371 lines
9.3 KiB
Markdown
371 lines
9.3 KiB
Markdown
# Technical Debt Analysis and Remediation
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You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create actionable remediation plans.
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## Context
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The user needs a comprehensive technical debt analysis to understand what's slowing down development, increasing bugs, and creating maintenance challenges. Focus on practical, measurable improvements with clear ROI.
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## Requirements
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$ARGUMENTS
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## Instructions
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### 1. Technical Debt Inventory
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Conduct a thorough scan for all types of technical debt:
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**Code Debt**
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- **Duplicated Code**
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- Exact duplicates (copy-paste)
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- Similar logic patterns
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- Repeated business rules
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- Quantify: Lines duplicated, locations
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- **Complex Code**
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- High cyclomatic complexity (>10)
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- Deeply nested conditionals (>3 levels)
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- Long methods (>50 lines)
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- God classes (>500 lines, >20 methods)
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- Quantify: Complexity scores, hotspots
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- **Poor Structure**
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- Circular dependencies
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- Inappropriate intimacy between classes
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- Feature envy (methods using other class data)
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- Shotgun surgery patterns
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- Quantify: Coupling metrics, change frequency
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**Architecture Debt**
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- **Design Flaws**
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- Missing abstractions
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- Leaky abstractions
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- Violated architectural boundaries
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- Monolithic components
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- Quantify: Component size, dependency violations
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- **Technology Debt**
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- Outdated frameworks/libraries
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- Deprecated API usage
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- Legacy patterns (e.g., callbacks vs promises)
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- Unsupported dependencies
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- Quantify: Version lag, security vulnerabilities
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**Testing Debt**
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- **Coverage Gaps**
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- Untested code paths
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- Missing edge cases
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- No integration tests
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- Lack of performance tests
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- Quantify: Coverage %, critical paths untested
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- **Test Quality**
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- Brittle tests (environment-dependent)
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- Slow test suites
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- Flaky tests
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- No test documentation
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- Quantify: Test runtime, failure rate
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**Documentation Debt**
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- **Missing Documentation**
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- No API documentation
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- Undocumented complex logic
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- Missing architecture diagrams
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- No onboarding guides
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- Quantify: Undocumented public APIs
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**Infrastructure Debt**
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- **Deployment Issues**
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- Manual deployment steps
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- No rollback procedures
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- Missing monitoring
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- No performance baselines
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- Quantify: Deployment time, failure rate
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### 2. Impact Assessment
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Calculate the real cost of each debt item:
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**Development Velocity Impact**
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```
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Debt Item: Duplicate user validation logic
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Locations: 5 files
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Time Impact:
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- 2 hours per bug fix (must fix in 5 places)
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- 4 hours per feature change
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- Monthly impact: ~20 hours
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Annual Cost: 240 hours × $150/hour = $36,000
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```
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**Quality Impact**
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```
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Debt Item: No integration tests for payment flow
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Bug Rate: 3 production bugs/month
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Average Bug Cost:
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- Investigation: 4 hours
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- Fix: 2 hours
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- Testing: 2 hours
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- Deployment: 1 hour
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Monthly Cost: 3 bugs × 9 hours × $150 = $4,050
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Annual Cost: $48,600
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```
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**Risk Assessment**
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- **Critical**: Security vulnerabilities, data loss risk
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- **High**: Performance degradation, frequent outages
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- **Medium**: Developer frustration, slow feature delivery
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- **Low**: Code style issues, minor inefficiencies
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### 3. Debt Metrics Dashboard
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Create measurable KPIs:
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**Code Quality Metrics**
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```yaml
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Metrics:
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cyclomatic_complexity:
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current: 15.2
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target: 10.0
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files_above_threshold: 45
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code_duplication:
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percentage: 23%
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target: 5%
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duplication_hotspots:
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- src/validation: 850 lines
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- src/api/handlers: 620 lines
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test_coverage:
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unit: 45%
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integration: 12%
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e2e: 5%
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target: 80% / 60% / 30%
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dependency_health:
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outdated_major: 12
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outdated_minor: 34
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security_vulnerabilities: 7
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deprecated_apis: 15
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```
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**Trend Analysis**
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```python
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debt_trends = {
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"2024_Q1": {"score": 750, "items": 125},
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"2024_Q2": {"score": 820, "items": 142},
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"2024_Q3": {"score": 890, "items": 156},
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"growth_rate": "18% quarterly",
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"projection": "1200 by 2025_Q1 without intervention"
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}
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```
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### 4. Prioritized Remediation Plan
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Create an actionable roadmap based on ROI:
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**Quick Wins (High Value, Low Effort)**
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Week 1-2:
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```
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1. Extract duplicate validation logic to shared module
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Effort: 8 hours
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Savings: 20 hours/month
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ROI: 250% in first month
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2. Add error monitoring to payment service
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Effort: 4 hours
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Savings: 15 hours/month debugging
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ROI: 375% in first month
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3. Automate deployment script
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Effort: 12 hours
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Savings: 2 hours/deployment × 20 deploys/month
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ROI: 333% in first month
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```
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**Medium-Term Improvements (Month 1-3)**
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```
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1. Refactor OrderService (God class)
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- Split into 4 focused services
