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Semantics guided filtering of combinatorial graph transformations in declarative equation-based languages

机译:基于声明式方程式语言的组合图变换的语义指导过滤

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摘要

This paper concerns the use of static analysis for debugging purposes of declarative object-oriented equation-based modeling languages. We propose a framework where over- and under-constraining situations present in simulation models specified in such languages are detected by combinatorial graph transformations performed on the flattened intermediate code and filtered by the semantic transformation rules derived from the original language. This is powerful enough to statically detect a broad range of errors without having to execute the simulation model. Debuggers associated with simulation environments for such languages can provide efficient error-fixing strategies based on the graph-based representation of the intermediate code. The emphasis, in this paper, is on detecting and debugging over-constraining equations, which are present in some simulation model specifications. We discuss various ways in which we have extended our approach to allow static global analysis of the original modeling source code.
机译:本文涉及将静态分析用于基于声明的面向对象的基于方程的建模语言的调试目的。我们提出了一个框架,其中通过对扁平化中间代码执行的组合图转换来检测以这种语言指定的仿真模型中存在过度约束和不足约束的情况,并通过从原始语言派生的语义转换规则对其进行过滤。它具有强大的功能,可以在不执行仿真模型的情况下静态检测各种错误。与此类语言的仿真环境关联的调试器可以基于中间代码的基于图的表示形式,提供有效的错误修复策略。本文的重点是检测和调试一些模型模型规范中存在的过约束方程。我们讨论了各种扩展方法的方式,以允许对原始建模源代码进行静态全局分析。

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