Artificial Intelligence (AI) and its research area Machine Learning (ML) are becoming increasingly important in many areas related to information processing, decision making, automation and systems engineering. While verification and validation for today’s large and complex software-based infrastructures are already at its limits, the advent of AI and ML, as well as their integration into larger IT infrastructures, dramatically exacerbates this existing problem. While the criticality of ES demands a rigorous, comprehensive and trustworthy quality assurance, both before and after deployment, the sheer size and complexity of these systems, their high innovation dynamics and the potential ability to learn and to change during runtime pose new challenges in the area of system validation and verification that are not yet completely understood.
Targeting the challenges in verification and validation of ES, IVVES will systematically develop Artificial Intelligence approaches for robust and comprehensive, industrial-grade verification and validation of “embedded AI”, i.e. machine-learning for control of complex, mission-critical evolving systems and services covering the major industrial domains in Europe. IVVES will develop the approaches in three direction to cover three amin aspects in quality development for ES.
All IVVES methods, techniques and tools will be driven and evaluated by the cases studies representing relevant industrial domains: Transportation and Automotive, Finance, Health, Telecommunication, Cyber Security, Industrial Automation and Agriculture and Forestry. To conclude, IVVES will develop cross-domain solutions that allow for a broad applicability and serve as a basis for standardization and certification approaches so that IVVES testing for AI-based systems will shape a breakthrough in innovation power for the major industrial domains in Europe.