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Why should code review and QA run while the developer performs manual testing?

Use parallel code review, QA, and developer testing to uncover different defects sooner while keeping the tested build and fixtures consistent.

Why should code review and QA run while the developer performs manual testing?

Code review, QA, and developer testing can run in parallel because they examine different aspects of a feature. This shortens the feedback cycle when the implementation is stable enough for each activity to inspect the same result.

Use different methods to inspect the feature

Code review follows the implementation and data flow. QA evaluates specified scenarios and records reproducible outcomes. Developer testing checks the experience directly, including details the developer knows are likely to be fragile.

For a task-completion feature, review might detect a missing membership check. QA might find that changes disappear after refresh. The developer might notice that the checkbox remains disabled after a failed request. These findings complement one another.

Establish a stable testing checkpoint

Identify the commit or application snapshot being reviewed. If the developer continues changing the feature while others test it, record those changes and communicate when a new build is ready.

Use separate fixtures for state-changing scenarios. Two testers completing or deleting the same task can create misleading failures. Give each tester controlled data or clearly divide the scenarios. Keep invitations in a test delivery environment so parallel checks do not send duplicate messages to real guests.

Triage findings before the next iteration

Collect reports with expected behavior, observed behavior, and the relevant version. Confirm issues, group duplicate findings, and prioritize failures that affect correctness, access, or the main user journey.

After fixes, rerun the affected checks against the updated version. Parallel work is useful only when results remain attributable and actionable. A faster review cycle should still end with a coherent decision about whether the final implementation satisfies the agreed acceptance criteria.

It is useful after a coherent implementation checkpoint exists and participants have clear assignments. Unstable inputs can create more coordination work than the parallelism saves.

One tester may complete, edit, or delete data another tester expects to remain unchanged. Separate fixtures make failures reproducible and easier to attribute.

Record the new version and tell reviewers which behavior changed. Recheck affected findings against that version rather than assuming earlier results still apply.

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