从零到一搭建 AI 测试工作流:从需求到可执行测试
用一个可运行的 Python 工程,逐步建立需求识别、规则审阅、测试剧本生成、骨架填充和结果验证流程,附完整 Prompt、Skill 和公司接入方法。
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用一个可运行的 Python 工程,逐步建立需求识别、规则审阅、测试剧本生成、骨架填充和结果验证流程,附完整 Prompt、Skill 和公司接入方法。
Use multi-business reuse and existing subclass compatibility to explain request layering, calling contracts, and the limits of return-code retries.
Compare method and file subprocesses through shared fixtures, then follow discovery isolation, checkpoints, and parent-driven termination.
Follow partial setup, cleanup exceptions, and worker termination to understand cleanup registration, retained errors, and resource lifetime.
Follow assertion failure, cleanup errors, and a worker crash through multiple issues, completeness, task identity checks, and command exit codes.
以测试工程的测量边界为起点,区分 TTFT、TPOT、ITL、开闭环负载与 goodput,避免把压力机限制和失败请求隐藏在漂亮报表里。
以日志查询和创建外部对象为例,区分 Schema、业务校验、权限和副作用状态,说明函数调用为什么不能替运行时完成验收。
Follow worker crashes and missing results through discovery, process scheduling, fixtures, method deadlines, and report validation.