Ambient Software Engineering –Moving Towards A Software Engineering Web of Things

在过去的二十年里，互联网已经从一个面向终端用户的全球(只读)信息中心发展到其目前的形式(Web 2.0)，它支持终端用户创建内容(例如，博客、社交网络)。然而，即使在目前的发展阶段，Web 2.0也只是朝着互联网可能成为的最初愿景迈出了一步--物联网也被称为Web 3.0。Web 3.0将建立在几项关键技术(例如，语义网、自动标记、推理和语义链接)的基础上，机器与其他机器对话来处理大部分日常工作，让人类在全球范围内提供灵感和直觉。虽然许多领域(例如，汽车、制造、家庭自动化)已经开始使Web 3.0成为其未来解决方案空间的重要和集成部分，但软件工程社区还没有接受这一举措。该研究项目的目标是引入环境软件工程作为一种跨学科的方法，将传统的软件工程(进化)研究与语义网、自然语言处理、知识建模和挖掘软件库等领域的最新研究相结合。该方法利用了成熟的语义网技术，支持使用本体和现有异质知识资源的关联数据进行标准化、统一和形式化的知识表示。 拟议的研究将侧重于引入信息中心，使用本体和关联数据表示法对从现有软件资源中提取的事实和知识进行正式建模。此外，还将研究使用自动标记、机器学习、源代码分析和语义网推理，以进一步丰富这些信息中心，使其具有语义信息和语义可追溯性链接--这两者都是建立软件工程物联网的基本前提。为进行评估，将为软件演进领域引入一套初始的智能工作流程和服务，以支持跨软件工程领域提取的全球异质知识的复合应用程序或任务上下文。 正在开发的数据集和智能服务将通过在线门户公开提供，以创建软件工程领域的物联网的初始版本，其中信息中心取代软件领域中的传统信息孤岛。这些信息中心(物联网)将促进知识共享、重用和集成，方法是促进让广大软件社区参与的众包工作，以共享和链接他们自己的数据(事实和分析结果)和智能服务，以继续发展软件工程领域的物联网。

The Internet has evolved over the last two decades from a global (read only) information hub for end-users, to its current form (Web 2.0) with its end-user support for content creation (e.g., blogging, social networking). However, even in its current development stage, Web 2.0 is only a step towards the original vision of what the Internet might become – a Web of Things also known as Web 3.0. Web 3.0 will be built upon several key technologies (e.g., Semantic Web, automated tagging, reasoning and semantic linking), with machines talking to other machines to deal with much of the daily routine work, leaving humans to provide the inspiration and intuition all in a global context. While many domains (e.g., automotive, manufacturing, home automation) have started to make the Web 3.0 an important and integrated part of their future solution space, the software engineering community has yet to embrace this move. The objective of this research program is to introduce Ambient Software Engineering as a cross disciplinary approach, integrating traditional software engineering (evolution) research, with state-of-the art research from domains such as Semantic Web, Natural Language Processing, knowledge modeling and Mining Software Repositories. The approach takes advantage of matured Semantic Web technologies, which support a standardized unified and formal knowledge representation using ontologies and Linked Data of existing heterogeneous knowledge resources. The proposed research will focus on the introduction of information hubs, with facts and knowledge extracted from existing software resources being formally modeled using ontologies and Linked Data representations. In addition the use of automated tagging, machine learning, source code analysis and Semantic Web reasoning will be investigate to further enrich these information hubs with semantic information and semantic traceability links - both being an essential prerequisite for establishing a Software Engineering Web of Things. For the evaluation an initial set of smart workflows and services for the software evolution domain will be introduced that allow for the support of composite applications or task contexts across global heterogeneous knowledge extracted from the software engineering domain. Both, the datasets and smart services being developed, will be publicly available through an online portal, to create an initial version of a Web of Things for the software engineering domain, where information hubs replace traditional information silos found in the software domain. These information hubs (things) will promote knowledge sharing, reuse and integration, by facilitating a crowd-sourcing effort involving the software community at large to share and link their own data (facts and analysis results) and smart services to continue evolving this Web of Things for the software engineering domain.