Predictive & Adaptive Software Language Engineering

预测性

• 批准号: RGPIN-2022-03252
• 负责人: Mussbacher, Gunter
• 金额: $ 2.11万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752208
• 关键词: Predictive; Adaptive; Software; Language; Engineering

Over the next years, key systems that significantly impact societies and everyone's everyday lives will be software-intensive, cyber-physical systems (CPS), with billions of connected smart objects and devices forecasted to exist in such systems (e.g., smart cities, buildings, and electrical grids). CPS include software as well as hardware components that need to interact with each other in increasingly complex ways and are described with a heterogeneous set of specification languages. CPS are often socio-technical systems, characterized by the complex interrelatedness of people with conflicting goals, technology, organizational processes, and the diverse social context in which these systems are deployed. A key aspect of such systems is a feedback loop that involves complex trade-off analyses and allows the CPS to self-adapt, leading to ever more dynamic systems. Such CPS will have to address many different concerns, some well-known (security and privacy), some having emerged over recent years (sustainability and human values), and unknown others that will emerge in the future. Just as natural languages evolve to communicate about new concerns and better describe new issues that mankind must face, software languages also need to continuously adapt to enable the ongoing specification of complex socio-technical systems and to cope with the profound impact that such systems have on humanity. Changes to software languages are not only triggered by emerging qualities such as sustainability or increasing system complexity, but also because problem domains are better understood over time, which needs to be reflected better by new or more concise constructs in domain-specific software languages. In essence, a software-intensive system, its users and their environments, and the software development environment form one interconnected, highly dynamic, heterogeneous, and adaptive eco-system with several feedback loops that is described with many specification languages. If required adaptations to software languages could be predicted as early as possible, software languages could be adapted more rapidly to provide the constructs needed to effectively describe CPS. Currently, the exploited feedback loop in adaptive socio-technical systems is limited to the users and their environment. This research program proposes to extend the feedback loop to the development environment including software languages, developers, and language engineers. By establishing predictive and adaptive software languages, it is possible to evolve software languages more effectively based on changes determined from the extended feedback loop, making such software languages a viable development choice for the Canadian software industry even in the context of rapidly evolving software development projects. The impact is improved productivity, leading to greater innovation in and increased competitiveness of the many organizations served by the Canadian software industry.

在未来几年，对社会和每个人的日常生活产生重大影响的关键系统将是软件密集型的网络物理系统（CPS），预计此类系统中将存在数十亿个连接的智能对象和设备（例如，智能城市、建筑和电网）。CPS包括软件和硬件组件，这些组件需要以越来越复杂的方式相互交互，并使用一组异构的规范语言进行描述。CPS通常是社会技术系统，其特征是具有相互冲突的目标，技术，组织流程以及这些系统部署的不同社会背景的人的复杂相互关联。这种系统的一个关键方面是一个反馈回路，它涉及复杂的权衡分析，并允许CPS自我适应，从而形成更加动态的系统。这样的CPS必须解决许多不同的问题，一些是众所周知的（安全和隐私），一些是近年来出现的（可持续性和人类价值观），还有一些是未来会出现的未知问题。正如自然语言不断发展以交流新的关注点并更好地描述人类必须面对的新问题一样，软件语言也需要不断适应，以支持复杂社会技术系统的持续规范，并科普此类系统对人类的深刻影响。软件语言的变化不仅是由诸如可持续性或增加系统复杂性等新出现的特性引发的，而且还因为随着时间的推移，问题领域会得到更好的理解，这需要通过特定领域软件语言中的新的或更简洁的结构来更好地反映。从本质上讲，软件密集型系统，它的用户和他们的环境，以及软件开发环境形成了一个互连的，高度动态的，异构的，自适应的生态系统，具有多个反馈回路，用许多规范语言描述。如果可以尽早预测软件语言所需的适应性，则软件语言可以更快地适应以提供有效描述CPS所需的结构。目前，在自适应社会技术系统中所利用的反馈回路仅限于用户及其环境。该研究计划建议将反馈循环扩展到包括软件语言，开发人员和语言工程师在内的开发环境。通过建立预测性和自适应性软件语言，可以根据扩展反馈循环确定的变化更有效地发展软件语言，使此类软件语言成为加拿大软件行业的可行开发选择，即使在快速发展的软件开发项目的背景下也是如此。其影响是提高了生产力，导致加拿大软件业所服务的许多组织的更大创新和竞争力的提高。