LadyBug: A GitHub Bot for UI-Enhanced Bug Localization in Mobile Apps
This paper introduces LadyBug, a GitHub bot that automatically localizes bugs for Android apps by combining UI interaction information with text-retrieval. LadyBug connects to an Android app’s GitHub repository, and is triggered when a bug is reported in the corresponding issue tracker. Developers can then record a reproduction trace for the bug on a device or emulator and upload the trace to LadyBug via the GitHub issue tracker. This enables LadyBug to utilize both the text from the original bug description, and UI information from the reproduction trace to accurately retrieve a ranked list of files from the project that most likely contain the reported bug.
We empirically evaluated LadyBug using an automated testing pipeline and benchmark called RedWing that contains 80 fully-localized and reproducible bug reports from 39 Android apps. Our results illustrate that LadyBug outperforms strong text-retrieval based baselines and that the utilization of GUI information leads to a substantial increase in localization accuracy. LadyBug is an open-source tool, available at https://github.com/LadyBugML/ladybug.
A video showing the capabilities of Ladybug can be viewed here: https://youtu.be/hI3tzbRK0Cw
Wed 10 SepDisplayed time zone: Auckland, Wellington change
13:30 - 15:00 | Session 3 - Debugging and RefactoringResearch Papers Track / Industry Track / Tool Demonstration Track / NIER Track at Case Room 3 260-055 Chair(s): Ashkan Sami Edinburgh Napier University | ||
13:30 15m | Boosting Redundancy-based Automated Program Repair by Fine-grained Pattern Mining Research Papers Track Jiajun Jiang Tianjin University, Fengjie Li Tianjin University, Zijie Zhao Tianjin University, Zhirui Ye Tianjin University, Mengjiao Liu Tianjin University, Bo Wang Beijing Jiaotong University, Hongyu Zhang Chongqing University, Junjie Chen Tianjin University | ||
13:45 10m | LadyBug: A GitHub Bot for UI-Enhanced Bug Localization in Mobile Apps Tool Demonstration Track Junayed Mahmud University of Central Florida, James Chen University of Toronto, Terry Achille University of Central Florida, Camilo Alvarez-Velez University of Central Florida, Darren Dean Bansil University of Central Florida, Patrick Ijieh University of Central Florida, Samar Karanch University of Central Florida, Nadeeshan De Silva William & Mary, Oscar Chaparro William & Mary, Andrian Marcus George Mason University, Kevin Moran University of Central Florida | ||
13:55 15m | Together We Are Better: LLM, IDE and Semantic Embedding to Assist Move Method Refactoring Research Papers Track Abhiram Bellur University of Colorado Boulder, Fraol Batole Tulane University, Malinda Dilhara Amazon Web Services, USA, Mohammed Raihan Ullah University of Colorado Boulder, Yaroslav Zharov JetBrains Research, Timofey Bryksin JetBrains Research, Kai Ishikawa NEC Corporation, Haifeng Chen NEC Laboratories America, Masaharu Morimoto NEC Corporation, Shota Motoura NEC Corporation, Takeo Hosomi NEC Corporation, Tien N. Nguyen University of Texas at Dallas, Hridesh Rajan Tulane University, Nikolaos Tsantalis Concordia University, Danny Dig University of Colorado Boulder, JetBrains Research | ||
14:10 10m | COB2PY - A Non-AI, Rule-Based COBOL to Python Translator Tool Demonstration Track Kowshik Reddy Challa Indian Institute of Technology, Tirupati, Sonith M V Indian Institute of Technology, Tirupati, Chiranjeevi B S Indian Institute of Technology Tirupati, Sridhar Chimalakonda Indian Institute of Technology Tirupati | ||
14:20 10m | How Does Test Code Differ From Production Code in Terms of Refactoring? An Empirical Study NIER Track Kosei Horikawa Nara Institute of Science and Technology, Yutaro Kashiwa Nara Institute of Science and Technology, Bin Lin Hangzhou Dianzi University, Kenji Fujiwara Nara Women’s University, Hajimu Iida Nara Institute of Science and Technology Pre-print | ||
14:30 10m | How Much Can a Behavior-Preserving Changeset Be Decomposed into Refactoring Operations? NIER Track Kota Someya Institute of Science Tokyo, Lei Chen Institute of Science Tokyo, Michael J. Decker Bowling Green State University, Shinpei Hayashi Institute of Science Tokyo DOI Pre-print | ||
14:40 15m | Governance Matters: Lessons from Restructuring the data.table OSS Project Industry Track Pedro Arantes RESHAPE LAB, Northern Arizona University, USA, Doris Amoakohene Northern Arizona University, Toby Hocking Université de Sherbrooke, Marco Gerosa Northern Arizona University, Igor Steinmacher RESHAPE LAB, Northern Arizona University, USA | ||