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NLP based verification of a UML class model

机译:基于NLP的UML类模型验证

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摘要

Robotized model time is a creating examination field. A significant number of representations are furthermore given where model checking has been associated for affirmation of various sorts of model. Such delineations are SAT based checks of UML/OCL models, embeded structures model affirmation, et cetera. In all these kind of employments, the complement is model checking. In later past, UML programming models are created from programming necessities conveyed in a trademark tongue, for instance, English by using NLP technique. Regardless, the diverse sorts of UML models delivered from consistent vernacular programming requirements specific using NLP approach have no technique for check as in the complete and correct models are done. It is a normal learning NLP techniques have been viably associated with make UML models as delineated above, in any case, in this paper, we address the issue of model checking and model affirmation by using NLP strategies. Such sort of changes require package of effort and time that makes the system of model affirmation wild and ambling. We used an approach for model watching that makes the technique of model checking straightforward and additionally the used philosophy should use the present resources used for generation of the UML class model.
机译:机器人模型时间是一个正在创建的检查领域。此外,给出了大量的表示,其中与模型检查相关联以确认各种模型。这样的描述是基于SAT的UML / OCL模型检查,嵌入式结构模型确认等等。在所有这些类型的工作中,补充是模型检查。在过去,UML编程模型是通过使用NLP技术从以商标语言(例如英语)传达的编程必需性中创建的。无论如何,从使用NLP方法特定的一致的本地语言编程要求中交付的各种UML模型都没有检查技术,因为已经完成了完整而正确的模型。这是一种正常的学习NLP技术,已经与上述的UML模型建立了有效的联系,无论如何,在本文中,我们都使用NLP策略解决了模型检查和模型确定的问题。这种变化需要花费大量的精力和时间,这使得模型确认系统变得狂野而繁琐。我们使用了一种用于模型观察的方法,该方法使模型检查的技术变得简单明了,此外,所使用的原理还应使用用于生成UML类模型的当前资源。

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