Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2021
Abstract
Million of mobile apps have been released to the market. Developers need to maintain these apps so that they can continue to benefit end users. Developers usually extract useful information from user reviews to maintain and evolve mobile apps. One of the important activities that developers need to do while reading user reviews is to locate the source code related to requested changes. Unfortunately, this manual work is costly and time consuming since: (1) an app can receive thousands of reviews, and (2) a mobile app can consist of hundreds of source code files. To address this challenge, Palomba et al. recently proposed CHANGEADVISOR that utilizes user reviews to locate source code to be changed. However, we find that it cannot identify real source code to be changed for part of reviews. In this work, we aim to advance Palomba et al.’s work by proposing a novel approach that can achieve higher accuracy in change localization. Our approach first extracts the informative sentences (i.e., user feedback) from user reviews and identifies user feedback related to various problems and feature requests, and then cluster the corresponding user feedback into groups. Each group reports the similar users’ needs. Next, these groups are mapped to issue reports by using W ord2V ec. The resultant enriched text consisting of user feedback and their corresponding issue reports is used to identify source code classes that should be changed by using our novel weight selection-based cosine similarity metric. We have evaluated the new proposed change request localization approach (Where2Change) on 31,597 user reviews and 3,272 issue reports of 10 open source mobile apps. The experiments demonstrate that Where2Change can successfully locate more source code classes related to the change requests for more user feedback clusters than CHANGEADVISOR as demonstrated by higher Top-N and Recall values. The differences reach up to 17 for Top-1, 18.1 for Top-3, 17.9 for Top-5, and 50.08% for Recall. In addition, we also compare the performance of Where2Change and two previous Information Retrieval (IR)-based fault localization technologies:BLUiR and BLIA. The results showed that our approach performs better than them. As an important part of our work, we conduct an empirical study to investigate the value of using both user reviews and historical issue reports for change request localization; the results shown that historical issue reports can help to improve the performance of change localization.
Keywords
User review, Issue report, Mobile app, Change Request localization, Software maintenance
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE Transactions on Software Engineering
Volume
47
Issue
11
First Page
2590
Last Page
2616
ISSN
0098-5589
Identifier
10.1109/TSE.2019.2956941
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
ZHANG, Tao; CHEN, Jiachi; ZHAN, Xian; LUO, Xiapu; LO, David; and JIANG, He.
Where2Change: Change request localization for app reviews. (2021). IEEE Transactions on Software Engineering. 47, (11), 2590-2616.
Available at: https://ink.library.smu.edu.sg/sis_research/4503
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1109/TSE.2019.2956941