ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2021, Vol. 58 ›› Issue (4): 763-776.doi: 10.7544/issn1000-1239.2021.20200756

Special Issue: 2021人工智能背景下的需求工程专题

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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).

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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