首页> 外文会议>System analysis and modeling: About models >Extensible and Automated Mo del-Evaluations with INProVE
【24h】

Extensible and Automated Mo del-Evaluations with INProVE

机译:利用IMProVE进行可扩展的自动化模型评估

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Model-based development is gaining more and more importance for the creation of software-intensive embedded systems. One important aspect of software models is model quality. This does not imply functional correctness, but non-functional properties, such as maintainability, scalability, extensibility. Lots of effort was put into development of metrics for control flow models. In the embedded systems domain however, domain specific- and data flow languages are commonly applied for model creation. For these languages, existing metrics are not applicable. Domain and project specific quality metrics therefore are informally defined; tracking conformance to these metrics is a manual and effort consuming task. To resolve this situation, we developed INProVE. INProVE is a model-based framework that supports definition of quality metrics in an intuitive, yet formal notion. It provides automated evaluation of design models through its indicators. Applied in different industry projects to complex models, INProVE has proven its applicability for quality assessment of data flow-oriented design models not only in research, but also in practice.
机译:基于模型的开发对于创建软件密集型嵌入式系统越来越重要。软件模型的一个重要方面是模型质量。这并不意味着功能正确性,而是暗示非功能属性,例如可维护性,可伸缩性,可扩展性。为控制流模型的度量开发投入了大量精力。然而,在嵌入式系统领域,领域特定语言和数据流语言通常用于模型创建。对于这些语言,现有指标不适用。因此,对领域和项目的特定质量指标进行了非正式定义;跟踪这些指标的符合性是一项手动且费力的任务。为了解决这种情况,我们开发了INProVE。 INProVE是一个基于模型的框架,以直观但正式的概念支持质量指标的定义。它通过指标提供对设计模型的自动评估。 INProVE应用于不同行业项目中的复杂模型,已证明其不仅在研究中而且在实践中都可用于面向数据流的设计模型的质量评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号