AI 中文总结
针对技术面试与岗位脱节的问题，基于911名受访者回顾和公开问题分析，提出基于工单的务实评估框架，使面试成为工作的压缩版本。
AI 中文摘要
技术招聘已日益成为一套自成体系的技能系统，要求候选人准备的流程仅部分类似于所应聘的职位。本文重构了软件工程社区在2005年至2026年四个时代中对该流程的记忆。来自911名受访者的回顾性评分显示，面试工作和负担呈持续扩大趋势，而对公开准备问题的分析发现，大多数被测试的知识在普通软件工程项目中具有合理用途。这一矛盾只是表面性的：当相关主题超出职位空缺而累积、在人为约束下呈现，或缺乏基于工作的通用标准进行选择和解释时，它们仍可能构成无效流程。本文以基于工单的务实评估框架作为回应，这是一个规范性参考框架，从声明的职责、近期工单和项目入门工作中推导出有界的评估。它保留常规工具，定义三个明确的证据门，限制重复会话，并在决策得到支持时停止。目标是使面试成为工作的压缩版本，而非候选人仅为获得职位而必须学习的平行职业。
英文摘要
Technical hiring has increasingly become a skill system of its own, requiring candidates to prepare for processes that only partially resemble the position being filled. This paper reconstructs how the software-engineering community remembers that process across four eras from 2005 to 2026. Retrospective ratings from 911 respondents show a history of expanding interview work and burden, while an analysis of public preparation questions finds that most tested knowledge has a plausible use in an ordinary software-engineering project. The contradiction is only apparent: relevant topics can still form an invalid process when they are accumulated beyond the vacancy, presented under artificial constraints, or selected and interpreted without a common job-derived standard. The paper responds with the Ticket-Based Pragmatic Assessment Framework, a prescriptive reference framework that derives a bounded assessment from declared responsibilities, near-term tickets, and project-entry work. It preserves normal tools, defines three explicit evidence gates, limits repeated sessions, and stops when the decision is supported. The objective is to make an interview a compressed version of the job rather than a parallel profession that candidates must learn merely to obtain it.
Comments19 pages, 12 tables
