automate-repair

Automating code review and testing involves running an iterative repair loop that applies targeted fixes to a repository until tests pass. This minimizes patch size, prioritizes impactful failing signals, and re-runs tests after patches to converge to a green state.

An automated repair loop is a bounded cycle of code review, testing, and targeted fixes applied to a repository. It uses evidence-driven iterations to run tests in fast, CI, or full modes, applying minimal patches until tests converge to a green state.

Running iterative test-fix cycles requires applying bounded, evidence-driven iterations that prioritize the most impactful failing test signal. The agent applies minimal patches to the codebase, re-runs failing tests after each patch, and generates structured reports for stakeholders.

Yes, automated repair loops support running tests in fast, CI, and full modes. This allows the repair process to reconcile diffs or codebases efficiently by selecting the appropriate test scope while applying minimal, auditable fixes during each iteration.

Yes, the automated repair loop enforces bounded iterations to prevent infinite cycles. If tests still fail after reaching the iteration limit, it stops and provides structured repair-loop reporting that documents commands, applied patches, and remaining risks for stakeholders.

Using an automated repair loop instead of manually patching failing tests reduces wasted cycles and surfaces blockers early. It enforces evidence-driven iteration and structured reporting, ensuring fixes are minimal, preserve contracts, and are fully auditable for stakeholders.