Ambient software engineering

在过去的几十年里，软件工程过程已经从它们的工业根源发展到包括新的社交和协作方面，例如结对编程和使用Web2.0等新技术(例如，社区、博客、服务和Wiki)共享虚拟工作空间。保存相关的软件产品(例如，工作产品和文档)及其正式和非正式记录至关重要。这些构件反映了组织和软件社区进行的重大投资，获取了(领域)知识和专业知识，这些知识和专业知识对于确保软件系统的可进化性和质量至关重要。与此同时，应用于软件库的挖掘技术已经成熟，现在能够提供从现有软件项目中收集的丰富信息。然而，由于对项目团队和软件系统的不断更改，现有的项目知识和专业知识通常不再完整、一致或可追溯到其起源，导致可以被视为信息孤岛的单个存储库。在拟议的研究中，我们重点关注捕获、集成和分析这些大型且往往高度分布的知识孤岛的需求。这项研究的主要目标是创建一个环境软件工程环境，该环境有助于公共知识表示，以允许跨单个知识资源的边界进行语义分析，以便支持在这些现有知识资源之间重新建立可追溯性链接。拟议的研究将解决几个重要问题：(1)开发(元)模型，以支持现有知识资源之间的集成、可跟踪性和重用；(2)开发环境软件工程环境，该环境将使跨知识和资源边界的管理、探索和推理能够通过上下文指导、语义分析、质量评估和过程改进来支持软件演化活动；以及(3)通过度量、用户反馈和案例研究来评估方法的影响和有效性。

Over the last decades, software engineering processes have evolved from their industrial roots to include new social and collaborative aspects such as pair-programming and shared virtual workspaces using new technologies such as Web 2.0 (e.g., communities, blogs, services, and wikis). Preservation of relevant software artifacts (e.g. work products and documentation) and their formal and informal records is of critical importance. These artifacts reflect a significant investment made by organization and software communities, capturing (domain) knowledge and expertise that is essential to ensure the evolvability and quality of software systems. At the same time, mining techniques applied on software repositories have matured and are now capable of providing a wealth of information collected from existing software projects. However, due to constant changes made to project teams and software systems, existing project knowledge and expertise is often no longer complete, consistent, or traceable to its origins, resulting in individual repositories that can be considered information silos. In the proposed research, we focus on the need to capture, integrate, and analyze these large and often highly distributed knowledge silos. The primary goal of this research is to create an ambient software engineering environment that facilitates a common knowledge representation to allow a semantic analysis across the boundaries of individual knowledge resources in order to support the re-establishing of traceability links among these existing knowledge resources. The proposed research will address several important issues: (1) the development of (meta-) models in order to support integration, traceability, and reuse among already existing knowledge resources; (2) the development of an ambient software engineering environment that will enable the management, exploration, and reasoning across knowledge and resources boundaries to support software evolution activities through contextual guidance, semantic analysis, quality assessments, and process improvement; and (3) the evaluation of the impact and efficacy of the approach through, metrics, user feedback and case studies.