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Semantic Integration of Software and Systems Engineering Environments

机译:软件和系统工程环境的语义集成

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Software-intensive systems in business information technology (IT) and industrial automation have become increasingly complex due to the need for more flexible system reconfiguration and business and engineering processes. Systems and software-engineering projects depend on the cooperation of experts from heterogeneous engineering domains using tools that were not designed to cooperate seamlessly. Current semantic-engineering-environment integration is often ad hoc and fragile, thereby making the evolution of tools and the reuse of integration solutions across projects unnecessarily inefficient and risky. This paper describes the engineering-knowledge-base (EKB) framework for engineering-environment integration in multidisciplinary engineering projects. The EKB stores explicit engineering knowledge to support access to and management of engineering models across tools and disciplines by providing 1) data integration based on mappings between local and domain-level engineering concepts; 2) transformations between local engineering concepts; and 3) advanced applications built on these foundations, e.g., end-to-end analyses. As a result, experts from different organizations may use their well-known tools and data models and can access data from other tools in their syntax. The research results have been evaluated in the industrial-application domain of software-intensive production-automation systems. The evaluation results indicate an effort-reduction for reuse in new engineering projects and finding defects earlier in the engineering process.
机译:由于需要更灵活的系统重新配置以及业务和工程流程,因此业务信息技术(IT)和工业自动化中的软件密集型系统变得越来越复杂。系统和软件工程项目依赖于来自异类工程领域的专家的合作,他们使用的工具并非旨在无缝协作。当前的语义工程环境集成通常是临时性的且脆弱的,从而使得工具的演进以及跨项目的集成解决方案的重用不必要地效率低下且具有风险。本文介绍了用于多学科工程项目中工程环境集成的工程知识基础(EKB)框架。 EKB存储明确的工程知识,以通过提供以下功能来支持跨工具和学科的工程模型的访问和管理:1)基于本地和领域级工程概念之间的映射的数据集成; 2)本地工程概念之间的转换;和3)在这些基础上构建的高级应用程序,例如端到端分析。结果,来自不同组织的专家可能会使用其知名的工具和数据模型,并可以使用其语法访问其他工具中的数据。研究结果已经在软件密集型生产自动化系统的工业应用领域中进行了评估。评估结果表明,减少了在新工程项目中重复使用的工作量,并在工程过程的早期发现了缺陷。

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