Towards prioritizing user-related issue reports of mobile applications

  • Ehsan NoeiEmail author
  • Feng Zhang
  • Shaohua Wang
  • Ying Zou


The competitive market of mobile applications (apps) has driven app developers to pay more attention to addressing the issues of mobile apps. Prior studies have shown that addressing the issues that are reported in user-reviews shares a statistically significant relationship with star-ratings. However, despite the prevalence and importance of user-reviews and issue reports prioritization, no prior research has analyzed the relationship between issue reports prioritization and star-ratings. In this paper, we integrate user-reviews into the process of issue reports prioritization. We propose an approach to map issue reports that are recorded in issue tracking systems to user-reviews. Through an empirical study of 326 open-source Android apps, our approach achieves a precision of 79% in matching user-reviews with issue reports. Moreover, we observe that prioritizing the issue reports that are related to user-reviews shares a significant positive relationship with star-ratings. Furthermore, we use the top apps, in terms of star-ratings, to train a model for prioritizing issue reports. It is a good practice to learn from the top apps as there is no well-established approach for prioritizing issue reports. The results show that mobile apps with a similar prioritization approach to our trained model achieve higher star-ratings.


Mobile application Issue report prioritization User-review Issue tracking system 



We thank the anonymous reviewers who reviewed our paper and the associated editor for their valuable feedback.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringQueen’s UniversityKingstonCanada
  2. 2.School of ComputingQueen’s UniversityKingstonCanada
  3. 3.Department of InformaticsNew Jersey Institute of TechnologyNewarkUSA

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