Epic: Validate and remediate AI-audited release-impact findings
Nobody has claimed this yet.
- Dominant language
- Java
- Stars
- 970
- Forks
- 486
- Avg merge
- 3d 33m
- Merged PRs (30d)
- 170
Description
Context
This epic tracks the larger findings from a local audit generated by Claude/Opus 4.8 multi-agent audit on main at beb3cce7f5.
Caveat
These findings were AI-found by Claude and should receive secondary human validation for correctness, severity, and product value before implementation. The audit report says candidates were adversarially re-judged, but that is not a substitute for maintainer review or reproduction.
Tracking
The release-impact findings are tracked as GitHub sub-issues on this epic.
Notes
The scope intentionally focuses on the report's larger release-impact items: Tier 1 backend issues and distinct frontend/UVE/analytics findings. Tier 2 quick wins and modernization roadmap items can be split into separate epics if maintainers want those tracked independently.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the audit context at commit beb3cce7f5 and the GitHub sub-issues, since no source files or tests are named here. Validate each finding with maintainers before implementation, and consider the epic complete when accepted release-impact findings have tracked remediations or documented decisions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java
- Domain
- backend, frontend, release
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100