EAGER: Bringing Design Thinking into Developers' Coding Activities through an Architectural Tactic Recommender System

EAGER：通过架构策略推荐系统将设计思维引入开发人员的编码活动

• 批准号: 1543176
• 负责人: Mehdi Mirakhorli
• 金额: $ 8万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1543176&HistoricalAwards=false
• 关键词: EAGER; Bringing; Design; Thinking; into

The success of any complex software-intensive system is highly dependent on the extent to which it addresses stakeholders' quality concerns such as reliability, availability, security and performance. Software architects utilize a rich set of proven and re-usable architectural solutions such as tactics and patterns to satisfy each specific quality attribute. The objective of this research project is to develop a novel tactic-recommender system that is trained through learning from the source code of thousands of open-source software systems. The project will include developing a set of novel big-data compatible architecture profilers that ?detect? and ?learn? architectural choices made by several developers across source codes of thousands of open-source systems. This knowledge is used to recommend architectural tactics fitting a new project. This represents a paradigm shift in utilizing automated techniques to bring design thinking into developers? daily coding activities. Unlike existing architecture design practices, which all involve a rigorous upfront analysis of the system's quality concerns, this research takes a bottom-up approach. It uses the latent domain topics in the source code and identifies not only architectural tactics/patterns missing in a given project but also recommends several high quality sample implementations of the tactics/patterns from open source software projects. The findings of this research will partially address the current gap between design and implementation. The broader impact of the work will be to improve the productivity of software development and to improve the quality and evolvability of software-intensive systems.

任何复杂的软件密集型系统的成功都在很大程度上取决于它解决利益相关者质量问题（例如可靠性，可用性，安全性和性能）的程度。软件架构师利用了一套丰富的经过验证和可重复使用的架构解决方案，例如策略和模式，以满足每个特定质量属性。 该研究项目的目的是开发一种新颖的战术征询者系统，该系统通过从数千个开源软件系统的源代码中学习而受到培训。该项目将包括开发一组新型的大数据兼容的建筑探查师？和？学习？数千个开源系统跨源代码中的几个开发人员做出的建筑选择。这些知识用于推荐适合新项目的建筑策略。 这代表了利用自动化技术将设计思维带入开发人员的范式转变？每日编码活动。 与现有的体系结构设计实践不同，这些实践都涉及对系统质量问题进行严格的前期分析，这项研究采用了自下而上的方法。它使用源代码中的潜在领域主题，不仅标识给定项目中缺少的建筑策略/模式，而且还建议从开源软件项目中对策略/模式进行几种高质量的示例实现。 这项研究的发现将部分解决设计和实施之间的当前差距。这项工作的广泛影响是提高软件开发的生产率，并提高软件密集型系统的质量和发展性。