ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2021, Vol. 58 ›› Issue (4): 731-748.doi: 10.7544/issn1000-1239.2021.20200732

所属专题: 2021人工智能背景下的需求工程专题

• 人工智能 • 上一篇    下一篇



  1. 1(高可信软件技术教育部重点实验室(北京大学) 北京 100871);2(北京大学信息科学技术学院计算机科学技术系 北京 100871);3(内蒙古师范大学计算机科学技术学院 呼和浩特 010022) (
  • 出版日期: 2021-04-01
  • 基金资助: 

An Approach for Improving the Requirements Quality of User Stories

Wang Chunhui1,3, Jin Zhi1,2, Zhao Haiyan1,2, Cui Muyuan1,2   

  1. 1(Key Laboratory of High Confidence Software Technology (Peking University),Ministry of Education,Beijing 100871);2(Department of Computer Science and Technology,School of Electronics Engineering and Computer Science,Peking University,Beijing 100871);3(College of Computer Science and Technology,Inner Mongolia Normal University,Hohhot 010022)
  • Online: 2021-04-01
  • Supported by: 
    This work was supported by the National Natural Science Foundation of China (61620106007, 61751210, 61690200).

摘要: 敏捷开发采用用户故事表达用户需求.一般采用格式受限的自然语言编写,但在用户故事编写过程中经常出现一些表述上的缺陷.典型的缺陷包括缺失必要信息、意思表达含糊不清、故事间有重复或存在冲突等.这很大程度上影响了需求的质量,影响软件开发项目的进行.提出一种用户故事需求质量提升方法.从故事缺陷定位的角度出发,该方法构建了用户故事概念模型,并根据实际案例总结并提出11条用户故事应遵循的质量准则.从而提出故事结构分析、句法模式分析以及语法分析等技术,用于自动构建带场景用户故事的实例层模型,并根据准则进行故事缺陷检测,进而提升用户故事质量.在包含36个用户故事84个场景的实际项目中进行实验,自动检测出173个缺陷,缺陷检测的准确率和召回率分别达到88.79%和95.06%.

关键词: 用户故事, 需求缺陷, 需求质量提升, 用户故事质量模型, 需求缺陷检测

Abstract: User story is a widely adopted requirements notation in agile development. Generally, user stories are written by customers or users in natural language with limited format, but there are often some defects in the writing of user stories. The typical detects include the lack of necessary information to make it difficult to understand, and the ambiguous expressions make the requirements impossible to estimate, and some stories have duplicates and conflicts. These defects affect the quality of requirements, resulting in incomplete, inconsistent, untestable, and so on. This paper proposes an automated approach for detecting the defects in user story requirements and improving the quality of user stories. First, a conceptual model of user story for defect identification is proposed. An approach based on structural analysis, syntactic analysis and semantic analysis is used for constructing the conceptual model. Secondly, 11 quality criteria are summarized from the actual cases and used to identify the defects in the user stories. An experimental study is carried out on a story set with 36 user stories and 84 scenarios. The automatic detection tool reports 173 defects, and the precision and recall of the reported results are 88.79% and 95.06%, respectively.

Key words: user story, requirements defect, requirements quality improving, user story quality model, requirements defect detection