Software Engineering · Cluster
Code Review
Defect detection and knowledge transfer.
- 01 What a Unified Diff Hunk Actually Encodes How the hunk header, the minus and plus blocks, and the context window are produced, and which parts of a change a line-oriented diff cannot represent at all.
- 02 Diff Algorithm Choice and the Noise It Adds to a Review Myers, histogram, and patience strategies produce different edit scripts for the same two files, and the choice determines whether a reviewer sees structure or a wall of moved lines.
- 03 Splitting a Change into Units That Can Be Reviewed Independently Why the unit of review should be a reversible intent rather than a file or a commit, how mixed changes produce review deadlock, and what splitting costs in history.
- 04 Which Defects a Diff Reader Can Actually Detect Local defects that live inside the changed lines are findable by reading, while invariant violations, races, and resource-lifecycle bugs mostly are not, and the difference sets the ceiling on review.
- 05 The Semantics of a Code Review Approval An approval is a statement with an unstated scope: which revision it applies to, which claims it vouches for, and how it goes stale when the change moves underneath it.
- 06 Reviewing Tests in the Same Diff as the Code A test written beside its implementation tends to assert what the code does rather than what it should do, and the diff is where that circularity becomes visible.
- 07 Stacked Changes and the Mechanics of Incremental Review How a chain of dependent changes lets each diff be read against its own base, what happens when the bottom of the stack changes, and why restacking is the expensive step.
- 08 Merge Queues and What Speculative Testing Actually Proves How a queue serialises candidate merges, tests each against the current tip rather than its own base, and why batching candidates changes the meaning of a green result.
- 09 Static Analysis Findings as a Review Signal What a linter or analyser can prove about a diff, how findings are ranked so that reviewers see the few that matter, and why suppression is the mechanism that decides whether any of it works.
- 10 Review Metrics and the Confounders That Invert Them Why latency, comment density, and approval counts measure queueing and authorship as much as review quality, and which quantities remain interpretable under those confounders.