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n e bene$ts of evaluating properties of software architectures stem from hvo important software architecture roles: (1) providing an opportunity to evaluate requirements and correct defects prior to implementation and (2) serving as a blueprint for system developers. Tliis paper focuses on a new software architecture evaluation tool called Architecture Analysis Dynamic Environment (Arcade) that uses model checking to provide software architecture safety and liveness evaluation during the requirements gathering and analysis phase. Model checking requires expertise not typically held by systems analysts and software developers. Thus, two barriers to applying model checking must be addressed: (1) translation of the software architecture specification to a form suitable for model checking, and (2) interpretation of the results of model checking. Arcade provides an automated approach to these barriers, allowing model checking of sofware architectures to be added to the list of techniques available to software analysts and developers focusing on requirements gathering and analysis.,

Sofrware architectures have received considerable attention in both research and practice for representing system stakeholder concerns, and many researchers have leveraged objectoriented models and methods for sofiare architecture representation and evaluation. While the benefits associated with object-oriented approaches are closely aligned with desirable qualities for sofrware architectures (e.g., reusability, extensibility, comprehensibility, performance), these beneJits are only realized through rational decision-making by the analyst when identihing object-oriented classes from a requirements specification. Traditionally, the class identification process has been somewhat subjective, with dvferent analysts often arriving at completely different class models from the same requirements specijkation. Since this subjectivity does not lend itself to automation, little tool support is available for identgfying object-oriented classes and their relationships. This paper describes a tool under development, Reference Architecture Representation Environment (RARE,), designed to systematically guide the analyst through class identification by applying heuristics associated with quality attributes and evaluating the resulting architecture based on relevant static metrics. RARE helps address a number of challenges typically faced during the class identification process, including (I) developing an architecture that reflects the quality attributes prioritized by the analyst, (2) managing inherent conflicts between selected attributes, and (3) capturing analyst expertise and rationale for use by others.

This paper presents the requirements gathering and software architecture derivation approach developed by the Universio of Texas at Austin and leveraged by the National Cancer Institute (NCl) in their efsorts to automate the creation, nlanagement, and evaluation of clinical trials. NCI must face the complexity of managing clinical trials and coordinating large numbers and varied types of stakeholders. The Systems Engineering Process Activities (SEPA) from the University of Texas at Austin is well suited to address domain modeling and software developnient at NCl due to a strong emphasis on explicit traceability from a derived architecture to individual Knowledge Acquisition (KA) sessions as well as facilitated resolution among conflicting stakeholder contributions. Specifically, this paper focuses on the SEPA Domain Reference Architecture (DRA), a software architecture designed to capture domain requirements (i.e., domain data, functionality, and timing).

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