3 min read
Preparing Your Codebase for 2026: A Technical Debt Audit Guide
Before the new year begins, take time to audit your codebase. Here’s a systematic approach to identifying and prioritizing technical debt for 2026.
The Audit Framework
1. Dependency Health Check
# Check for outdated packages
dotnet list package --outdated
# Check for vulnerabilities
dotnet list package --vulnerable
# For Node.js
npm audit
npm outdated
Create a dependency report:
import subprocess
import json
def audit_dependencies():
"""Generate dependency health report."""
report = {
"outdated": [],
"vulnerable": [],
"deprecated": []
}
# Run npm audit
result = subprocess.run(
["npm", "audit", "--json"],
capture_output=True,
text=True
)
audit_data = json.loads(result.stdout)
for vuln_id, vuln in audit_data.get("vulnerabilities", {}).items():
report["vulnerable"].append({
"package": vuln_id,
"severity": vuln["severity"],
"recommendation": vuln.get("fixAvailable", "No fix available")
})
return report
2. Code Complexity Analysis
# Using radon for Python
radon cc src/ -a -s
# Using SonarQube for comprehensive analysis
sonar-scanner \
-Dsonar.projectKey=my-project \
-Dsonar.sources=src \
-Dsonar.host.url=http://localhost:9000
Flag files exceeding thresholds:
from radon.complexity import cc_visit
def find_complex_functions(source_code: str, threshold: int = 10):
"""Find functions with cyclomatic complexity above threshold."""
results = cc_visit(source_code)
complex_functions = [
{
"name": r.name,
"complexity": r.complexity,
"line": r.lineno
}
for r in results
if r.complexity > threshold
]
return complex_functions
3. Test Coverage Gaps
# Generate coverage report
dotnet test --collect:"XPlat Code Coverage"
# Identify untested code
reportgenerator \
-reports:coverage.cobertura.xml \
-targetdir:coveragereport \
-reporttypes:Html
Prioritize coverage for:
- Business-critical paths
- Recently changed code
- Integration points
4. Documentation Debt
def audit_documentation(repo_path: str) -> dict:
"""Check documentation completeness."""
issues = []
# Check for README
readme_path = os.path.join(repo_path, "README.md")
if not os.path.exists(readme_path):
issues.append("Missing README.md")
# Check for API documentation
api_docs = glob.glob(f"{repo_path}/**/openapi*.yaml", recursive=True)
if not api_docs:
issues.append("Missing OpenAPI specification")
# Check for architecture docs
arch_docs = glob.glob(f"{repo_path}/**/ARCHITECTURE.md", recursive=True)
if not arch_docs:
issues.append("Missing architecture documentation")
return {
"documentation_score": max(0, 100 - len(issues) * 20),
"issues": issues
}
5. Performance Bottlenecks
Review APM data for:
- Slow database queries
- High memory usage patterns
- API endpoints with high latency
-- Find slow queries in Azure SQL
SELECT TOP 20
qs.total_elapsed_time / qs.execution_count AS avg_elapsed_time,
qs.execution_count,
SUBSTRING(st.text, (qs.statement_start_offset/2)+1,
((CASE qs.statement_end_offset
WHEN -1 THEN DATALENGTH(st.text)
ELSE qs.statement_end_offset
END - qs.statement_start_offset)/2)+1) AS query_text
FROM sys.dm_exec_query_stats qs
CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st
ORDER BY avg_elapsed_time DESC;
Prioritization Matrix
| Category | Impact | Effort | Priority |
|---|---|---|---|
| Security vulnerabilities | High | Varies | P0 |
| Performance bottlenecks | High | Medium | P1 |
| Outdated frameworks | Medium | High | P1 |
| Test coverage gaps | Medium | Medium | P2 |
| Code complexity | Low | High | P3 |
| Documentation | Low | Low | P3 |
Create Your 2026 Roadmap
- Q1: Address all P0 and critical P1 items
- Q2: Complete remaining P1 items
- Q3: Work through P2 items
- Q4: Continuous P3 improvements
Technical debt compounds like financial debt. Regular audits and systematic paydown keep your codebase healthy and your team productive.