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npx skills add https://github.com/proffesor-for-testing/sentinel-api-testing --skill risk-based-testingيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
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تحميل Zip جاري التحميل... المهن ذات الصلة SOC
استنادا إلى تصنيف SOC المهني
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"]
Risk-Based Testing
<default_to_action>
When planning tests or allocating testing resources:
IDENTIFY risks: What can go wrong? What's the impact? What's the likelihood?
CALCULATE risk: Risk = Probability × Impact (use 1-5 scale for each)
PRIORITIZE: Critical (20+) → High (12-19) → Medium (6-11) → Low (1-5)
ALLOCATE effort: 60% critical, 25% high, 10% medium, 5% low
REASSESS continuously: New info, changes, production incidents
Quick Risk Assessment:
Probability factors: Complexity, change frequency, developer experience, technical debt
Impact factors: User count, revenue, safety, reputation, regulatory
Dynamic adjustment: Production bugs increase risk; stable code decreases
Critical Success Factors:
Test where bugs hurt most, not everywhere equally
Risk is dynamic - reassess with new information
Production data informs risk (shift-right feeds shift-left)
</default_to_action>
Quick Reference Card
When to Use
Planning sprint/release test strategy
Deciding what to automate first
Allocating limited testing time
Justifying test coverage decisions
Risk Calculation
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
Probability Factors
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
Technical Debt Clean code Some debt Legacy, no tests
Impact Factors 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
Risk Assessment Workflow
Step 1: List Features/Components 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
Step 2: Apply Test Depth 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" );
Step 3: Reassess Dynamically
await Task ("Update Risk Score" , {
feature : 'search' ,
event : 'production-incident' ,
previousRisk : 9 ,
newProbability : 5 ,
newRisk : 15
}, "qe-regression-risk-analyzer" );
ML-Enhanced Risk Analysis
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" );
Agent Coordination Hints
Memory Namespace 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
Fleet Coordination const riskFleet = await FleetManager .coordinate ({
strategy : 'risk-based-testing' ,
agents : [
'qe-regression-risk-analyzer' ,
'qe-test-generator' ,
'qe-production-intelligence' ,
'qe-quality-gate'
],
topology : 'sequential'
});
Integration with CI/CD
- 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
Related Skills
Remember 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.
