The value of code review appears when the team can explain the decision before discussing implementation. The practical scope is to review intent, risk, behavior, tests, security boundaries, and operational impact instead of formatting trivia. The central risk is that large mixed changes hide consequential decisions and exhaust reviewer attention.
Turn "done" into observable behavior: Code Review
Acceptance criteria for code review should identify the actor, starting state, action, durable result, denied path, repeated action, and recovery evidence. The interface may report success while large mixed changes hide consequential decisions and exhaust reviewer attention. The criterion therefore has to compare visible feedback with the server-enforced policy and auditable state transition.
Cover the states that change the decision: Code Review
Test ready, empty, invalid, denied, delayed, duplicate, partial, successful, and recovered states where they apply. Add a case in which access is revoked, an owner is absent, or a repeated request arrives after partial completion. Each case should say whether input is preserved, whether retry is safe, and which record a reviewer inspects. Avoid criteria such as "works" or "implemented" because two reviewers can interpret them differently.
Test authority, not visibility: Code Review
The expected behavior must hold for an allowed actor, a denied actor, a revoked role, and a direct request that bypasses the normal interface. A denial should leave protected state unchanged and produce a useful audit record without exposing secrets. The accountable actor should have only the permissions required for code review.
Attach evidence to every important claim: Code Review
Use allowed and denied tests, audit records, ownership dates, recovery notes, and redacted logs. Record the environment, configuration, and time range so another reviewer can reproduce the result. A passing test supports only the behavior it exercised; it does not prove every security, accessibility, performance, or operational claim. Monitor unowned exceptions as a release signal.
Decision map: Code Review
- Behavior. Name the owner, authoritative record, expected state, and denial behavior for this part of code review.
- Tests. Document the normal transition, one interrupted transition, and the smallest safe recovery.
- Security boundaries. Attach a reproducible test, dated result, and reviewer who accepts the remaining risk.
- Operational impact instead of formatting trivia. State the input, output, permission boundary, and removal condition before adding automation.
- Review intent. Record how repeated action behaves and which evidence distinguishes retry from duplication.
Boundary cases: Code Review
- When the recorded value for behavior changes after tests is stored, name which value wins and how the losing state is reconciled.
- If evidence for security boundaries becomes unavailable while the code review request is in progress, preserve enough context to distinguish rejection from partial completion.
- A repeated action involving operational impact instead of formatting trivia should return the existing result or expose the possible duplicate effect before retry.
- A denied change to review intent must leave authoritative state untouched and create an audit record that reveals no secret.
- Recovery should restore the smallest trustworthy state first, then verify the visible code review outcome against the maintained record.
Measure the decision, not activity: Code Review
Track unowned exceptions and denied-action accuracy. Before collecting results for code review, define each measure's population, environment, time window, and owner. Activity is useful only when it clarifies whether the protected code review outcome became safer or easier to recover.
Set the investigation threshold for code review in advance. The acceptance review should also name the permitted response, the evidence required to close the issue, and the next review date. Stop collecting code review data when it no longer distinguishes success, denial, delay, duplication, or recovery, or when it no longer changes a decision.
Sources and local proof: Code Review
These primary references document platform behavior relevant to code review. For code review, those references establish terminology and constraints; they do not verify the local implementation.
- About Code Owners
- About Pull Requests
- Reviewing Proposed Changes in a Pull Request
- What to Look For in a Code Review
- The Standard of Code Review
Any publishable code review claim still needs dated local evidence: configuration, test output, screenshots, logs, queries, or recovery results from the named product. The acceptance review should say exactly which artifact supports each important claim.
A related InMyDraft example: Code Review
InMyCitizen provides a local example of an inspectable product boundary relevant to code review. Its project catalog records this implementation detail: A civic timeline, direct messaging (citizen, support, community, and AI conversations), a document wallet, civic reports with photo and location, bills, and appointments are all wired into the same resident account.
The comparison between InMyCitizen and code review is deliberately narrow. It shows how one product makes state and evidence visible; it does not prove that every code review recommendation has been implemented. Use the InMyCitizen example to review code review, not as a substitute for testing the product in scope.
Review checklist: Code Review
- Given a valid starting state, the accountable operator with the narrowest required permission can complete the intended code review outcome.
- Invalid and unauthorized requests leave the server-enforced policy and auditable state transition unchanged.
- A repeated action does not duplicate a protected side effect.
- The team can demonstrate that it can sample the merged behavior and compare escaped defects with the original review.
- Failure and recovery produce evidence another reviewer can reproduce.
A code review decision is ready for the next stage when another accountable person can reproduce the evidence, explain the failure boundary, and perform the recovery without relying on the original author's memory.
