Browsing by Author "Pati, Tanumoy"

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    Auto-Generating Models From Their Semantics and Constraints
    (2013-08-20) Pati, Tanumoy; Hill, James H. (James Haswell); Raje, Rajeev; Al Hasan, Mohammad
    Domain-specific models powered using domain-specific modeling languages are traditionally created manually by modelers. There exist model intelligence techniques, such as constraint solvers and model guidance, which alleviate challenges associated with manually creating models, however parts of the modeling process are still manual. Moreover, state-of-the-art model intelligence techniques are---in essence---reactive (i.e., invoked by the modeler). This thesis therefore provides two contributions to model-driven engineering research using domain-specific modeling language (DSML). First, it discusses how DSML semantic and constraint can enable proactive modeling, which is a form of model intelligence that foresees model transformations, automatically executes these model transformations, and prompts the modeler for assistance when necessary. Secondly, this thesis shows how we integrated proactive modeling into the Generic Modeling environment (GME). Our experience using proactive modeling shows that it can reduce modeling effort by both automatically generating required model elements, and by guiding modelers to select what actions should be executed on the model.
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    AUTO-GENERATING MODELS FROM THEIR SEMANTICS AND CONSTRAINTS
    (Office of the Vice Chancellor for Research, 2012-04-13) Pati, Tanumoy; Hill, James H.
    Model-Driven Engineering (MDE) facilitates building solutions in many en-terprise application domains through the systematic use of graphical lan-guages called domain-specific modeling languages (DSMLs). MDE tools, such as the Generic Modeling Environment (GME) and the Generic Eclipse Modeling System (GEMS), enable end-users to rapidly create such custom DSMLs. When DSMLs are coupled with constraint solvers, it is possible for DSML end-users to auto-generate solutions (i.e., models) based on the goals of the constraint solver (e.g., finding the optimal deployment for a set of software components given resource availability and resource needs). One requirement of using a constraint solver with a DSML, however, is that mod-elers have to create an initial model, also known as a “partial model”. This implies that it is the end-users responsibility to (1) understand how to use the DSML and (2) understand when they have created an appropriate partial model that is a candidate for completion using a constraint solver. Our research therefore focuses on addressing the two problems men-tioned above. We address the problems by analyzing the semantics and con-straints of the DSML (i.e., the meta-model). Based on our analysis, we then auto-generate as much of the model until we reach a point that requires us-er intervention. At that point, we present a set of operations (or moves) to the user and continue the process until the model is complete, or is solvable using a constraint solver.