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Rugaber, Spencer

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    Automating UI Generation by Model Composition
    (Georgia Institute of Technology, 1998) Stirewalt, R. E. Kurt ; Rugaber, Spencer
    Automated user-interface generation environments have been criticized for their failure to deliver rich and powerful interactive applications. To specify more powerful systems, designers need multiple, specialized modeling notations. The model composition problem is concerned with automatically deriving powerful, correct, and efficient user interfaces from multiple models specified in different notations. Solutions balance the advantages of separating code generation into specialized code generators with deep, model-specific knowledge against the correctness and efficiency obstacles that result from such separation. We present a solution that maximizes the advantages of separating code generation. In our approach, highly specialized, model-specific code generators synthesize run-time modules from individual models. We address the correctness and efficiency obstacles by formalizing composition mechanisms that code generators may assume and that are guaranteed by a run-time infrastructure. The mechanisms operate to support run-time module composition as conjunctions in the sense defined by Zave and Jackson.
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    Automating the Design of Specification Interpreters
    (Georgia Institute of Technology, 1996) Stirewalt, R. E. Kurt ; Rugaber, Spencer ; Abowd, Gregory D.
    In this paper, we demonstrate the use of model checking in an automated technique to verify the operationalization of a declarative specification language. We refer to an interpreter synthesizer as a software tool that transforms a declarative specification into an executable interpreter. Iterative approaches to synthesizer generation refine initial synthesizer designs by validating them over a test suite of specifications. Carefully chosen test suites and structural constraints enable inductive reasoning with support from a model checker to assert the correctness of generated interpreters. This iterative approach to synthesizer generation occurred naturally in our work on developing interpreters for declarative human-computer dialogue languages as part of the DARPA MASTERMIND project. We will discuss the issues underlying the translation, operationalization and verification of the hierarchical task language for MASTERMIND. We will also discuss the importance of this semi-automated, iterative approach for assessing non-functional design tradeoffs.
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    The MASTERMIND User Interface Generation Project
    (Georgia Institute of Technology, 1996) Browne, Thomas ; Davila, David ; Rugaber, Spencer ; Stirewalt, R. E. Kurt
    Graphical user interfaces are difficult to construct and, consequently, suffer from high development and maintenance costs. Automatic generation from declarative descriptions can reduce costs and enforce design principles. MASTERMIND is a model based approach to user interface generation. Designers model different aspects of an interface using declarative modeling languages, and tools synthesize these models into run-time code. The design process begins with user task and application modeling. These models are then refined into dialogue, presentation, and interaction models and an application API. These latter models drive the synthesis of run-time code. A design tool called Dukas is employed to support the refinement of task models into dialogue models.