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Composing Models for Detecting Inconsistencies: A Requirements Engineering Perspective

机译:构图检测不一致的模型:需求工程视角

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[Context and motivation] Ever-growing systems' complexity and novel requirements engineering approaches such as reuse or globalization imply that requirements are produced by different stakeholders and written in possibly different languages. [Question/problem] In this context, checking consistency so that requirements specifications are amenable to formal analysis is a challenge. Current techniques either fail to consider the requirement set as a whole, missing certain inconsistency types or are unable to take heterogeneous (i.e. expressed in different languages) specifications into account. [Principal ideas/results] We propose to use model composition to address this problem in a staged approach. First, heterogeneous requirements are translated in model fragments which are instances of a common metamodel. Then, these fragments are merged in one unique model. On such a model inconsistencies such as under-specifications can be incrementally detected and formal analysis is made possible. Our approach is fully supported by our model composition framework. [Contribution] We propose model composition as means to address flexibility needs in requirements integration. Threats to validity such as the impact of new requirements languages needs to be addressed in future work.
机译:[背景和动机]越来越多的系统的复杂性和新的需求工程方法,如重用或全球化,意味着要求由不同的利益相关者产生并以可能不同的语言编写。 [问题/问题]在这种情况下,检查一致性,以便要求规范适用于正式分析是一项挑战。当前技术无法考虑整个要求设置的要求,缺少某些不一致类型或无法考虑异质(即以不同语言表达)规格。 [主要思想/结果]我们建议使用模型组成来以分阶段的方法解决这个问题。首先,异构要求在模型片段中翻译,这些片段是普通元模型的实例。然后,这些片段在一个唯一的模型中合并。在这种模型中,例如规范之类的不一致可以逐步检测,并且可以进行正式分析。我们的方法完全由我们的模型组成框架提供支持。 [贡献]我们将模型组成作为解决需求集成中的灵活性需求的手段。需要在将来的工作中解决对新要求语言的影响等有效性的威胁。

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