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Review AI-generated Rust as an untrusted change, not as an authority. Start by reconstructing the requested behavior and the surrounding API contract, then use the compiler, tests, Clippy, and (when applicable) Miri as separate signals. Rust can prove many properties of safe code, but it cannot prove that an implementation meets your specification, and it cannot verify the programmer’s safety contract inside unsafe operations.
What a complete review must establish
A good review answers two different questions:
- Safety: Does the code preserve Rust’s memory, thread, and aliasing requirements, especially at every
unsafeboundary? - Correctness: Does it implement the requested behavior, API contract, failure semantics, compatibility requirements, and project conventions?
These questions overlap but are not interchangeable. A program can compile without violating memory safety and still return the wrong value, mishandle an error, use the wrong ordering, leak a resource, or break a public contract. Conversely, a test can pass while an unexecuted unsafe path remains unsound.
The compiler is therefore a filter, not a verdict. Treat a generated patch like code from a contributor who may have made plausible but undocumented assumptions. Your job is to identify those assumptions, verify them against the project, and either prove them or remove the code that depends on them.
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1. Recover the intended behavior before reading line by line
Begin with the issue, request, design note, or acceptance criteria that motivated the change. Write down the observable behavior the patch must provide before judging its implementation. This prevents an attractive implementation from redefining the task.
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Turn the request into reviewable obligations
- What inputs are valid, and what must happen for empty, malformed, extreme, or duplicate inputs?
- What state may change, and what state must remain untouched when an operation fails?
- Which ordering, atomicity, timeout, retry, or concurrency properties are required?
- What errors must be returned, and which errors may be propagated, translated, or retried?
- Does the change need to preserve a public API, serialized format, feature flag, or minimum supported Rust version?
- Are side effects such as file writes, network calls, logging, metrics, or callbacks required, forbidden, or conditional?
Compare every new branch, allocation, mutation, dependency, and side effect with those obligations. AI-generated code often adds “helpful” behavior—fallback values, retries, broad error conversion, or silent filtering—that was never requested.
Make assumptions explicit
Record assumptions about ownership, lifetimes, initialization, thread use, numeric ranges, encoding, and failure recovery. An assumption is not a proof. It becomes reviewable only when you can point to a caller guarantee, a validation check, a type invariant, or a documented contract that establishes it.
2. Read the project context before the generated implementation
Open neighboring modules, public interfaces, trait definitions, and tests before deciding whether a new function is correct. A locally reasonable function can violate conventions that are invisible in the prompt.
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- Read callers and callees to see what values and error variants actually flow through the API.
- Check trait contracts, including requirements implied by methods that are not part of the generated diff.
- Look for existing helpers that already validate inputs, normalize paths, acquire locks, or convert errors.
- Review feature flags and conditional compilation. Code compiled only under a feature may have no ordinary build coverage.
- Confirm the crate edition, supported Rust versions, target platforms, and project policy for warnings and lints.
- Check whether generated code introduces a dependency, permission, environment variable, file access, or network access that the task did not require.
Compare naming, error types, logging levels, ownership patterns, and module boundaries with established code. Consistency is not merely stylistic: a project’s conventions often encode operational or compatibility guarantees.
3. Compile, then interpret what compilation does—and does not—mean
Run the project’s normal build or check command first, using the same features and targets used by continuous integration. For a typical crate, that may include:
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cargo check
cargo test
cargo build --all-features
Use the project’s documented commands when they differ. A successful check confirms that the selected code satisfies type, lifetime, visibility, trait, and borrow-checking rules. It does not confirm the intended algorithm, correct error semantics, absence of deadlocks, or soundness of an unsafe assertion.
Read diagnostics as evidence
Do not stop at the first green command. Inspect warnings, feature-specific failures, and platform-specific configurations. A warning can reveal an unreachable branch, an ignored result, an accidental clone, or a compatibility problem. Conversely, suppressing a warning merely to obtain a clean build removes information; first determine whether the warning exposes a real defect.
Rust’s safe type system cannot check the programmer’s obligations for raw pointers, unsafe calls, mutable statics, unsafe trait implementations, or union fields. Compilation of such code means only that the compiler accepted the surrounding types and syntax.
4. Test the specification, not just the happy path
Run the existing unit, integration, documentation, and feature-gated tests that cover the changed behavior. Then add focused tests for requirements that the old suite does not express. Rust’s memory-safety guarantees do not establish logic correctness; tests are still needed to show that the program produces the required results.
Cover boundaries and invalid inputs
- Empty collections, zero and one-element cases, maximum and minimum numeric values, and large realistic inputs.
- Malformed text, invalid encodings, missing fields, duplicate identifiers, and unexpected enum variants.
