You can make a solo codebase more dependable with a repeatable self-review and automated checks, but neither is independent peer review. Use a small diff and a checklist for human judgment, run tests and static checks on every change, and add security testing in proportion to the project’s risks. For consequential or uncertain changes, seek another qualified perspective when you can.
What a solo review can—and cannot—do
Google’s engineering guidance defines code review as examination of code by someone other than its author. Reading your own diff is still valuable, but it is self-review: you bring the same assumptions and context that shaped the change. A checklist can make that inspection more systematic; it cannot supply an independent perspective. Google’s code review guidance makes that distinction explicit.
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Automation helps with a different part of the problem. Tests, static analysis, and security checks can be repeated consistently and catch classes of defects without relying on another person being available. They do not establish that the design is suitable, that every relevant behavior was tested, or that the software is correct. NIST recommends multiple verification techniques rather than treating any one check as comprehensive. NIST IR 8397, published in October 2021, says its recommendations do not address the totality of software verification.
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1. Keep the change inspectable
Use a commit, pull request, or equivalent diff as a review surface, even if you are the only developer. Smaller changes are easier to compare with their stated purpose and make it easier to spot unrelated edits. Before integrating a change, read the diff from top to bottom rather than relying only on what you remember changing.
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2. Check the change against a short list
Google identifies design, functionality, complexity, test quality, naming, comments, style, and relevant documentation as review dimensions. Adapt those questions for self-review:
- Design: Does this fit the project’s structure, and is there a simpler approach?
- Behavior: Does the code do what the change is meant to do, including relevant edge cases and failure paths?
- Complexity: Can any logic or dependency be removed without losing needed behavior?
- Tests: Do the tests exercise the important behavior, not just execute the changed lines?
- Clarity: Are names, comments, formatting, and documentation accurate and useful?
These questions apply Google’s review dimensions to a solo workflow; they do not turn self-review into peer review.
3. Run the project’s ordinary checks before integrating
Run the automated test suite and the project’s configured static checks consistently, ideally as part of the same routine for every change. NIST recommends automated testing to make verification more consistent and reduce human effort, and static code scanning to find common bugs. A passing run means those checks did not report a problem under their configuration; it does not show that untested behavior is sound.
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Do not treat a failing check as noise or leave an important design concern unresolved simply because the change appears small. Investigate the cause, fix the change, or pause integration. Keep a practical way to revert or correct a change; LLVM’s policy describes reverting as a way to make room for design discussion when concerns arise. LLVM’s code-review policy reflects its own project practice, not a universal rule for every solo repository.
Add security checks according to the project’s risk
NIST IR 8397 recommends a broad set of verification methods. They are options to adapt to the software and its exposure, not a requirement that every small project install every tool.
- Think through threats: Identify sensitive data, trust boundaries, and ways the software could be misused before choosing checks.
- Look for secrets: Use heuristic checks for hardcoded credentials and investigate any finding rather than assuming a clean scan is proof none exist.
- Use built-in protections: Check that the platform and frameworks’ available security features are enabled and used appropriately.
- Test behavior from the outside and inside: Black-box tests check observable behavior; structural tests examine internal properties. Choose those that fit the risk and architecture.
- Test unusual inputs: Fuzzing can help explore unexpected inputs and edge cases, especially where parsing or input handling matters.
- Scan web applications where applicable: Use a web-application scanner when the project’s form and exposure make that relevant.
- Inspect what you include: Consider libraries, packages, and services incorporated into the software, not only code you wrote yourself.
- Use historical tests when useful: Tests based on past failures can guard against regressions in areas that have caused problems before.
NIST’s list is guidance for tailoring verification, not evidence that a particular combination guarantees security.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use coverage as a map, not a verdict
A coverage report can point to code that tests do not exercise or to areas where coverage has declined. That makes it useful for deciding where to add or improve tests. Coverage is a measure of exercised code, not whether the tests assert the right outcomes or whether the software is correct.
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When another reviewer is worth seeking
Ask another qualified maintainer or community member to review consequential changes, unfamiliar security-sensitive work, or designs you are unsure about, when that option is available. A second person can bring independent judgment and may notice assumptions the author missed. LLVM requests review for significant changes under its own project policy; that is an example of one project’s process, not a universal mandate for solo developers.
Self-review and automation can improve consistency, expose defects, and make changes easier to maintain. They cannot reproduce the independence of another reviewer, and no test count, coverage percentage, lint result, or automated review proves correctness.
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