  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.
