# GIFdroid: Automated Replay of Visual Bug Reports for Android Apps

arXiv: https://arxiv.org/abs/2112.04128 · HTML: https://mlsanity.com/paper/2112.04128/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Dec 2021.

## Built on by (most cited first, 5 of 5)

- [Psychologically-Inspired, Unsupervised Inference of Perceptual Groups of GUI Widgets from GUI Images](https://mlsanity.com/paper/2206.10352/) (2022)
- [Agent for User: Testing Multi-User Interactive Features in TikTok](https://mlsanity.com/paper/2504.15474/) (2025)
- [Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug Reports](https://mlsanity.com/paper/2407.08610/) (2024)
- [Breaking Single-Tester Limits: Multi-Agent LLMs for Multi-User Feature Testing](https://mlsanity.com/paper/2506.17539/) (2025)
- [GUISpector: An MLLM Agent Framework for Automated Verification of Natural Language Requirements in GUI Prototypes](https://mlsanity.com/paper/2510.04791/) (2025)

## Abstract (arXiv)

Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using software. However, it is difficult for non-technical users to write clear descriptions about the bug occurrence. Therefore, more and more users begin to record the screen for reporting bugs as it is easy to be created and contains detailed procedures triggering the bug. But it is still tedious and time-consuming for developers to reproduce the bug due to the length and unclear actions within the recording. To overcome these issues, we propose GIFdroid, a light-weight approach to automatically replay the execution trace from visual bug reports. GIFdroid adopts image processing techniques to extract the keyframes from the recording, map them to states in GUI Transitions Graph, and generate the execution trace of those states to trigger the bug. Our automated experiments and user study demonstrate its accuracy, efficiency, and usefulness of the approach.