ai-generated-ut-code-review

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Translated

Use when reviewing or scoring AI-generated unit tests/UT code, especially when coverage, assertion effectiveness, or test quality is in question and a numeric score, risk level, or must-fix checklist is needed

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Sourceopenharmonyinsight/openharmony-skills

Added on2026-02-07

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AI UT Code Review

Overview

Review AI-generated unit tests for effectiveness, coverage, assertions, negative cases, determinism, and maintainability. Output a 0-10 score, a risk level, and a must-fix checklist. Overall line coverage must be >= 80%; otherwise risk is at least High.

When to Use

AI-generated UT/test code review or quality evaluation
Need scoring, risk level, or must-fix checklist
Questions about coverage or assertion validity

Workflow

Confirm tests target the intended business code and key paths.
Check overall line coverage (>= 80% required).
Inspect assertions for behavioral validity; flag missing/ineffective assertions.
Verify negative/edge cases and determinism (no env/time dependency).
Score by rubric, assign risk, list must-fix items with evidence.

Scoring (0-10)

Each dimension 0-2 points. Sum = total score.

Dimension	0	1	2
Coverage	< 80%	80%+ but shallow	80%+ and meaningful
Assertion Quality	No/invalid assertions	Some weak assertions	Behavior-anchored assertions
Negative & Edge	Missing	Partial	Comprehensive
Data & Isolation	Flaky/env-dependent	Mixed	Deterministic, isolated
Maintainability	Hard to read/modify	Mixed quality	Clear structure & naming

Risk Levels

Blocker: Coverage < 80% AND key paths untested, or tests have no meaningful assertions
High: Coverage < 80% OR assertions largely ineffective
Medium: Coverage OK but weak edge cases or fragile design
Low: Minor improvements

Must-Fix Checklist

Overall line coverage >= 80%
Each test has at least one behavior-relevant assertion
Negative/exception cases exist for core logic
Tests are deterministic and repeatable

AI-Generated Test Pitfalls (Check Explicitly)

No assertions or assertions unrelated to behavior (e.g., only not-null)
Over-mocking hides real behavior
Only happy-path coverage
Tests depend on time/network/env
Missing verification of side effects

Output Format (Required, Semi-fixed)

```
Score
```
: x/10 — Coverage x, Assertion Quality x, Negative & Edge x, Data & Isolation x, Maintainability x
```
Risk
```
: Low/Medium/High/Blocker — 简述原因（1 行）
```
Must-fix
```
:
- [动作 + 证据]
- [动作 + 证据]
```
Key Evidence
```
:
- 引用具体测试用例名或覆盖率报告摘要（1-2 条）
```
Notes
```
:
- 最小修复建议或替代方案（1-2 行）

Rules:

覆盖率 < 80% 风险至少 High，并必须列入
```
Must-fix
```
无断言/无效断言直接提升风险级别，必须列入
```
Must-fix
```
至少 2 条证据；证据不足需说明并降分

Common Mistakes

仅报告覆盖率，不评价断言有效性
把日志输出当成断言
忽略失败路径/异常路径

Example (Concise)

Score: 5/10 (Coverage 1, Assertion 0, Negative 1, Data 2, Maintainability 1) Risk: High Must-fix:

Tests for
```
parseConfig()
```
contain no behavior assertions (only logs)
No negative cases for malformed input Key Evidence:
```
parseConfig()
```
tests only assert no crash
Coverage report shows 62% lines Notes:
Add assertions on outputs and side effects; add invalid input tests.