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P2 Characterizing search activities on stack overflow

刻画 Stack Overflow 上的搜索活动
FSE Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering2021匹配度 1/10 · 该论文分析开发者在 Stack Overflow 上的搜索日志与查询重构行为,属于开发者工具/经验研究,与用户关注的静态分析、LLM/Agent 程序分析、浮点程序分析、贝叶斯程序分析等核心方向几乎没有直接交集。引用 16 inbox
Jiakun Liu, Sebastian Baltes, Christoph Treude, David Lo, Yun Zhang, Xin Xia
crossref: 2026-09-12

AI 速览

一句话:通过真实搜索日志刻画开发者在 Stack Overflow 上的搜索与查询重构行为,并给出改进检索的建议。

论文关注开发者在 Stack Overflow 上搜索编程问题解决方案时,常难以检索到真正所需知识的问题。已有工作多提出查询重构与答案摘要技术,但缺少基于真实搜索日志的大规模分析。作者利用 Stack Overflow Web 服务器请求日志,刻画搜索活动,重点分析查询重构策略与查询结构。结果显示,最常见的活动是重构紧邻的前序查询;71.78% 的重构可归入通用搜索引擎的 13 类重构策略;17.41% 的会话只搜索源代码片段(如类名、方法名),未指明语言、库或框架。论文据此为版主提出建议,并指出未来方向,如构建编程术语关系库以提升搜索性能。

问题
开发者在 Stack Overflow 上搜索编程知识时存在检索鸿沟,且缺乏基于真实搜索日志的大规模行为刻画。
方法
利用 Stack Overflow Web 服务器请求产生的真实搜索日志,对搜索活动、查询重构策略和查询结构进行统计与分类分析。
评估
通过日志数据的定量分析(如重构策略匹配比例、会话中仅含代码片段的比例)总结开发者挑战,并据此提出平台改进建议。
原文摘要(Abstract)

To solve programming issues, developers commonly search on Stack Overflow to seek potential solutions. However, there is a gap between the knowledge developers are interested in and the knowledge they are able to retrieve using search engines. To help developers efficiently retrieve relevant knowledge on Stack Overflow, prior studies proposed several techniques to reformulate queries and generate summarized answers. However, few studies performed a large-scale analysis using real-world search logs. In this paper, we characterize how developers search on Stack Overflow using such logs. By doing so, we identify the challenges developers face when searching on Stack Overflow and seek opportunities for the platform and researchers to help developers efficiently retrieve knowledge. To characterize search activities on Stack Overflow, we use search log data based on requests to Stack Overflow's web servers. We find that the most common search activity is reformulating the immediately preceding queries. Related work looked into query reformulations when using generic search engines and found 13 types of query reformulation strategies. Compared to their results, we observe that 71.78% of the reformulations can be fitted into those reformulation strategies. In terms of how queries are structured, 17.41% of the search sessions only search for fragments of source code artifacts (e.g., class and method names) without specifying the names of programming languages, libraries, or frameworks. Based on our findings, we provide actionable suggestions for Stack Overflow moderators and outline directions for future research. For example, we encourage Stack Overflow to set up a database that includes the relations between all computer programming terminologies shared on Stack Overflow, e.g., method name, data structure name, design pattern, and IDE name. By doing so, Stack Overflow could improve the performance of search engines by considering related programming terminologies at different levels of granularity.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot6324,
  title = {Characterizing search activities on stack overflow},
  author = {Jiakun Liu and Sebastian Baltes and Christoph Treude and David Lo and Yun Zhang and Xin Xia},
  booktitle = {FSE},
  year = {2021},
  doi = {10.1145/3468264.3468582}
}