Model-Driven Engineering of Integrated Digital Infrastructures

集成数字基础设施的模型驱动工程

• 批准号: RGPIN-2014-06183
• 负责人: Stroulia, Eleni
• 金额: $ 3.35万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=612078
• 关键词: Model; Driven; Engineering; Integrated; Digital

The proposed research program aims to make contributions to the theory and practice of developing complex ecosystems of software components to support teams of individuals engaged in knowledge-based work. All knowledge-based work today across disciplines involves working with software, using sensors and digital instruments, developing software simulations, and cross-referencing and analyzing different types of digital materials to extract information for complex problem-solving and decision-making tasks. Software-engineering research offers three major technical and methodological solutions to this challenge: (a) service orientation and virtualization for building complex systems as scalable evolving aggregations of software components; (b) model-driven engineering (MDE) for systematic software construction through model-transformation chains; and (c) tools and processes for effective distributed teamwork. Recognizing a great opportunity in this alignment of knowledge-workers’ needs and software-engineering competencies, I have planned a research program that aims to support interdisciplinary teams of knowledge workers through model-driven engineering of integrated digital infrastructures. I use the term “integrated digital infrastructures” to mean an evolving ecosystem of independently developed software components and smart devices, flexibly coordinated to support complex activities of expert teams. Adopting a core MDE methodology, the proposed program will answer basic research questions on how to support evolution and maintenance of MDE software, so that manual post-generation code refinements may be propagated back to the relevant models in the code-construction chain. Next, we will apply (and stress test) the MDE methodology by integrating it with different types of models that embody domain-specific semantics in order to develop (a) a high-level programming model for software systems integrating sensors and smart devices, and (b) a new breed of socially aware, RDF-mediated asset repositories. The underlying hypothesis is that model-transformation processes should rely on the domain-specific semantics of the manipulated models, to support the alignment of the constructed software with its requirements. Aiming at systematizing the users’ interaction with the underlying system, we plan to develop a general monitoring and coordination service, informed by the underlying data models and integrated with personalizable applications, to enable users to interact with the infrastructure and each other, any time through any device. Finally, the usage record of the infrastructure, as captured by the monitoring service, will be analyzed to gain insights on the data, the team practices and their evolution. The potential impact of these activities is substantial. (1) Improving our ability to maintain model-driven constructed software in sync with its underlying models and transformation rules, even as it evolves with new requirements, is essential for the adoption of this methodology, which promises improvements in code quality and increased productivity. (2) Equally importantly, systematizing the construction and improving the utility and usability of digital infrastructures promises to substantially improve the productivity of knowledge-worker teams, and advance our digital-economy agenda. (3) Finally, the choice of the Smart-CondoTM project as the testbed for the empirical real-world validation of the results of the proposed activities was motivated by the desire to put software in the service of patients and the clinicians who care for them and to develop a comprehensive platform for patient-centric healthcare.

拟议的研究计划旨在为开发软件组件的复杂生态系统的理论和实践做出贡献，以支持从事知识型工作的个人团队。 今天，跨学科的所有基于知识的工作都涉及使用软件，使用传感器和数字仪器，开发软件模拟，以及交叉引用和分析不同类型的数字材料，以提取用于复杂问题解决和决策任务的信息。软件工程研究为这一挑战提供了三个主要的技术和方法解决方案：（a）面向服务和虚拟化，用于将复杂系统构建为可扩展的不断发展的软件组件集合;（B）模型驱动工程（MDE），用于通过模型转换链进行系统的软件构建;以及（c）有效的分布式团队合作的工具和过程。 认识到知识工作者的需求和软件工程能力的这种一致性是一个很好的机会，我计划了一个研究计划，旨在通过集成数字基础设施的模型驱动工程来支持跨学科的知识工作者团队。我使用“集成数字基础设施”一词来表示一个不断发展的生态系统，由独立开发的软件组件和智能设备组成，灵活协调以支持专家团队的复杂活动。采用核心MDE方法，拟议的计划将回答如何支持MDE软件的进化和维护的基本研究问题，使手动生成后的代码细化可能会传播回代码构建链中的相关模型。接下来，我们将应用（和压力测试）MDE方法，通过将其与体现特定领域语义的不同类型的模型集成，以开发（a）集成传感器和智能设备的软件系统的高级编程模型，以及（B）新一代的社会感知，RDF介导的资产存储库。基本的假设是，模型转换过程应该依赖于被操纵的模型的特定于域的语义，以支持构建的软件与其需求的对齐。为了使用户与底层系统的交互系统化，我们计划开发一个通用的监控和协调服务，通过底层数据模型提供信息，并与个性化应用程序集成，使用户能够随时通过任何设备与基础设施进行交互。最后，将分析由监控服务捕获的基础设施的使用记录，以了解数据、团队实践及其演变。 这些活动的潜在影响是巨大的。 (1)提高我们维护模型驱动的构造软件与其底层模型和转换规则同步的能力，即使它随着新的需求而发展，对于采用这种方法至关重要，这种方法有望提高代码质量和提高生产力。 (2)同样重要的是，数字基础设施建设的系统化以及数字基础设施的实用性和可用性的提高有望大幅提高知识工作者团队的生产力，并推进我们的数字经济议程。 (3)最后，选择Smart-CondoTM项目作为对拟议活动结果进行实证真实世界验证的测试平台，是出于将软件用于患者和护理他们的临床医生服务以及开发以患者为中心的医疗保健综合平台的愿望。