Recommending and Localizing Change Requests for Mobile Apps Based on User Reviews

@article{Palomba2017RecommendingAL,
  title={Recommending and Localizing Change Requests for Mobile Apps Based on User Reviews},
  author={Fabio Palomba and Pasquale Salza and Adelina Ciurumelea and Sebastiano Panichella and Harald C. Gall and Filomena Ferrucci and Andrea De Lucia},
  journal={2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)},
  year={2017},
  pages={106-117}
}
Researchers have proposed several approaches to extract information from user reviews useful for maintaining and evolving mobile apps. However, most of them just perform automatic classification of user reviews according to specific keywords (e.g., bugs, features). Moreover, they do not provide any support for linking user feedback to the source code components to be changed, thus requiring a manual, time-consuming, and error-prone task. In this paper, we introduce ChangeAdvisor, a novel… CONTINUE READING
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  • Moreover, the obtained results show that ChangeAdvisor is more accurate than a baseline approach for linking user feedback clusters to the source code in terms of both precision (+47%) and recall (+38%).

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Recommending and Localizing Code Changes for Mobile Apps based on User Reviews: Online Appendix

  • F. Palomba, P. Salza, +4 authors A. De Lucia
  • . [Online]. Available: https://sites.google.com…
  • 2017
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