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P2 Improving Design Reviews at Google

改进 Google 的设计评审
ASE 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)2023匹配度 1/10 · 该论文关注 Google 内部设计评审流程的自动化与审批效率提升,属于软件工程/开发者工具方向,未涉及静态分析、程序分析、LLM/Agent、浮点程序分析或贝叶斯程序分析,与用户研究画像的核心问题几乎不重叠。引用 0 inbox
Celal Ziftci, Ben Greenberg
crossref: 2026-09-12dblp: 2026-09-12

AI 速览

一句话:提出结构化自动化的设计评审方案,将 Google 设计文档审批中位时间缩短 25%。

设计评审是软件开发生命周期的重要早期阶段,利益相关者借此讨论设计可行性、发现代价高昂的错误与不一致之处。为提升开发速度,设计负责人需要尽快获得审批。本文介绍 Google 工程设计中设计评审的典型流程,并提出一种新颖、结构化且自动化的解决方案以缩短评审周期。作者基于四年内 41,030 名用户撰写的 141,652 份已批准文档数据,发现该方案使审批中位时间减少 25%,持续使用时收益更明显。文章还给出定性数据以证明方案成功,讨论影响评审延迟的因素,提出应对策略,并分享使用经验。

问题
软件设计评审流程中,设计负责人能否尽快获得审批直接影响开发速度,但现有流程存在延迟和不一致问题。
方法
介绍 Google 设计评审的典型实践,并提出一种结构化、自动化的设计评审支持方案,以加速审批并提升一致性。
评估
基于四年内 141,652 份已批准文档、41,030 名用户的数据进行定量分析,并结合定性反馈评估方案效果。
原文摘要(Abstract)

Design review is an important initial phase of the software development life-cycle where stakeholders gain and discuss early insights into the design's viability, discover potentially costly mistakes, and identify inconsistencies and inadequacies. For improved development velocity, it is important that design owners get their designs approved as Quickly as possible. In this paper, we discuss how engineering design reviews are typically conducted at Google, and propose a novel, structured, automated solution to improve design review velocity. Based on data collected on 141,652 approved documents authored by 41,030 users over four years, we show that our proposed solution decreases median time-to-approval by 25%, and provides further gains when used consistently. We also provide qualitative data to demonstrate our solution's success, discuss factors that impact design review latency, propose strategies to tackle them, and share lessons learned from the usage of our solution.

链接与引用

DOI 原文 · PDF(开放获取) · DBLP

BibTeX
@inproceedings{ZiftciG23,
  title = {Improving Design Reviews at Google},
  author = {Celal Ziftci and Ben Greenberg},
  booktitle = {ASE},
  year = {2023},
  doi = {10.1109/ase56229.2023.00066}
}