- Permission failures, unavailable resources, timeouts, cancellation, partial writes, and downstream errors.
- Repeated calls, retries, concurrent calls, and calls after a previous failure.
- Ordering guarantees and deterministic output when the implementation uses hash maps, channels, tasks, or parallel work.
Test the negative contract
For each operation, assert what must not happen on failure: state should not be partially mutated, a lock should not remain held, a temporary file should not be left behind, and sensitive data should not be logged. If the API promises a particular error type or status, assert that exact contract rather than merely checking that an error occurred.
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Protect against regressions
Turn every discovered bug into a minimal regression test. Prefer a test that fails for the original defect and passes for the corrected behavior. For public APIs, include compile-time or integration coverage for the way downstream callers use the interface. If behavior depends on a feature, target, or edition, run that matrix explicitly instead of assuming the default build represents it.
5. Run Clippy and review each suggestion
The standard invocation is:
cargo clippy
Use the project’s feature and target options when needed. Clippy’s default clippy::all collection includes correctness, suspicious, style, complexity, and performance lints. Treat a diagnostic as a review lead, not an automatic edit.
Understand the lint groups
| Group | Default status | How to review it |
|---|---|---|
clippy::correctness |
Deny-by-default | Investigate immediately. These lints describe code Clippy considers outright wrong or useless. |
| Suspicious lints | Included in normal checks | Look for likely mistakes, unintended behavior, or a construct that does not do what the author expects. |
| Style, complexity, and performance lints | Included in normal checks | Apply when the suggested change preserves the contract and improves clarity or cost; do not trade away readability for a cosmetic warning. |
clippy::pedantic |
Allow-by-default | Enable selectively. The documentation notes that these checks can produce intentional false positives. |
The Clippy documentation describes clippy::correctness as the only lint group whose lints are deny-by-default and abort compilation when triggered. That makes a correctness finding especially important, but it still requires understanding the specific code and configuration.
Handle suppressions narrowly
AI-generated code may include an #[allow(...)] attribute or apply an automatic fix without explaining why. Verify that the diagnostic is irrelevant in this context before keeping a suppression. Prefer the narrowest scope—an expression, item, or module rather than the entire crate—and add a comment that explains the contract or intentional trade-off. Never suppress a warning simply because it makes the output look clean.
Some projects deny warnings in continuous integration. Follow the existing policy rather than adding a broad warning denial to this patch. A global setting can turn unrelated, platform-specific, or newly introduced warnings into failures and obscure the issue under review.
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6. Audit every unsafe boundary manually
Search the complete diff, not only lines containing the word unsafe. Include unsafe functions and trait implementations, raw pointers, unions, mutable statics, foreign-function interfaces, and attributes that affect safety or linkage. Rust’s five explicitly unsafe capabilities are:
- Dereferencing a raw pointer.
- Calling an unsafe function or method.
- Accessing or modifying a mutable static.
- Implementing an unsafe trait.
- Accessing a union field.
For each operation, write down the exact safety contract and the code that establishes it. “This pointer came from the caller” or “the slice is probably initialized” is not an argument.
Check the required invariants
- Validity: The pointer or reference points to an object of the required type, not freed or otherwise invalid storage.
- Alignment: The address meets the alignment requirement of the type being accessed.
- Initialization: Every read observes initialized bytes, including partially initialized buffers and union fields.
- Bounds: Pointer arithmetic and indexing remain within the allocated object and use the correct length.
- Aliasing: No simultaneous references or raw accesses violate the exclusivity rules assumed by the operation.
- Lifetime and ownership: The object remains alive for every use, and ownership is not duplicated or dropped incorrectly.
- Synchronization: Shared mutable state is protected by the required lock, atomic ordering, or external protocol on every path.
- FFI compatibility: Layout, calling convention, nullability, ownership, error values, and thread assumptions match the foreign API.
Trace every reachable path
Verify the invariant on success, early return, error conversion, cancellation, panic, and retry paths. An initialization check that occurs only in the common branch does not protect a later error branch. A lock acquired before an unsafe call must still be released or guarded if that call can unwind or return an error.
Keep the unsafe region minimal
Move validation and ordinary computation into safe code, then isolate only the operation that truly requires unsafe. The Rust Book gives practical advice: “Keep unsafe blocks small; you’ll be thankful later when you investigate memory bugs.” A small block makes the proof obligation visible and limits the code that must be re-audited after future edits.
