The need for more autonomy in many systems (e.g., automotive, aerospace) leads to increasingly complex systems that are becoming harder to verify and certify. This problem is compounded by the rising use of AI to enable such autonomy in many critical functions. Such situation has a significant impact on software development practice and makes it particularly difficult to assess risks and meet industry standards. This talk will focus on automated techniques, relying on various AI disciplines, to enable the testing and risk analysis of such systems, in ways that are practical and scalable. The talk will report and reflect on various research projects carried out in collaboration with the automotive and satellite industries.

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