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Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/proffesor-for-testing/sentinel-api-testing --skill risk-based-testing명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | risk-based-testing |
| description | Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions. |
| category | testing-methodologies |
| priority | high |
| tokenEstimate | 1000 |
| agents | ["qe-regression-risk-analyzer","qe-test-generator","qe-production-intelligence","qe-quality-gate"] |
| implementation_status | optimized |
| optimization_version | 1 |
| last_optimized | 2025-12-02T00:00:00.000Z |
| dependencies | [] |
| quick_reference_card | true |
| tags | ["risk","prioritization","test-planning","coverage","impact-analysis"] |
<default_to_action> When planning tests or allocating testing resources:
Quick Risk Assessment:
Critical Success Factors:
Risk Score = Probability (1-5) × Impact (1-5)
| Score | Priority | Effort | Action |
|---|---|---|---|
| 20-25 | Critical | 60% | Comprehensive testing, multiple techniques |
| 12-19 | High | 25% | Thorough testing, automation priority |
| 6-11 | Medium | 10% | Standard testing, basic automation |
| 1-5 | Low | 5% | Smoke test, exploratory only |
| Factor | Low (1) | Medium (3) | High (5) |
|---|---|---|---|
| Complexity | Simple CRUD | Business logic | Algorithms, integrations |
| Change Rate | Stable 6+ months | Monthly changes | Weekly/daily changes |
| Developer Experience |
| Senior, domain expert |
| Mid-level |
| Junior, new to codebase |
| Technical Debt | Clean code | Some debt | Legacy, no tests |
| Factor | Low (1) | Medium (3) | High (5) |
|---|---|---|---|
| Users Affected | Admin only | Department | All users |
| Revenue | None | Indirect | Direct (checkout) |
| Safety | Convenience | Data loss | Physical harm |
| Reputation | Internal | Industry | Public scandal |
Feature | Probability | Impact | Risk | Priority
--------|-------------|--------|------|----------
Checkout | 4 | 5 | 20 | Critical
User Auth | 3 | 5 | 15 | High
Admin Panel | 2 | 2 | 4 | Low
Search | 3 | 3 | 9 | Medium
await Task("Risk-Based Test Generation", {
critical: {
features: ['checkout', 'payment'],
depth: 'comprehensive',
techniques: ['unit', 'integration', 'e2e', 'performance', 'security']
},
high: {
features: ['auth', 'user-profile'],
depth: 'thorough',
techniques: ['unit', 'integration', 'e2e']
},
medium: {
features: ['search', 'notifications'],
depth: 'standard',
techniques: ['unit', 'integration']
},
low: {
features: ['admin-panel', 'settings'],
depth: 'smoke',
techniques: ['smoke-tests']
}
}, "qe-test-generator");
// Production incident increases risk
await Task("Update Risk Score", {
feature: 'search',
event: 'production-incident',
previousRisk: 9,
newProbability: 5, // Increased due to incident
newRisk: 15 // Now HIGH priority
}, "qe-regression-risk-analyzer");
// Agent predicts risk using historical data
const riskAnalysis = await Task("ML Risk Analysis", {
codeChanges: changedFiles,
historicalBugs: bugDatabase,
prediction: {
model: 'gradient-boosting',
factors: ['complexity', 'change-frequency', 'author-experience', 'file-age']
}
}, "qe-regression-risk-analyzer");
// Output: 95% accuracy risk prediction per file
aqe/risk-based/
├── risk-scores/* - Current risk assessments
├── historical-bugs/* - Bug patterns by area
├── production-data/* - Incident data for risk
└── coverage-map/* - Test depth by risk level
const riskFleet = await FleetManager.coordinate({
strategy: 'risk-based-testing',
agents: [
'qe-regression-risk-analyzer', // Risk scoring
'qe-test-generator', // Risk-appropriate tests
'qe-production-intelligence', // Production feedback
'qe-quality-gate' // Risk-based gates
],
topology: 'sequential'
});
# Risk-based test selection in pipeline
- name: Risk Analysis
run: aqe risk-analyze --changes ${{ github.event.pull_request.files }}
- name: Run Critical Tests
if: risk.critical > 0
run: npm run test:critical
- name: Run High Tests
if: risk.high > 0
run: npm run test:high
- name: Skip Low Risk
if: risk.low_only
run: npm run test:smoke
Risk = Probability × Impact. Test where bugs hurt most. Critical gets 60%, low gets 5%. Risk is dynamic - reassess with new info. Production incidents raise risk scores.
With Agents: Agents calculate risk using ML on historical data, select risk-appropriate tests, and adjust scores from production feedback. Use agents to maintain dynamic risk profiles at scale.