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- Add comprehensive tests
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- Create clear interfaces
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Effort: 60 hours
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Savings: 30 hours/month maintenance
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ROI: Positive after 2 months
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2. Upgrade React 16 → 18
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- Update component patterns
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- Migrate to hooks
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- Fix breaking changes
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Effort: 80 hours
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Benefits: Performance +30%, Better DX
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ROI: Positive after 3 months
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```
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**Long-Term Initiatives (Quarter 2-4)**
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```
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1. Implement Domain-Driven Design
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- Define bounded contexts
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- Create domain models
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- Establish clear boundaries
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Effort: 200 hours
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Benefits: 50% reduction in coupling
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ROI: Positive after 6 months
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2. Comprehensive Test Suite
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- Unit: 80% coverage
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- Integration: 60% coverage
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- E2E: Critical paths
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Effort: 300 hours
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Benefits: 70% reduction in bugs
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ROI: Positive after 4 months
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```
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### 5. Implementation Strategy
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**Incremental Refactoring**
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```python
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# Phase 1: Add facade over legacy code
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class PaymentFacade:
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def __init__(self):
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self.legacy_processor = LegacyPaymentProcessor()
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def process_payment(self, order):
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# New clean interface
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return self.legacy_processor.doPayment(order.to_legacy())
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# Phase 2: Implement new service alongside
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class PaymentService:
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def process_payment(self, order):
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# Clean implementation
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pass
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# Phase 3: Gradual migration
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class PaymentFacade:
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def __init__(self):
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self.new_service = PaymentService()
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self.legacy = LegacyPaymentProcessor()
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def process_payment(self, order):
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if feature_flag("use_new_payment"):
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return self.new_service.process_payment(order)
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return self.legacy.doPayment(order.to_legacy())
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```
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**Team Allocation**
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```yaml
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Debt_Reduction_Team:
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dedicated_time: "20% sprint capacity"
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roles:
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- tech_lead: "Architecture decisions"
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- senior_dev: "Complex refactoring"
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- dev: "Testing and documentation"
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sprint_goals:
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- sprint_1: "Quick wins completed"
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- sprint_2: "God class refactoring started"
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- sprint_3: "Test coverage >60%"
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```
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### 6. Prevention Strategy
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Implement gates to prevent new debt:
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**Automated Quality Gates**
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```yaml
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pre_commit_hooks:
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- complexity_check: "max 10"
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- duplication_check: "max 5%"
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- test_coverage: "min 80% for new code"
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ci_pipeline:
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- dependency_audit: "no high vulnerabilities"
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- performance_test: "no regression >10%"
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- architecture_check: "no new violations"
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code_review:
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- requires_two_approvals: true
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- must_include_tests: true
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- documentation_required: true
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```
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**Debt Budget**
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```python
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debt_budget = {
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"allowed_monthly_increase": "2%",
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"mandatory_reduction": "5% per quarter",
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"tracking": {
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"complexity": "sonarqube",
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"dependencies": "dependabot",
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"coverage": "codecov"
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}
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}
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```
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### 7. Communication Plan
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**Stakeholder Reports**
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```markdown
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## Executive Summary
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- Current debt score: 890 (High)
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- Monthly velocity loss: 35%
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- Bug rate increase: 45%
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- Recommended investment: 500 hours
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- Expected ROI: 280% over 12 months
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## Key Risks
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1. Payment system: 3 critical vulnerabilities
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2. Data layer: No backup strategy
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3. API: Rate limiting not implemented
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## Proposed Actions
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1. Immediate: Security patches (this week)
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2. Short-term: Core refactoring (1 month)
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3. Long-term: Architecture modernization (6 months)
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```
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**Developer Documentation**
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```markdown
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## Refactoring Guide
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1. Always maintain backward compatibility
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2. Write tests before refactoring
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3. Use feature flags for gradual rollout
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4. Document architectural decisions
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5. Measure impact with metrics
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## Code Standards
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- Complexity limit: 10
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- Method length: 20 lines
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- Class length: 200 lines
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- Test coverage: 80%
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- Documentation: All public APIs
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```
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### 8. Success Metrics
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Track progress with clear KPIs:
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**Monthly Metrics**
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- Debt score reduction: Target -5%
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- New bug rate: Target -20%
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- Deployment frequency: Target +50%
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- Lead time: Target -30%
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- Test coverage: Target +10%
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**Quarterly Reviews**
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- Architecture health score
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- Developer satisfaction survey
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- Performance benchmarks
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- Security audit results
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- Cost savings achieved
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## Output Format
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1. **Debt Inventory**: Comprehensive list categorized by type with metrics
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2. **Impact Analysis**: Cost calculations and risk assessments
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3. **Prioritized Roadmap**: Quarter-by-quarter plan with clear deliverables
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4. **Quick Wins**: Immediate actions for this sprint
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5. **Implementation Guide**: Step-by-step refactoring strategies
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6. **Prevention Plan**: Processes to avoid accumulating new debt
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7. **ROI Projections**: Expected returns on debt reduction investment
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Focus on delivering measurable improvements that directly impact development velocity, system reliability, and team morale. |