用于识别新出现问题的在线应用程序评论分析

Cuiyun Gao, Jichuan Zeng, Michael R. Lyu, Irwin King
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引用次数: 95

摘要

及时准确地发现新出现的问题(如新bug)对开发者更新应用至关重要。应用评论提供了一个主动收集用户投诉的机会,并在漏洞修复和功能完善方面迅速改善应用的用户体验。然而,大量的评论和噪音词(如拼写错误的单词)增加了准确识别新出现的应用问题的难度。在本文中,我们提出了一个新颖的自动化框架IDEA,旨在基于在线评论分析有效地识别新兴的应用程序问题。我们在Google Play和苹果App Store的6款热门应用中对IDEA进行了评估,并以官方应用更新日志为依据。实验结果证明了IDEA在识别新出现的应用程序问题方面的有效性。来自工程师和产品经理的反馈显示,88.9%的人认为已识别的问题可以在实践中促进应用开发。并且,我们已经成功地将IDEA应用到腾讯的多个产品中,服务于上亿的用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online App Review Analysis for Identifying Emerging Issues
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.
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