This paper introduces BURT, a web-based chatbot for interactive reporting of Android app bugs. BURT is designed to assist Android app end-users in reporting high-quality defect information using an interactive interface. BURT guides the users in reporting essential bug report elements, i.e., the observed behavior, expected behavior, and the steps to reproduce the bug. It verifies the quality of the text written by the user and provides instant feedback. In addition, BURT provides graphical suggestions that the users can choose as alternatives to textual descriptions. We empirically evaluated BURT, asking end-users to report bugs from six Android apps. The reporters found that BURT’s guidance and automated suggestions and clarifications are useful and BURT is easy to use. BURT is an open-source tool, available at github.com/sea-lab-wm/burt/tree/tool-demo. A video showing the full capabilities of BURT can be found at https://youtu.be/SyfOXpHYGRo.
Fri 19 MayDisplayed time zone: Hobart change
13:45 - 15:15 | Issue reporting and reproductionTechnical Track / DEMO - Demonstrations at Meeting Room 110 Chair(s): Daniel Russo Department of Computer Science, Aalborg University | ||
13:45 15mTalk | Incident-aware Duplicate Ticket Aggregation for Cloud Systems Technical Track Jinyang Liu The Chinese University of Hong Kong, Shilin He Microsoft Research, Zhuangbin Chen Chinese University of Hong Kong, China, Liqun Li Microsoft Research, Yu Kang Microsoft Research, Xu Zhang Microsoft Research, Pinjia He Chinese University of Hong Kong at Shenzhen, Hongyu Zhang The University of Newcastle, Qingwei Lin Microsoft Research, Zhangwei Xu Microsoft Azure, Saravan Rajmohan Microsoft 365, Dongmei Zhang Microsoft Research, Michael Lyu The Chinese University of Hong Kong | ||
14:00 15mTalk | Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction Technical Track Pre-print | ||
14:15 15mTalk | On the Reproducibility of Software Defect Datasets Technical Track | ||
14:30 15mTalk | Context-aware Bug Reproduction for Mobile Apps Technical Track Yuchao Huang , Junjie Wang Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Zhe Liu Institute of Software, Chinese Academy of Sciences, Song Wang York University, Chunyang Chen Monash University, Mingyang Li Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Qing Wang Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences | ||
14:45 15mTalk | Read It, Don't Watch It: Captioning Bug Recordings Automatically Technical Track Sidong Feng Monash University, Mulong Xie Australian National University, Yinxing Xue University of Science and Technology of China, Chunyang Chen Monash University Pre-print | ||
15:00 7mTalk | BURT: A Chatbot for Interactive Bug Reporting DEMO - Demonstrations Yang Song College of William and Mary, Junayed Mahmud George Mason University, Nadeeshan De Silva William & Mary, Ying Zhou University of Texas at Dallas, Oscar Chaparro College of William and Mary, Kevin Moran George Mason University, Andrian Marcus University of Texas at Dallas, Denys Poshyvanyk College of William and Mary | ||