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Require proof-oriented comments
A useful safety comment states the preconditions, where they come from, and why the operation preserves them. A comment that only restates “cast pointer and dereference” adds no evidence. If the proof depends on a caller promise, document that promise at the API boundary and test the validation that enforces it where possible.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Account for the crate edition
Edition settings change how diagnostics guide unsafe review. The unsafe_op_in_unsafe_fn lint is enabled by default in Edition 2024 and allowed by default in earlier editions. In a 2024 crate, an unsafe operation inside an unsafe fn generally needs an explicit unsafe block, making the exact operation and its justification easier to identify.
Do not infer the edition from the syntax of a generated file. Check the crate’s manifest and workspace configuration. When reviewing a patch that changes the edition or moves code between crates, reassess lint behavior, language compatibility, and the project’s minimum supported Rust version.
8. Use Miri as a dynamic check, not a safety certificate
For supported tests and unsafe paths, consider:
cargo +nightly miri test
cargo +nightly miri run
Miri requires a nightly toolchain. It interprets the program or test suite and can detect undefined behavior that falls within the rules it understands. A finding is a strong bug signal, but a clean run has limited meaning: Miri observes only code exercised by that run and does not cover every possible unsoundness.
Make Miri runs informative
- Add tests that exercise each unsafe branch, boundary condition, and error path you want Miri to inspect.
- Run the smallest relevant test first, then expand to the integration suite if the project supports it.
- Separate environment limitations from program results; unsupported dependencies or targets can prevent a meaningful run.
- Treat failures as evidence to investigate at the invariant level, not as a reason to patch around the reported line.
The Rust Book calls Miri “an official Rust tool for detecting undefined behavior,” while also explaining that only executed code is checked. Use it to increase confidence in exercised paths, never to certify an unsafe abstraction as sound.
Static checks, tests, and Miri answer different questions
| Method | What it can reveal | What it cannot establish |
|---|---|---|
| Compiler and borrow checker | Type errors, lifetime violations, trait mismatches, and many invalid safe-code operations. | Whether the algorithm meets the specification, whether unsafe preconditions are true, or whether runtime interactions are correct. |
| Clippy | Known correctness, suspicious, style, complexity, and performance patterns in the code it analyzes. | Complete semantic correctness or the soundness of an unsafe proof; individual lints can be inapplicable or intentionally noisy. |
| Project tests | Observed behavior for the inputs, states, targets, and failure paths covered by the suite. | Unexecuted branches, missing requirements, and every possible concurrency or unsafe failure. |
| Miri | Some undefined behavior in executed code under Miri’s model. | Unexecuted paths, unsupported behavior, and every form of unsoundness; a clean run is not proof. |
| Human contract review | Intent, API compatibility, invariants, side effects, threat assumptions, and project fit. | Mechanical exhaustiveness; it should be combined with automated checks rather than replace them. |
9. Review provenance and the final diff
After tests, lint fixes, or tool-assisted edits, inspect the final patch again. Generated changes can duplicate existing helpers, retain dead code from an earlier approach, or leave a workaround after the original problem has been fixed.
- Confirm that every changed file is required by the request.
- Remove unnecessary dependencies, broad permissions, debug output, and unrelated formatting churn.
- Check for unexpected network, file, process, environment, or telemetry access.
- Verify that generated code does not copy large blocks when a project utility already exists.
- Review feature-gated and platform-specific hunks, not only the default build.
- Run the project’s final check and relevant tests after the last edit, then record the commands and configurations used.
Provenance matters because a patch can pass tests while still exceeding the requested scope. A small, explainable diff is easier to maintain and makes future safety reviews tractable.
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- State the required behavior, inputs, outputs, errors, side effects, and compatibility constraints.
- Read callers, neighboring modules, traits, feature flags, edition settings, and project policies.
- Compare each generated branch and dependency with a documented requirement.
- Run the normal build or check commands and inspect warnings and feature-specific diagnostics.
- Run existing tests, then add cases for boundaries, invalid input, failures, ordering, concurrency, and regressions.
- Run
cargo clippy; investigate correctness and suspicious findings and justify any narrow suppression. - Search for all unsafe operations and record the exact preconditions for each one.
- Verify validity, alignment, initialization, bounds, aliasing, lifetime, ownership, synchronization, and FFI assumptions on every reachable path.
- Keep unsafe blocks small and confirm that any safe wrapper preserves its invariant for every permitted call sequence.
- Use
cargo +nightly miri testorcargo +nightly miri runwhen the code and test environment support it; interpret results as dynamic evidence only. - Check edition-specific behavior, especially
unsafe_op_in_unsafe_fnin Edition 2024. - Inspect the final diff for scope creep, unnecessary access, duplicated helpers, and changes made by automatic fixes.
The result should be a patch whose behavior is justified by the specification and project contracts, whose unsafe operations have explicit proofs, and whose automated checks are used as evidence rather than substituted for engineering judgment.
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