iterate

Automating iterative code improvements requires a deterministic loop that applies one atomic change at a time, verifies the outcome against a baseline metric, and commits or reverts the result. This approach handles tasks like reducing lint warnings or increasing test coverage while maintaining traceable history.

Atomic change rollback is a mechanism that reverts a single modification if verification fails, preventing codebase drift. By isolating each change, the system preserves previously stacked progress and ensures only validated improvements are kept in the final history.

To set up a verification loop for test coverage, you provide your goal, baseline measurement, and verify commands. The system then iteratively applies targeted changes, checks the metric, and keeps or discards each modification based on the verification result.

Automated iterative improvement works for performance optimization tasks by applying the same baseline, change, verify, and guard cycle. It makes small reversible modifications to targeted modules, measures the performance metric, and reverts any change that degrades results.

The deterministic loop requires clearly quantifiable goals, explicit baseline metrics, and reliable verification commands. It is limited by the quality of your guard checks and may not suit subjective refactoring tasks that lack measurable success criteria or automated validation.

Guard checks can be integrated into the automated refactoring loop to prevent bad commits. The workflow respects these guard commands during each iteration, ensuring that any change violating the constraints is automatically reverted before moving to the next cycle.