# Test Priorities Matrix for Risk-Based Testing

## Priority Classification Framework

Test scenarios should be prioritized using a Risk-Based Testing approach that considers both **Business Impact** and **Failure Probability**.

## Risk Assessment Matrix

```
         HIGH PROBABILITY    MEDIUM PROBABILITY    LOW PROBABILITY
HIGH    │     P1            │        P1          │      P2        │
IMPACT  │  (CRITICAL)       │    (CRITICAL)      │   (HIGH)       │
        │                   │                    │                │
────────┼───────────────────┼────────────────────┼────────────────┤
MEDIUM  │     P1            │        P2          │      P3        │
IMPACT  │  (CRITICAL)       │     (HIGH)         │   (MEDIUM)     │
        │                   │                    │                │
────────┼───────────────────┼────────────────────┼────────────────┤
LOW     │     P2            │        P3          │      P4        │
IMPACT  │   (HIGH)          │    (MEDIUM)        │    (LOW)       │
```

## Priority Definitions

### P1 - Critical Priority
**Characteristics**: High business impact with any probability of failure
**Test Coverage**: 100% automated + comprehensive manual testing
**Execution Frequency**: Every build and deployment
**Response Time**: Immediate fix required

**Examples**:
- User authentication and authorization
- Payment processing and transactions
- Data security and privacy functions
- Core business workflow features
- System availability and performance

### P2 - High Priority  
**Characteristics**: Medium-high business impact or high probability issues
**Test Coverage**: Automated where possible + targeted manual testing
**Execution Frequency**: Daily or per release cycle
**Response Time**: Fix within 24-48 hours

**Examples**:
- User registration and profile management
- Data export and reporting features
- Non-critical integrations with third-party services
- Advanced search and filtering capabilities
- Notification and messaging systems

### P3 - Medium Priority
**Characteristics**: Medium impact with medium probability
**Test Coverage**: Strategic automation + periodic manual validation
**Execution Frequency**: Weekly or per sprint
**Response Time**: Fix within sprint or next release

**Examples**:
- UI polish and visual improvements
- Non-essential feature enhancements
- Performance optimizations for edge cases
- Accessibility improvements beyond compliance
- Analytics and tracking features

### P4 - Low Priority
**Characteristics**: Low impact and low probability of failure
**Test Coverage**: Minimal automated testing + exploratory manual testing
**Execution Frequency**: Per major release
**Response Time**: Fix when resources available

**Examples**:
- Cosmetic UI adjustments
- Nice-to-have convenience features
- Edge case error message improvements
- Advanced customization options
- Experimental or beta features

## Business Impact Assessment

### High Business Impact Factors
- **Revenue Impact**: Directly affects sales, subscriptions, or transactions
- **User Retention**: Critical to user satisfaction and retention
- **Compliance Risk**: Regulatory or legal compliance requirements
- **Security Risk**: Data breaches or unauthorized access potential
- **Reputation Risk**: Public-facing failures affecting brand reputation
- **Operational Risk**: System downtime or critical workflow interruption

### Medium Business Impact Factors
- **User Experience**: Affects usability but not core functionality
- **Efficiency**: Impacts user productivity but has workarounds
- **Data Integrity**: Non-critical data loss or corruption potential
- **Integration**: Third-party service disruption with backup options
- **Performance**: Degraded performance but system remains functional

### Low Business Impact Factors
- **Cosmetic Issues**: Visual or aesthetic problems
- **Convenience Features**: Nice-to-have functionality
- **Edge Cases**: Rare scenarios with minimal user impact
- **Advanced Features**: Features used by small user percentage
- **Non-Critical Analytics**: Tracking or reporting that's not essential

## Failure Probability Assessment

### High Probability Factors
- **New Features**: Recently developed functionality
- **Complex Logic**: Intricate business rules or calculations
- **External Dependencies**: Integration with unreliable third-party services  
- **High Usage Areas**: Frequently used features with heavy load
- **Historical Issues**: Areas with previous bug reports or failures
- **Technology Changes**: New frameworks, libraries, or infrastructure

### Medium Probability Factors
- **Modified Code**: Existing features with recent changes
- **Moderate Complexity**: Standard business logic implementation
- **Stable Dependencies**: Well-established third-party integrations
- **Moderate Usage**: Regularly used but not heavily trafficked features
- **Proven Technology**: Mature, well-tested technology stack

### Low Probability Factors
- **Stable Code**: Long-established, unchanged functionality
- **Simple Logic**: Straightforward, well-understood implementations
- **Internal Components**: No external dependencies
- **Low Usage**: Rarely accessed features
- **Well-Tested Areas**: High test coverage with proven stability

## Testing Strategy by Priority

### P1 - Critical Testing Strategy
**Test Types**:
- Comprehensive unit testing (95%+ coverage)
- Full integration testing of all scenarios
- End-to-end testing of complete user journeys
- Performance testing under load
- Security penetration testing
- Accessibility compliance validation

**Automation Level**: 90%+ automated
**Manual Testing**: Exploratory testing and edge case validation
**Monitoring**: Real-time alerting and monitoring in production

### P2 - High Testing Strategy
**Test Types**:
- Thorough unit testing (85%+ coverage)
- Key integration scenarios testing
- Primary user journey end-to-end testing
- Basic performance validation
- Security review and testing

**Automation Level**: 80%+ automated
**Manual Testing**: User acceptance testing and usability validation
**Monitoring**: Regular health checks and performance monitoring

### P3 - Medium Testing Strategy
**Test Types**:
- Standard unit testing (75%+ coverage)
- Critical integration paths
- Core functionality end-to-end testing
- Performance spot checks

**Automation Level**: 70%+ automated
**Manual Testing**: Periodic regression testing
**Monitoring**: Basic error tracking and user feedback

### P4 - Low Testing Strategy
**Test Types**:
- Basic unit testing (60%+ coverage)
- Smoke testing for basic functionality
- Manual exploratory testing

**Automation Level**: 50%+ automated
**Manual Testing**: Ad-hoc testing during development
**Monitoring**: User feedback and error logs

## Implementation Guidelines

### For QA Agent
1. **Risk Assessment**: Use this matrix to classify all test scenarios
2. **Resource Allocation**: Spend 60% of effort on P1, 25% on P2, 10% on P3, 5% on P4
3. **Test Planning**: Create test plans that reflect priority classifications
4. **Quality Gates**: Establish different criteria for different priority levels

### For PM Agent
1. **Feature Prioritization**: Consider testing priority in feature planning
2. **Release Planning**: Ensure P1 features have adequate testing time
3. **Risk Communication**: Clearly communicate high-risk areas to stakeholders
4. **Acceptance Criteria**: Include testing priority in story acceptance criteria

### For Developer Agent
1. **Development Focus**: Implement comprehensive error handling for P1 features
2. **Code Quality**: Apply highest standards to P1 and P2 priority areas
3. **Testing Integration**: Ensure automated tests are implemented for high-priority features
4. **Documentation**: Provide detailed documentation for critical functionality

### Priority Review Process

**Weekly Reviews**: Assess if any features need priority level changes
**Post-Incident**: Re-evaluate priority based on actual failure impact
**Release Planning**: Adjust testing time allocation based on priority distribution
**Metrics Analysis**: Use production data to validate priority assignments