ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2021, Vol. 58 ›› Issue (4): 763-776.doi: 10.7544/issn1000-1239.2021.20200756

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

基于版本更新日志的移动应用演化趋势自动分析

钟仁毅1,王翀1,梁鹏1,罗忠2   

  1. 1(武汉大学计算机学院 武汉 430072);2(海军工程大学舰船与海洋学院 武汉 430033) (xiyezry@whu.edu.cn)
  • 出版日期: 2021-04-01
  • 基金资助: 
    国家重点研发计划项目(2018YFB1003800);国家自然科学基金项目(61702378,61972292,62032016)

Automatic Trend Analysis of Mobile App Updates Based on App Changelogs

Zhong Renyi1, WangChong1, Liang Peng1, Luo Zhong2   

  1. 1(School of Computer Science,Wuhan University,Wuhan 430072);2(Department of Naval Architecture Engineering,Naval University of Engineering,Wuhan 430033)
  • Online: 2021-04-01
  • Supported by: 
    This work was supported by the National Key Research and Development Program of China (2018YFB1003800) and the National Natural Science Foundation of China (61702378, 61972292, 62032016).

摘要: 数据驱动的移动应用开发、维护和演化分析正成为移动应用领域的研究热点.然而,鲜少有研究以移动应用的版本更新记录为对象,从需求类型的角度探索开发者在发布移动应用时的偏好以及移动应用的开发和更新趋势.为此,以苹果App Store中社交、旅游和阅读3种类别60个应用的6527条版本更新记录条目为数据集,验证并评估了监督式机器学习算法对移动应用版本更新记录自动分类的可行性和有效性;进一步,基于最优的监督式机器学习算法对版本更新记录自动分类的结果,从需求类型和更新热点2个方面对移动应用的演化特点进行了分析,展示了苹果App Store中3种类别的移动应用在近5年的更新趋势,以帮助研究者与实践者从需求工程的角度了解当前移动应用市场的现状和变化动态.

关键词: 需求工程, 非功能需求, 发布计划, 更新日志, 移动应用市场, 实证研究

Abstract: Data-driven analysis on the development, maintenance, and evolution has recently become an area of active research. However, little is known to treat app changelogs as the input to explore the types of requirements that app developers pay the most attention when releasing an app, as well as trend of app development and updates. This paper reports the results of an exploratory study in which we analyze the requirements and buzzwords that dominate the changes of apps, according to a set of 6527 changes collected from 60 apps from three categories in the Apple App Store: “Travel”, “Social Networking” and “Books”. First, the performance of three supervised machine learning algorithms is evaluated to find the most suitable classifiers for the automatic classification of app changelogs. Furthermore, based on the classification results of app changelogs, characteristics and trends of app updates are revealed from two perspectives, i.e., the requirement type that app changelog items mention and the hot words in app changelog items that are labeled as a certain requirement type. The results are valuable for researchers and practitioners to have a comprehensive understanding on the current app stores from RE perspective.

Key words: requirements engineering, non-functional requirement, release planning, changelogs, app store, empirical study

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