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AI Refactoring Workflow

Change code structure while preserving observable behavior.

Introduction​

Coding agents handle broad mechanical edits such as moving modules, renaming symbols, and updating call sites. The risk is behavioral drift hidden inside a large structural diff.

This workflow establishes current behavior first, limits the transformation, and verifies equivalence after each step.

Understanding the Workflow​

Refactoring changes the internal structure of code without changing its observable behavior. A bug fix or feature belongs in a separate change because it has a different review question.

Definition

Refactoring

A change to code structure that preserves the system's observable behavior.

A characterization test records behavior that the system currently exhibits. It creates a safety net when existing tests do not cover the code being changed.

Definition

Characterization Test

A test written before refactoring to capture current behavior, including behavior whose original intent is uncertain.

Keep structural changes separate from behavior changes. This makes the diff reviewable and lets you revert the refactor without reverting a feature or fix.

Applying It in Practice​

Define the transformation and its boundary:

Extract authentication logic from UserController into AuthService.
Preserve public API signatures and error behavior.
Do not change authorization rules or response bodies.
Update callers and tests only where names or imports require it.

Ask the agent to identify affected interfaces, callers, side effects, and existing coverage. Add characterization tests before production edits when important behavior lacks coverage.

Split broad work into stages:

  1. add missing behavior coverage
  2. move or extract code without cleanup
  3. update callers and imports
  4. remove obsolete structure
  5. apply names or formatting that improve the new structure

Run relevant tests after every stage. Keep each diff small enough to compare control flow, data flow, and side-effect order with the previous version.

During review, check:

  • public and internal contracts
  • error types and timing
  • ordering of writes, events, logs, and cleanup
  • null, empty, and boundary cases
  • concurrency and resource lifetime
  • tests that changed alongside production behavior

Run the complete test suite, static analysis, and build before merge. Benchmark when the refactor touches a measured hot path. Structural intent does not guarantee unchanged performance.

Engineering Considerations​

Tests reduce risk but do not prove equivalence outside their assertions. Use type checking, static analysis, runtime traces, and targeted benchmarks where they cover different failure modes.

Mechanical codemods and language-server refactors are preferable when they can express the transformation exactly. Use an agent when the change requires repository-wide context or different edits at different call sites.

Do not let the agent “clean up nearby code” during the refactor. Record useful follow-up work as separate tasks.

Some test changes are necessary after moving modules or renaming interfaces. Review them separately and confirm that assertions did not weaken.

Scaling and Operations​

Sequence refactors that touch shared interfaces. Parallel agents updating the same callers create conflicts and make equivalence harder to review.

For large migrations, define an intermediate compatibility layer and migrate bounded groups of callers. Keep the repository buildable after each group.

Track the baseline test and benchmark results with the change. When a regression appears after merge, a standalone refactoring change is easier to revert and bisect.

Delete temporary compatibility code under an explicit follow-up criterion. Otherwise an incremental refactor can leave two permanent paths.

Next Steps​