RoseMatcher: Identifying the Impact of User Reviews on App Updates
Tianyang Liu, Chong Wang, Kun Huang, Peng Liang, Beiqi Zhang, Maya, Daneva, Marten van Sinderen

TL;DR
This paper introduces RoseMatcher, an automatic method to match user reviews with app release notes, revealing their relationship and roles in app update processes through analysis of large-scale app data.
Contribution
The paper presents RoseMatcher, a novel approach for accurately matching user reviews with release notes, and provides insights into the roles of reviews in app updates.
Findings
RoseMatcher achieves a hit ratio of 0.718 in identifying relevant pairs.
Eight roles of user reviews in app updates are identified.
User reviews and release notes are closely related in timing and content.
Abstract
: The release planning of mobile apps has become an area of active research, with most studies centering on app analysis through release notes in the Apple App Store and tracking user reviews via issue trackers. However, the correlation between these release notes and user reviews in App Store remains understudied. : In this paper, we introduce , a novel automatic approach to match relevant user reviews with app release notes and identify matched pairs with high confidence. : We collected 944 release notes and 1,046,862 user reviews from 5 mobile apps in the Apple App Store as research data to evaluate the effectiveness and accuracy of , and conducted deep content analysis on matched pairs. : Our evaluation shows that can reach a hit ratio of 0.718…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Software Engineering Research · Open Source Software Innovations
