Constraint validation support in visual model transformation systems

Model-Driven Architecture (MDA) standardized by OMG facilitates to separate the platform independent part and the platform specific part of a system model. Due to this separation Platform-Independent Model (PIM) can be reused across several implementation platforms of the system. Platform-Specific Model (PSM) is ideally generated automatically from PIM via model transformation steps. Because of the appearance of high level languages, object-oriented technologies and CASE tools, metamodeling becomes more and more important. Metamodeling is one of the most central techniques both in design of visual languages, and reuse existing domains by extending the metamodel level. The creation of model compliers on a metamodeling basis is illustrated by a software package called Visual Modeling and Transformation System (VMTS), which is an n-layer multipurpose modeling and metamodel-based transformation system. VMTS is able to realize an MDA model compiler. This paper (i) addresses the relationship between the constraints enlisted in metamodel-based rewriting rules and the pre- and postconditions, (ii) it introduces the concepts of general validation, general preservation and general guarantee, which facilitate that if a transformation step is specified adequately with the help of constraints, and the step has been executed successfully for the input model, then the generated output model is in accordance with the expected result, which is described by the transformation step refined with the constraints. An illustrative case study based on constraint specification in rewriting rules is also provided

Sensitivity analysis of expensive black-box systems using metamodeling

Simulations are becoming ever more common as a tool for designing complex products. Sensitivity analysis techniques can be applied to these simulations to gain insight, or to reduce the complexity of the problem at hand. However, these simulators are often expensive to evaluate and sensitivity analysis typically requires a large amount of evaluations. Metamodeling has been successfully applied in the past to reduce the amount of required evaluations for design tasks such as optimization and design space exploration. In this paper, we propose a novel sensitivity analysis algorithm for variance and derivative based indices using sequential sampling and metamodeling. Several stopping criteria are proposed and investigated to keep the total number of evaluations minimal. The results show that both variance and derivative based techniques can be accurately computed with a minimal amount of evaluations using fast metamodels and FLOLA-Voronoi or density sequential sampling algorithms.Comment: proceedings of winter simulation conference 201

Screening and metamodeling of computer experiments with functional outputs. Application to thermal-hydraulic computations

To perform uncertainty, sensitivity or optimization analysis on scalar variables calculated by a cpu time expensive computer code, a widely accepted methodology consists in first identifying the most influential uncertain inputs (by screening techniques), and then in replacing the cpu time expensive model by a cpu inexpensive mathematical function, called a metamodel. This paper extends this methodology to the functional output case, for instance when the model output variables are curves. The screening approach is based on the analysis of variance and principal component analysis of output curves. The functional metamodeling consists in a curve classification step, a dimension reduction step, then a classical metamodeling step. An industrial nuclear reactor application (dealing with uncertainties in the pressurized thermal shock analysis) illustrates all these steps

A Language Description is More than a Metamodel

Within the context of (software) language engineering, language descriptions are considered first class citizens. One of the ways to describe languages is by means of a metamodel, which represents the abstract syntax of the language. Unfortunately, in this process many language engineers forget the fact that a language also needs a concrete syntax and a semantics. In this paper I argue that neither of these can be discarded from a language description. In a good language description the abstract syntax is the central element, which functions as pivot between concrete syntax and semantics. Furthermore, both concrete syntax and semantics should be described in a well-defined formalism

Metamodel variability analysis combining bootstrapping and validation techniques

Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of the EOQ model show encouraging results