一句话：提出自动化框架 IDEA，基于在线应用评论分析及时、精准地识别应用新出现的问题。
应用评论为开发者主动收集用户抱怨并改进应用提供了机会，但评论数量巨大且含噪声（如拼写错误），使准确识别新出现的应用问题变得困难。本文提出自动化框架 IDEA，旨在基于在线评论分析有效识别新出现的应用问题。作者在 Google Play 和 Apple App Store 的六个流行应用上评估 IDEA，并以官方应用更新日志作为真值。实验结果表明 IDEA 能有效识别新出现的问题；来自工程师和产品经理的反馈显示，88.9% 的受访者认为所识别问题能促进实际应用开发。IDEA 还成功应用于腾讯多个服务数亿用户的产品。
Detecting emerging issues (e.g., new bugs) timely and precisely is crucial for developers to update their apps. App reviews provide an opportunity to proactively collect user complaints and promptly improve apps' user experience, in terms of bug fixing and feature refinement. However, the tremendous quantities of reviews and noise words (e.g., misspelled words) increase the difficulties in accurately identifying newly-appearing app issues. In this paper, we propose a novel and automated framework IDEA, which aims to IDentify Emerging App issues effectively based on online review analysis. We evaluate IDEA on six popular apps from Google Play and Apple's App Store, employing the official app changelogs as our ground truth. Experiment results demonstrate the effectiveness of IDEA in identifying emerging app issues. Feedback from engineers and product managers shows that 88.9% of them think that the identified issues can facilitate app development in practice. Moreover, we have successfully applied IDEA to several products of Tencent, which serve hundreds of millions of users.
DOI 原文 ·
@inproceedings{paperbot4446,
title = {Online app review analysis for identifying emerging issues},
author = {Cuiyun Gao and Jichuan Zeng and Michael R. Lyu and Irwin King},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3180218}
}