首页> 外文会议>Working Conference on Mining Software Repositories >Deficient documentation detection a methodology to locate deficient project documentation using topic analysis
【24h】

Deficient documentation detection a methodology to locate deficient project documentation using topic analysis

机译:缺陷文档检测:使用主题分析来查找缺陷项目文档的方法

获取原文

摘要

A project's documentation is the primary source of information for developers using that project. With hundreds of thousands of programming-related questions posted on programming Q&A websites, such as Stack Overflow, we question whether the developer-written documentation provides enough guidance for programmers. In this study, we wanted to know if there are any topics which are inadequately covered by the project documentation. We combined questions from Stack Overflow and documentation from the PHP and Python projects. Then, we applied topic analysis to this data using latent Dirichlet allocation (LDA), and found topics in Stack Overflow that did not overlap the project documentation. We successfully located topics that had deficient project documentation. We also found topics in need of tutorial documentation that were outside of the scope of the PHP or Python projects, such as MySQL and HTML.
机译:项目文档是使用该项目的开发人员的主要信息来源。在编程问答网站(如Stack Overflow)上发布了成千上万与编程相关的问题,我们质疑开发人员编写的文档是否为程序员提供了足够的指导。在这项研究中,我们想知道项目文档中是否涵盖了不足的主题。我们结合了Stack Overflow的问题以及PHP和Python项目的文档。然后,我们使用潜在的Dirichlet分配(LDA)将主题分析应用于此数据,并在Stack Overflow中找到与项目文档不重叠的主题。我们成功地找到了项目文档不足的主题。我们还发现需要教程文档的主题不在PHP或Python项目的范围之内,例如MySQL和HTML。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号