# Automated Code Fix Suggestions for Accessibility Issues in Mobile Apps

arXiv: https://arxiv.org/abs/2408.03827 · HTML: https://mlsanity.com/paper/2408.03827/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 49 references that are in the map.
- First posted on arXiv 7 Aug 2024.

## Builds on (most cited first, 15 of 15)

- [Reflexion: Language Agents with Verbal Reinforcement Learning](https://mlsanity.com/paper/2303.11366/) (2023)
- [SWE-bench: Can Language Models Resolve Real-World GitHub Issues?](https://mlsanity.com/paper/2310.06770/) (2023)
- [SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://mlsanity.com/paper/2405.15793/) (2024)
- [AutoCodeRover: Autonomous Program Improvement](https://mlsanity.com/paper/2404.05427/) (2024)
- [RepairAgent: An Autonomous, LLM-Based Agent for Program Repair](https://mlsanity.com/paper/2403.17134/) (2024)
- [MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution](https://mlsanity.com/paper/2403.17927/) (2024)
- [CodeR: Issue Resolving with Multi-Agent and Task Graphs](https://mlsanity.com/paper/2406.01304/) (2024)
- [Screen Recognition: Creating Accessibility Metadata for Mobile Applications from Pixels](https://mlsanity.com/paper/2101.04893/) (2021)
- [Applying CodeBERT for Automated Program Repair of Java Simple Bugs](https://mlsanity.com/paper/2103.11626/) (2021)
- [RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair](https://mlsanity.com/paper/2309.06057/) (2023)
- [A Systematic Literature Review on Large Language Models for Automated Program Repair](https://mlsanity.com/paper/2405.01466/) (2024)
- [Accessibility in Software Practice: A Practitioner's Perspective](https://mlsanity.com/paper/2103.08778/) (2021)
- [Towards Automated Accessibility Report Generation for Mobile Apps](https://mlsanity.com/paper/2310.00091/) (2023)
- [Automated and Context-Aware Repair of Color-Related Accessibility Issues for Android Apps](https://mlsanity.com/paper/2308.09029/) (2023)
- [ACCESS: Prompt Engineering for Automated Web Accessibility Violation Corrections](https://mlsanity.com/paper/2401.16450/) (2024)

## Built on by (most cited first, 2 of 2)

- [Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale](https://mlsanity.com/paper/2511.08475/) (2025)
- [WebAccessVL: Violation-Aware VLM for Web Accessibility](https://mlsanity.com/paper/2602.03850/) (2025)

## Abstract (arXiv)

Accessibility is crucial for inclusive app usability, yet developers often struggle to identify and fix app accessibility issues due to a lack of awareness, expertise, and inadequate tools. Current accessibility testing tools can identify accessibility issues but may not always provide guidance on how to address them. We introduce FixAlly, an automated tool designed to suggest source code fixes for accessibility issues detected by automated accessibility scanners. FixAlly employs a multi-agent LLM architecture to generate fix strategies, localize issues within the source code, and propose code modification suggestions to fix the accessibility issue. Our empirical study demonstrates FixAlly's capability in suggesting fixes that resolve issues found by accessibility scanners -- with an effectiveness of 77% in generating plausible fix suggestions -- and our survey of 12 iOS developers finds they would be willing to accept 69.4% of evaluated fix suggestions.