We present CAISAR, an open-source platform under active development for the characterization of AI systems' robustness and safety. CAISAR provides a unified entry point for defining verification problems by using WhyML, the mature and expressive language of the Why3 verification platform. Moreover, CAISAR orchestrates and composes state-of-the-art machine learning verification tools which, individually, are not able to efficiently handle all problems but, collectively, can cover a growing number of properties. Our aim is to assist, on the one hand, the V\&V process by reducing the burden of choosing the methodology tailored to a given verification problem, and on the other hand the tools developers by factorizing useful features-visualization, report generation, property description-in one platform. CAISAR will soon be available at https://git.frama-c.com/pub/caisar.
翻译:我们介绍了一个开放源码的平台,这个平台正在积极开发,以描述AI系统是否稳健和安全;CAISAR提供了一个统一的切入点,通过使用“为什么ML”这个“为什么3”核查平台的成熟和表达语言来界定核查问题;此外,CAISAR管弦乐队和组成最先进的机器学习核查工具,这些工具无法单独有效地处理所有问题,但可以集体地涵盖越来越多的特性;我们的目的是一方面通过减少选择适合特定核查问题的方法的负担来帮助VQV进程,另一方面通过将有用的特征化、报告生成、财产描述纳入一个平台来帮助工具开发者;CAISAR不久将在https://git.frama-c.com/pub/caisar上查阅。