectural concepts are often embodied in infrastructure to support specific architectural styles and in the initial conceptualization of a system configuration, the lack of an explicit, independently-characterized architecture or architectural style significantly limits the benefits of software architectural design in current practice.
In this dissertation, I show that an Architecture Description Language based on a formal, abstract model of system behavior can provide a practical means of describing and analyzing software architectures and architectural styles. This dissertation demonstrates this claim through Wright, an architectural description language based on the formal description of the abstract behavior of architectural components and connectors. Wright provides a practical formal basis for the description of both architectural configurations and of architectural styles. It is distinguished by the use of explicit, independent connector types as interaction patterns, the ability to describe the abstract behavior of components using a CSP-like notation, the characterization of styles using predicates over system instances, and a collection of static checks to determine the consistency and completeness of an architectural specification. We introduce techniques to support the analysis of large-scale systems, and demonstrate Wright's expressiveness and practicality through three case studies.
For further information, please visit the home pages of the ABLE research project and Carnegie Mellon University's Composable Systems Group.
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