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+# Technical Debt Management Methodology - Reference
+
+This reference documentation provides comprehensive details on the SQALE-based technical debt quantification methodology developed in bootstrap-012.
+
+## Core Methodology Components
+
+**Six Components** (complete methodology):
+1. Measurement Framework (SQALE Index calculation)
+2. Categorization Framework (Code smell taxonomy)
+3. Prioritization Framework (Value-effort matrix)
+4. Paydown Framework (Phased roadmap)
+5. Tracking Framework (Trend analysis)
+6. Prevention Framework (Proactive practices)
+
+## SQALE Methodology
+
+**SQALE (Software Quality Assessment based on Lifecycle Expectations)**:
+- Industry-standard debt quantification
+- Development cost: LOC / 30 (30 LOC/hour productivity)
+- Remediation cost: Graduated complexity thresholds
+- TD Ratio: (Debt / Development Cost) × 100%
+- Rating: A (≤5%) to E (>50%)
+
+## Knowledge Artifacts
+
+All knowledge artifacts from bootstrap-012 are documented in:
+`experiments/bootstrap-012-technical-debt/knowledge/`
+
+**Patterns** (3):
+- SQALE-Based Debt Quantification (90% reusable)
+- Code Smell Taxonomy Mapping (80% reusable)
+- Value-Effort Prioritization Matrix (95% reusable)
+
+**Principles** (3):
+- Pay High-Value Low-Effort Debt First
+- SQALE Provides Objective Baseline
+- Complexity Drives Maintainability Debt
+
+**Templates** (4):
+- SQALE Index Report Template
+- Code Smell Categorization Template
+- Remediation Cost Breakdown Template
+- Transfer Guide Template
+
+**Best Practices** (3):
+- Use SQALE standard productivity (30 LOC/hour)
+- Apply graduated complexity thresholds
+- Categorize debt by SQALE characteristics
+
+## Effectiveness Validation
+
+**Speedup**: 4.5x vs manual approach
+- Manual: 9 hours (ad-hoc review, subjective)
+- Methodology: 2 hours (tool-based, SQALE)
+
+**Accuracy**: Subjective → Objective (SQALE standard)
+**Reproducibility**: Low → High (industry standard)
+
+## Transferability
+
+**Overall**: 85% transferable across languages
+
+**Language-Specific Adaptations**:
+- Go: 90% (native)
+- Python: 85% (threshold 10→12, tools: radon, pylint, pytest-cov)
+- JavaScript: 85% (threshold 10→8, tools: eslint, jscpd, nyc)
+- Java: 90% (tools: PMD, JaCoCo, CheckStyle)
+- Rust: 80% (threshold 10→15, tools: cargo-geiger, clippy, skip OO smells)
+
+**Universal Components** (13/16, 81%):
+- SQALE formulas (100%)
+- Prioritization matrix (100%)
+- Paydown roadmap structure (100%)
+- Tracking approach (95%)
+- Prevention practices (85%)
+
+**Language-Specific** (3/16, 19%):
+- Complexity threshold calibration (±20%)
+- Tool selection (language-specific)
+- OO smells applicability (OO languages only)
+
+## Experiment Results
+
+See full results: `experiments/bootstrap-012-technical-debt/results.md`
+
+**Key Metrics**:
+- V_instance = 0.805 (CONVERGED)
+- V_meta = 0.855 (CONVERGED)
+- 4 iterations, ~7 hours total
+- 4.5x speedup, 85% transferability
+- meta-cc debt: 66 hours, 15.52% TD ratio, rating C
+- Paydown roadmap: 31.5 hours → rating B (8.23%)