# AI code review, debugging, and validation practice

> Situational resources for reviewing generated code, debugging plausible fixes, tracing unfamiliar state, and preparing focused code review.

- Canonical HTML: [https://unrust.dev/use-cases](https://unrust.dev/use-cases)
- Markdown representation: [https://unrust.dev/use-cases/index.md](https://unrust.dev/use-cases/index.md)

## Use cases

- [How to Review AI-Generated Code Safely](https://unrust.dev/use-cases/review-ai-generated-code/index.md): Use a contract-first review loop to inspect AI-generated code, test risky boundaries, and decide whether a proposed change is ready to merge.
- [How to Debug a Plausible AI Fix](https://unrust.dev/use-cases/debug-a-plausible-ai-fix/index.md): A disciplined way to investigate a believable AI-suggested fix without confusing a fluent explanation with evidence about the real failure.
- [How to Validate Copilot Suggestions](https://unrust.dev/use-cases/validate-copilot-suggestions/index.md): Validate autocomplete and Copilot suggestions by checking their contract, assumptions, and tests before a small completion becomes a hidden behavior change.
- [How to Spot Hallucinated APIs in Code](https://unrust.dev/use-cases/spot-hallucinated-apis/index.md): Find invented or mismatched APIs in proposed code by checking imports, installed versions, signatures, and failure behavior instead of trusting familiar names.
- [How to Trace State in Unfamiliar Code](https://unrust.dev/use-cases/trace-state-in-unfamiliar-code/index.md): Trace state in an unfamiliar function by following only the values, references, branches, and side effects that can change the behavior you are investigating.
- [How to Regain Useful Code Recall](https://unrust.dev/use-cases/regain-code-recall/index.md): Regain useful code recall with small retrieval exercises that target recurring patterns, then compare your draft with a trusted reference and name the gap.
- [How to Prepare for a Focused Code Review](https://unrust.dev/use-cases/prepare-for-code-review/index.md): Prepare a small, evidence-rich code review by clarifying the contract, reducing unrelated changes, and showing tests that cover the risky behavior.
- [How to Investigate a Production Bug](https://unrust.dev/use-cases/investigate-a-production-bug/index.md): Investigate a production bug with a safe evidence loop: stabilize impact, capture facts, form narrow hypotheses, and verify the smallest corrective change.
- [How to Understand an AI-Generated Pull Request](https://unrust.dev/use-cases/understand-an-ai-generated-pull-request/index.md): Understand an AI-generated pull request by mapping the request to the diff, tracing its data flow, and isolating every assumption before approval.
- [How to Test an AI-Suggested Refactor](https://unrust.dev/use-cases/test-an-ai-suggested-refactor/index.md): Test an AI-suggested refactor by preserving observable behavior, specifying invariants, and comparing before-and-after cases instead of trusting cleaner-looking code.
- [How to Practice Before an On-Call Shift](https://unrust.dev/use-cases/practice-before-on-call/index.md): Prepare for on-call with short, repeatable debugging and tracing drills that strengthen evidence habits without pretending to simulate every incident.
- [How to Prepare for a Coding Interview Without an Assistant](https://unrust.dev/use-cases/prepare-for-a-coding-interview/index.md): Prepare for a coding interview with a short baseline read, a few days of focused unassisted practice on your two softest skills, and an honest second read that separates noise from change.
- [How to Inspect an Autocomplete Completion](https://unrust.dev/use-cases/inspect-an-autocomplete-completion/index.md): Inspect an autocomplete completion by checking the surrounding contract, its hidden defaults, and the smallest test that shows whether the proposed lines belong there.

Each resource is practice material, not a causal explanation for an individual diagnostic result.