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

进化系统（ES）形成了一类新的系统，由于开发中的快速迭代周期和/或其自适应和学习能力，它们可以快速改变其行为;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ML的（关键）应用程序的足迹在加拿大和全球范围内急剧增加。关键领域包括但不限于航空航天、网络安全、汽车和运输、银行和金融以及商业和数据分析。ES不遵循为传统系统开发的建模、设计和实现标准：ES的行为不如大多数传统系统透明; ES的开发是敏捷的，通常由数据或用户不断变化的期望驱动。ES的正式规范可能会丢失，而用数据或非结构化文本表达的需求通常是可用的。工业级测试和验证（T&V）方法用于全面彻底的ES质量保证是行业和我们的安全所需要的。CRIM是加拿大的一家研究机构，它与三家加拿大工业组织联合了来自四个欧洲国家的20多个组织，以满足IVVES项目（工业级验证和验证不断发展的系统）背景下的工业需求。IVVES已获得尤里卡集群伊泰亚的批准。在IVVES-CC内进行的为期3年的研究将提出系统的方法，用于强大而全面的工业级ES T&V。它开发（1）专用于ML启用应用的T&V方法，（2）AI和数据驱动的测试和验证方法，专门用于ES，以覆盖目前最先进的基于规范的测试无法覆盖的领域;（3）智能工程方法，使用数据分析为ES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，以掌握开发的方法，以便更好地在行业中推广。该项目得到了调查委员会的部分支持。

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.