一句话：立场论文分析生成式AI如何改变测试与评估，并讨论其非确定性带来的验证挑战与机遇。
生成式人工智能正在改变软件开发流程中的测试与评估（T&E）：从自动设计测试用例到在DevOps流水线中实现持续测试，AI驱动工具提升了软件测试的效率、准确性和速度。与此同时，将AI组件集成到依赖软件的系统后，验证与确认（V&V）面临新挑战，传统T&E方法必须应对AI偏见、幻觉输出以及非确定性行为验证的复杂性。这篇立场论文考察现有T&E方法应如何演进以适应AI的随机性，并反向分析GenAI如何在整个软件开发生命周期中改变T&E实践。
Generative Artificial Intelligence (GenAI) is transforming software development processes, including test and evaluation (T&E). From automating test case design to enabling continuous testing in DevOps pipelines, AI-driven tools enhance the efficiency, accuracy, and speed of software testing. At the same time, the integration of AI components into software-reliant systems introduces new challenges for verification and validation (V&V). Traditional T&E methodologies must evolve to address issues such as AI bias, hallucinated outputs, and the complexity of validating non-deterministic behaviors. This position paper examines how existing T&E methods must evolve to account for AI's stochastic nature, and conversely how GenAI is transforming T&E practices across the software development lifecycle (SDLC).