Ambient software engineering

在过去的几十年里，软件工程过程已经从其工业根源发展到包括新的社会和协作方面，例如使用Web 2.0等新技术的配对编程和共享虚拟编程（例如，社区、博客、服务和wiki）。相关软件工件（例如工作产品和文档）及其正式和非正式记录的保存至关重要。这些工件反映了组织和软件社区所做的重大投资，捕获（领域）知识和专业知识，这对确保软件系统的可演化性和质量至关重要。与此同时，应用于软件仓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大量信息。然而，由于项目团队和软件系统的不断变化，现有的项目知识和专业知识往往不再完整，一致或可追溯到其起源，导致可以被视为信息孤岛的单独存储库。在拟议的研究中，我们专注于捕捉，集成和分析这些大型的，往往是高度分布的知识孤岛的需要。本研究的主要目标是创建一个周围的软件工程环境，促进共同的知识表示，允许跨边界的单个知识资源的语义分析，以支持这些现有的知识资源之间的可追溯性链接的重新建立。该研究将解决几个重要问题：（1）（Meta）模型的发展，以支持集成，可追溯性和重用之间已经存在的知识资源;（2）开发一个软件工程环境，使管理、探索和推理能够跨越知识和资源边界，通过上下文指导支持软件演化活动，语义分析、质量评估和过程改进;（3）通过度量、用户反馈和案例研究评估方法的影响和功效。

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.