Attribute grammar specification languages, like many domain-specific languages, offer significant advantages to their users, such as high-level declarative constructs and domain-specific analyses. Despite these advantages, attribute grammars are often not adopted to the degree that their proponents envision. One practical obstacle to their adoption is a perceived lack of both domain-specific and general purpose language features needed to address the many different aspects of a problem. Here we describe Silver, an extensible attribute grammar specification system, and show how it can be extended with general purpose features such as pattern matching and domain-specific features such as collection attributes and constructs for supporting data-flow analysis of imperative programs. The result is an attribute grammar specification language with a rich set of language features. Silver is implemented in itself by a Silver attribute grammar and utilizes forwarding to implement the extensions in a cost-effective manner.

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In model-based development, a formal description of the software (the model) is the central artifact that drives other development activities. The availability of a modeling language well-suited for the system under development and appropriate tool support are of utmost importance to practitioners. Considering the diverse needs of different application domains, flexibility in the choice of modeling languages and tools may advance the industrial acceptance of formal methods. We describe a flexible modeling language framework by which language and tool developers may better meet the special needs of various users groups without incurring prohibitive costs. The framework is based on a modular and extensible implementation of languages features using attribute grammars and forwarding. We show a prototype implementation of such a framework by extending the host language Mini-Lustre, an example synchronous data-flow language, with a collection of features such as state transitions, condition tables, and events. We also show how new languages can be created in this framework by feature composition.

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