Toward interactive bug reporting for (android app) end-users
Yang Song, Junayed Mahmud, Ying Zhou, Oscar Chaparro, Kevin Moran, Andrian Marcus, Denys Poshyvanyk
摘要
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.
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引用它的顶会 Paper7
- Prompting Is All You Need: Automated Android Bug Replay with Large Language ModelsSidong Feng, Chunyang ChenICSE 2024 · 被引用 143 次
- Feedback-Driven Automated Whole Bug Report Reproduction for Android AppsDingbang Wang, Yu Zhao, Sidong Feng, Zhaoxu Zhang 等ISSTA 2024 · 被引用 16 次
- Automatically Reproducing Android Bug Reports using Natural Language Processing and Reinforcement LearningZhaoxu Zhang, Robert Winn, Yu Zhao, Tingting Yu 等ISSTA 2023 · 被引用 14 次
- Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug ReportsYanfu Yan, Nathan Cooper, Oscar Chaparro, Kevin Moran 等ICSE 2024 · 被引用 7 次
- Mobile Bug Report Reproduction via Global Search on the App UI ModelZhaoxu Zhang, Fazle Mohammed Tawsif, Komei Ryu, Tingting Yu 等FSE 2024 · 被引用 4 次
它引用的顶会 Paper3
- Translating video recordings of mobile app usages into replayable scenariosCarlos Bernal-Cárdenas, Nathan Cooper, Kevin Moran, Oscar Chaparro 等ICSE 2020 · 被引用 61 次
- Automated classification of actions in bug reports of mobile appsHui Liu, Mingzhu Shen, Jiahao Jin, Yanjie JiangISSTA 2020 · 被引用 21 次
- It Takes Two to TANGO: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug ReportsNathan Cooper, Carlos Bernal-Cárdenas, Oscar Chaparro, Kevin Moran 等ICSE 2021 · 被引用 2 次
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