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Keep code reviews fast in trunk-based development by reviewing small, self-contained changes as they are ready to integrate, rather than letting them collect in an approval queue. Pairing can provide immediate peer review; when a separate review is needed, ask a teammate to review synchronously at commit-ready time. Run fast automated tests after each trunk commit so the team gets prompt feedback and can keep the shared branch healthy.
Why review speed matters in trunk-based development
Trunk-based development relies on frequent integration and small batches. A small change is easier to understand, review, test, and move toward production than a large change accumulated while waiting for approval. DORA identifies heavyweight multi-approval processes and asynchronous review queues as common pitfalls because they can encourage developers to accumulate changes and make integration slower. DORA’s trunk-based development guidance recommends synchronous review when extra review is required: ask a teammate to review when the developer is ready to commit.
Review still matters; speed does not mean skipping judgment. Pair programming includes a second-person review, and a separate review can focus on material correctness, maintainability, and code health without turning every preference into a blocking request.
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Break work into reviewable changes
Slice work into small, self-contained changes that can be integrated independently. A feature does not have to be finished before useful parts can reach trunk: use incremental changes so each batch is understandable and testable. This avoids the large, difficult-to-reason-about review that can result when work waits until an entire feature is complete.
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Review when the change is ready
Pairing or direct collaboration gives the author feedback while the code is being written. If your team requires a separate reviewer, request that review when the change is commit-ready rather than placing it in a long asynchronous queue and switching to unrelated work. A short-lived branch or pull request can still be part of the workflow; the important point is to keep review and integration feedback timely.
Use review to improve code health, not seek perfection
Google Engineering Practices describes the primary purpose of review as ensuring that overall code health improves over time. Its guidance also says reviewers should seek continuous improvement rather than perfection. Apply that distinction by separating changes required for correctness or the team’s standard from non-blocking educational suggestions. When more than one approach is sound, accept the author’s reasonable choice instead of blocking integration over preference. Google’s Standard of Code Review explains this balance.
How often should changes reach trunk?
DORA’s trunk-based development guidance describes three or fewer active branches, merging to trunk at least once a day, and avoiding code freezes or integration phases as practice targets. DORA associates these practices with stronger delivery and operational performance in analyses of 2016 and 2017 data; they are not a guarantee that every organization will get the same result. Use them as signals to examine how work flows, not as a substitute for judging your team’s context. DORA’s guidance provides the context for these targets.
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Automated tests and human review do complementary jobs: tests provide repeatable feedback on behavior, while reviewers bring engineering judgment about correctness, maintainability, and code health. A green test suite does not replace review, and an approval count does not establish that a change is sound.
DORA’s continuous integration guidance says tests should run in no more than a few minutes, with about 10 minutes as an upper limit cited from DORA research. Keep the feedback loop short enough that a failing trunk commit is actionable. If CI fails, fix the problem promptly; if it cannot be fixed in a few minutes, DORA advises reverting the change rather than leaving the shared branch broken. DORA’s continuous integration guidance covers this practice.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to tell whether review is slowing integration
Track active branch count, how often changes merge, whether the team has code freezes or integration phases, and how long reviews wait for approval. Look for patterns that point to oversized changes or a queue, then adjust the workflow—for example, slice work more finely or arrange synchronous review. Treat these measures as diagnostic signals for improvement, not as metrics that by themselves guarantee delivery performance.
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