# Auto-completing Bug Reports for Android Applications

arXiv: https://arxiv.org/abs/1705.04016 · HTML: https://mlsanity.com/paper/1705.04016/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 May 2017.

## Built on by (most cited first, 7 of 7)

- [DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning](https://mlsanity.com/paper/2108.08041/) (2021)
- [Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews](https://mlsanity.com/paper/2104.05861/) (2021)
- [An Empirical Investigation into the Use of Image Captioning for Automated Software Documentation](https://mlsanity.com/paper/2301.01224/) (2023)
- [Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation](https://mlsanity.com/paper/2504.18804/) (2025)
- [Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Steps](https://mlsanity.com/paper/2502.04251/) (2025)
- [ImproBR: Bug Report Improver Using LLMs](https://mlsanity.com/paper/2604.26142/) (2026)
- [Writing Bug Reports for Software Repair Agents: What Information Matters Most?](https://mlsanity.com/paper/2607.09553/) (2026)

## Abstract (arXiv)

The modern software development landscape has seen a shift in focus toward mobile applications as tablets and smartphones near ubiquitous adoption. Due to this trend, the complexity of these apps has been increasing, making development and maintenance challenging. Additionally, current bug tracking systems are not able to effectively support construction of reports with actionable information that directly lead to a bug's resolution. To address the need for an improved reporting system, we introduce a novel solution, called FUSION, that helps users auto complete reproduction steps in bug reports for mobile apps. FUSION links user provided information to program artifacts extracted through static and dynamic analysis performed before testing or release. The approach that FUSION employs is generalizable to other current mobile software platforms, and constitutes a new method by which off device bug reporting can be conducted for mobile software projects. In a study involving 28 participants we applied FUSION to support the maintenance tasks of reporting and reproducing defects from 15 real world bugs found in 14 open source Android apps while qualitatively and qualitatively measuring the user experience of the system. Our results demonstrate that FUSION both effectively facilitates reporting and allows for more reliable reproduction of bugs from reports compared to traditional issue tracking systems by presenting more detailed contextual app information.