Verification Methodology

Methods to ensure quality when applying AIDLC in complex MSA environments.

Verification Checklist

Ontology Verification

• Completeness: Are all entities/events defined in the ontology?
• Consistency: Is the ontology consistent across Bounded Contexts?
• Accuracy: Do invariants match business rules?
• Traceability: Are ontology and code synchronized?

Harness Verification

• Coverage: Are all required harnesses implemented?
• Automation: Are harnesses integrated into CI/CD?
• Failure Scenarios: Are all failure scenarios tested?
• Performance: Is harness execution time reasonable?

Deployment Verification

• Canary Deployment: Is there a progressive rollout strategy?
• Rollback Plan: Can you rollback if problems occur?
• Monitoring: Is real-time monitoring available post-deployment?
• Alerting: Are anomaly detection alerts configured?

Verification Automation

CI/CD Pipeline

# .github/workflows/aidlc-validation.yml
name: AIDLC Validation

on: [push, pull_request]

jobs:
  validate-ontology:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Validate Ontology
        run: |
          aidlc-cli validate-ontology --path ontology/
  
  run-harness:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run Harness Tests
        run: |
          aidlc-cli run-harness --suite saga
          aidlc-cli run-harness --suite idempotency
  
  quality-gate:
    runs-on: ubuntu-latest
    needs: [validate-ontology, run-harness]
    steps:
      - name: Check Quality Gate
        run: |
          aidlc-cli quality-gate --threshold 80

Expert Review

Complexity L4-5 requires expert review

Review Checklist

• Is the Saga design appropriate?
• Does compensation logic cover all failure scenarios?
• Is there an event schema version management strategy?
• Is projection logic accurate?
• Are performance/scalability considerations reflected?

Review Process

1. Design Review: Review Saga/Event Sourcing design
2. Ontology Review: Verify ontology completeness/accuracy
3. Harness Review: Verify test coverage and failure scenarios
4. Performance Review: Review bottlenecks and scalability
5. Security Review: Analyze data consistency and security vulnerabilities

Quality Gate

Pass Criteria

Item	Minimum Requirement	Recommended Target
Ontology Coverage	90%	100%
Harness Success Rate	95%	100%
Required Harness Implementation	100%	-
Code Review Approval	Required	-
Expert Review (L4-5)	Required	-

Action on Failure

1. Incomplete Ontology: Add missing items and re-verify
2. Harness Failure: Fix bugs and re-run
3. Performance Issues: Resolve bottlenecks and re-measure
4. Expert Review Failure: Improve design and re-review

Continuous Improvement

Metric Tracking

• Ontology change frequency
• Harness execution time trends
• Production issue occurrence rate
• Rollback frequency

Feedback Loop

1. Add harness when production issues occur
2. Improve ontology for frequently failing patterns
3. Optimize slow harnesses
4. Document best practices

Next Steps

• Ontology Guide: Ontology writing methods
• Harness Checklist: Required harnesses by pattern
• MSA Complexity Overview: Return to full guide