Industrial-grade Verification & Validation of Evolving Systems - Canadian cluster

由于开发中的快速迭代周期和/或自适应和学习的能力，进化系统（ESs）形成了一类可以快速改变其行为的新系统；它们可以包括支持机器学习（ML）的组件。到2025年，加拿大人工智能相关产品的市场预计将达到1270亿美元。基于机器学习的（关键）应用程序的足迹在加拿大和世界范围内急剧增加。关键领域包括但不限于航空航天、网络安全、汽车与交通、银行与金融、商业和数据分析。ESs没有遵循为传统系统制定的建模、设计和实施标准：与大多数传统系统相比，ES的行为不那么透明；ESs的开发是敏捷的，通常由数据或用户不断发展的期望驱动。ESs的正式规范可能会缺失，而用数据或非结构化文本表示的需求通常是可用的。行业和我们的安全需要全面彻底的ESs质量保证的工业级测试和验证（T&V）方法。CRIM，一个加拿大的研究机构和三个加拿大的工业组织联合了来自四个欧洲国家的20多个组织，在IVVES（演进系统的工业级验证和验证）项目的背景下满足工业需求。IVVES已获得EUREKA的下属机构ITEA的批准。在IVVES-CC内进行的为期3年的研究将提出系统的方法，以实现强大而全面的工业级ESs T&V。它开发了(1)专用于支持ml的应用程序的T&V方法，(2)专用于ESs的人工智能和数据驱动的T&V方法，以覆盖目前无法由最先进的基于规范的测试覆盖的领域，(3)智能工程方法，使用数据分析为ESs建立高效和高质量的工程流程。这些方法将在工业用例中进行评估；HQP和工业合作伙伴将接受培训，掌握已开发的方法，以便在行业中更好地推广。该项目得到了CRIAQ的部分支持。

Evolving systems (ESs) form a new class of systems that can rapidly change their behavior, due to fast iteration cycles in development and/or to their ability to self-adapt and learn; they can include Machine Learning (ML)-enabled components. By 2025 the market for artificial intelligence related products in Canada is expected to reach $127 billion. The footprint of ML-based (critical) applications is dramatically increasing in Canada and worldwide. Critical domains include but are not limited to Aerospace, Cybersecurity, Automotive & Transportation, Banking & Finance and Business and data analytics. ESs do not follow the modelling, design and implementation standards developed for traditional systems: the behavior of ES is less transparent than for most of traditional systems; the development of ESs is agile and often driven by data or user-evolving expectations. Formal specifications for ESs can be missing and requirements expressed with data or unstructured text are often available. Industrial-grade testing and verification (T&V) approaches for a comprehensive and thorough quality assurance of ESs are needed by the industry and for our safety. CRIM, a Canadian research organisation, and three Canadian industrial organisations teamed up over 20 organisations from four European countries to fulfil the industrial needs within the context of the project IVVES (Industrial-graded Verification and Validation of Evolving Systems). IVVES has been approved by ITEA that is a cluster of EUREKA. The research conducted for 3 years within IVVES-CC will propose systematic approaches for robust and comprehensive, industrial-grade T&V of ESs. It develops (1) T&V approaches dedicated to ML-enabled applications, (2) AI and data-driven T&V approaches dedicated to ESs to cover areas that currently cannot be covered by state-of-the-art specification-based testing and (3) smart engineering approaches that use data analytics to establish efficient and high-quality engineering processes for ESs. The approaches will be evaluated on industrial use cases; HQP and industrial partners will be trained to master the developed approaches for a better roll-out in the industry. The project is partially supported by CRIAQ.