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Advanced and efficient execution trace management for executable domain-specific modeling languages

机译:针对可执行域特定建模语言的高级高效执行跟踪管理

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Executable Domain-Specific Modeling Languages (xDSMLs) enable the application of early dynamic verification and validation (V&V) techniques for behavioral models. At the core of such techniques, execution traces are used to represent the evolution of models during their execution. In order to construct execution traces for any xDSML, generic trace metamodels can be used. Yet, regarding trace manipulations, generic trace metamodels lack efficiency in time because of their sequential structure, efficiency in memory because they capture superfluous data, and usability because of their conceptual gap with the considered xDSML. Our contribution is a novel generative approach that defines a multidimensional and domain-specific trace metamodel enabling the construction and manipulation of execution traces for models conforming to a given xDSML. Efficiency in time is improved by providing a variety of navigation paths within traces, while usability and memory are improved by narrowing the scope of trace metamodels to fit the considered xDSML. We evaluated our approach by generating a trace metamodel for fUML and using it for semantic differencing, which is an important V&V technique in the realm of model evolution. Results show a significant performance improvement and simplification of the semantic differencing rules as compared to the usage of a generic trace metamodel.
机译:可执行的特定于域的建模语言(xDSML)支持将早期动态验证和确认(V&V)技术应用于行为模型。这种技术的核心是执行跟踪,用于表示模型在执行过程中的演变。为了构造任何xDSML的执行跟踪,可以使用通用跟踪元模型。但是,关于跟踪操作,通用跟踪元模型由于其顺序结构而在时间上缺乏效率,由于捕获了多余的数据而在内存中没有效率,并且由于与所考虑的xDSML的概念差距而缺乏可用性。我们的贡献是一种新颖的生成方法,该方法定义了多维且特定于域的跟踪元模型,从而能够构建和操纵符合给定xDSML的模型的执行跟踪。通过在跟踪中提供各种导航路径来提高时间效率,同时通过缩小跟踪元模型的范围以适合所考虑的xDSML来提高可用性和内存。我们通过为fUML生成跟踪元模型并将其用于语义区分来评估我们的方法,这是模型演化领域中的重要V&V技术。结果表明,与使用通用跟踪元模型相比,语义差异规则具有显着的性能改进和简化。

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