III: Small: Making and Tracing: Architecture-centric Information Integration

III：小：制作与追踪：以架构为中心的信息集成

• 批准号: 0917129
• 负责人: Richard Taylor
• 金额: $ 49.96万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917129&HistoricalAwards=false
• 关键词: III; Small; Making; Tracing; Architecture

In many scientific domains information is scattered across numerous interrelated and heterogeneous artifacts. In software engineering in particular, artifacts such as requirements, design documents, and code are often isolated by tools, development groups, and geographic locations. Current traceability approaches ? attempts to link related information ? fall short in tracing across heterogeneous artifacts and in supporting user-customized links. This project is aimed at crossing these information barriers, enabling the creation of traceability links between related artifacts, to support tasks such as impact analysis and software maintenance.This project targets automated architecture-centric traceability which centers links on the architecture, enabling scalable and flexible link capture. Furthermore, stakeholders control link capture, enabling them to directly benefit from the links. The prevalent approach to automatic traceability is to recover links from existing artifacts. In contrast, this project pursues prospective generation of trace links which captures links in situ, while artifacts are generated or modified, enabling the capture of contextual relationships. Open hypermedia adapters enable the capture of links across heterogeneous artifacts and the rendering of resources at different levels of granularity. Users can determine the artifacts to trace and the link semantics to assign via externally customizable rules.The approach is applicable to data provenance capture in e-Science. Prospective capture can aid in inferring experiment design and capturing links across heterogeneous artifacts like publications, data files, and plots. The results will also be valuable to the development of safety critical systems where satisfaction of all requirements is part of safety assurance.

在许多科学领域中，信息分散在许多相互关联和异质的人工制品中。特别是在软件工程中，需求、设计文档和代码等工件通常被工具、开发小组和地理位置隔离。当前的可追溯性方法？尝试链接相关信息？在跨异构工件的跟踪和支持用户自定义链接方面存在不足。该项目旨在跨越这些信息障碍，在相关工件之间创建可追溯性链接，以支持影响分析和软件维护等任务。该项目的目标是以架构为中心的自动化可追溯性，以架构为中心的链接，实现可扩展和灵活的链接捕获。此外，利益相关者控制链接捕获，使他们能够直接从链接中受益。自动跟踪的流行方法是从现有工件中恢复链接。 相比之下，这个项目追求的是跟踪链接的预期生成，它在原地捕获链接，而工件被生成或修改，从而能够捕获上下文关系。开放的超媒体适配器能够捕获跨异构工件的链接，并以不同的粒度级别呈现资源。用户可以通过外部定制的规则来确定要跟踪的工件和要分配的链接语义，该方法适用于e-Science中的数据来源捕获。 前瞻性捕获可以帮助推断实验设计和捕获跨异构工件（如出版物、数据文件和图）的链接。结果也将是有价值的安全关键系统的发展，满足所有要求的安全保证的一部分。