一句话：探讨生成式AI系统给软件测试带来的新挑战，并展望未来测试研究的机遇。
本文关注生成式人工智能（GenAI）系统给软件测试带来的新挑战。传统测试技术难以适用于能够生成新颖、创造性输出的 GenAI 系统，因为这些系统具有独特复杂性。作者通过分析这些系统的具体特征，指出传统测试方法为何不足或不再适用，并讨论未来研究机会，以期提升 GenAI 的质量保障与安全防护。作为一篇展望性论文，文章未报告具体实验评估，而是为 GenAI 测试这一快速演进领域勾勒研究议程。
Software Testing is a well-established area in software engineering, encompassing various techniques and methodologies to ensure the quality of software systems. However, with the arrival of generative artificial intelligence (GenAI) systems, new challenges arise in the testing domain. These systems, capable of generating novel and creative outputs, introduce unique complexities that require novel testing approaches. In this paper, I aim to explore the challenges posed by GenAI systems and discuss potential opportunities for future research in the area of testing. I will touch on the specific characteristics of GenAI systems that make traditional testing techniques inadequate or insufficient. By addressing these challenges and pursuing further research, we can enhance our understanding of how to safeguard GenAI and pave the way for improved quality assurance in this rapidly evolving area.