GitHub Code Quality: Agentic Autofix for Backlog Experiences [Public Preview]
- Langage dominant
- Aucune donnée de langage
- Étoiles
- 8.9k
- Forks
- 1.8k
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
### Value Prop
GitHub Code Quality now brings the full power of agentic AI to help you tackle your existing code quality backlog — not just new findings. With Agentic Autofix for Backlog, Copilot autonomously generates high-quality, validated fixes for standard code quality findings already present in your codebase. You can select multiple findings at once and remediate them in a single action, dramatically reducing the manual effort required to improve code health at scale. This means your team spends less time triaging and hand-fixing known issues and more time shipping new features.
### Expected Outcome
Today, addressing a backlog of code quality findings is tedious and time-consuming — developers must manually review each finding, write a fix, and validate it, one at a time. We're building Agentic Autofix for Backlog so that teams can systematically and efficiently clean up existing technical debt. By enabling AI-driven, bulk remediation of code quality issues, we expect to significantly reduce the time-to-fix for backlog findings, increase the rate at which codebases reach and maintain a healthy quality bar, and lower the barrier to adopting code quality scanning — since customers no longer need to dread the initial wave of pre-existing findings.
Guide de contribution
Ouvrir le guide de contribution
Évaluation
Cette issue n'a pas encore été évaluée.