一句话：提出并评估任务型聊天机器人 Burt，引导终端用户交互式报告 Android 应用缺陷并即时验证质量。
许多缺陷由用户手动报告，尤其是 UI 可见缺陷；现有报告系统多依赖模板或表单，难以向经验不足的终端用户提供有效引导、具体反馈和质量验证，导致低质量报告增加开发者负担。本文提出面向终端用户的交互式缺陷报告系统 Burt，以任务型聊天机器人形式，引导用户提供观察行为、期望行为与复现步骤，并即时进行质量验证和图形化建议。作者实现 Android 版本，并开展用户实证评估：用户在六个 Android 应用上报告了 12 个缺陷。结果表明 Burt 的引导与自动建议/澄清有用且易用，其报告信息质量高于基于模板的系统；用户反馈还提出支持多样措辞和改进质量验证等方向。
Many software bugs are reported manually, particularly bugs that manifest themselves visually in the user interface. End-users typically report these bugs via app reviewing websites, issue trackers, or in-app built-in bug reporting tools, if available. While these systems have various features that facilitate bug reporting (e.g., textual templates or forms), they often provide limited guidance, concrete feedback, or quality verification to end-users, who are often inexperienced at reporting bugs and submit low-quality bug reports that lead to excessive developer effort in bug report management tasks. We propose an interactive bug reporting system for end-users (Burt), implemented as a task-oriented chatbot. Unlike existing bug reporting systems, Burt provides guided reporting of essential bug report elements (i.e., the observed behavior, expected behavior, and steps to reproduce the bug), instant quality verification, and graphical suggestions for these elements. We implemented a version of Burt for Android and conducted an empirical evaluation study with end-users, who reported 12 bugs from six Android apps studied in prior work. The reporters found that Burt’s guidance and automated suggestions/clarifications are useful and Burt is easy to use. We found that Burt reports contain higher-quality information than reports collected via a template-based bug reporting system. Improvements to Burt, informed by the reporters, include support for various wordings to describe bug report elements and improved quality verification. Our work marks an important paradigm shift from static to interactive bug reporting for end-users.
@inproceedings{paperbot6993,
title = {Toward interactive bug reporting for (android app) end-users},
author = {Yang Song and Junayed Mahmud and Ying Zhou and Oscar Chaparro and Kevin Moran and Andrian Marcus and Denys Poshyvanyk},
booktitle = {FSE},
year = {2022},
doi = {10.1145/3540250.3549131}
}