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Issues pertaining to separation of concerns have been the primary nexus between software engineering and programming language research. Several techniques for advanced separation of concerns have been proposed within the area of Aspect-Oriented Software Development (AOSD). These techniques have focused on the modularization of non-orthogonal concerns that exhibit crosscutting behavior. This dissertation is about advanced separation of concerns at the modeling level, and the construction of support tools that facilitate the elevation of crosscutting modeling concerns to first-class citizens.
A key objective of the research described in this dissertation is the application of Aspect-Oriented (AO) concepts at a higher level of abstraction. The principles of modularity espoused by AO offer a powerful technology for supporting the separation of crosscutting concerns in domain-specific modeling. Although there have been other efforts that explore AO at the design and analysis level, the work described in this dissertation represents one of the earliest occurrences in the literature of an actual aspect-oriented weaver that is focused on modeling issues, rather than topics that are applicable to traditional programming languages.
Another objective of the research presented in this dissertation pertains to the creation of new weavers using a metaweaver framework. Because the syntax and semantics of each modeling domain are unique, a different weaver is needed for each domain. A metaweaver framework has been created as an aid toward the construction of new domain-specific weavers. This framework utilizes several code generators that take metalevel specifications, described in a Domain-Specific Language (DSL), as input. The generators produce code that serves as a hook into the framework.
These two objectives provide a contribution toward the synergy of AOSD and Model-Integrated Computing (MIC). This union assists a modeler in capturing concerns that, heretofore, were very difficult, if not impossible, to modularize. A key benefit is the ability to explore numerous scenarios by considering crosscutting modeling concerns as aspects that can be rapidly inserted and removed from a model.