amoa-verification-patterns

Verification Patterns for AMOA

Overview

Evidence-based verification for proving code and systems work correctly. Collect measurable, reproducible evidence -- not assumptions.

Prerequisites

• Python 3.8+, Bash, Git
• Optional: Selenium (E2E), Docker (containerized tests), SQLite/PostgreSQL (integration)

Output

Verification reports with pass/fail status, collected evidence, and formatted results per test-report-format.md.

Core Patterns

1. Evidence-based -- evidence-based-verification.md

2. Exit code proof -- exit-code-proof.md

3. E2E testing -- end-to-end-testing.md

4. Integration -- integration-verification.md

Principles

See: verification-principles.md

Instructions

1. Select the appropriate verification pattern (evidence-based, exit code, E2E, or integration)
2. Set up the test environment per testing-protocol.md
3. Execute verification and collect measurable evidence
4. Format results per evidence-format.md and test-report-format.md
5. Report pass/fail with evidence; escalate failures immediately (fail-fast)
6. Update GitHub issues per github-integration.md and clean up test environment

Copy this checklist and track your progress:

• Select pattern, set up environment
• Execute verification, collect evidence
• Format results, report pass/fail
• Update GitHub issues, clean up

Examples

Input: Agent receives verification request for a new function. Output: Verification report with pass/fail, collected evidence, formatted results.

See examples.md for worked examples.

Resources

• combining-patterns.md -- Combining patterns
  • 5.1 Pattern Combinations
  • 5.2 Verification Pyramid
  • 5.3 Complete Verification Strategy Example
• cross-platform-support.md -- Cross-platform
  • 6.1 Platform-Specific Behavior
  • 6.2 UTF-8 Encoding
  • 6.3 Platform Detection
  • 6.4 Path Handling
  • ...
• troubleshooting.md -- Troubleshooting
  • 10.1 Tests Pass Locally but Fail in CI/CD
  • 10.2 Exit Code is 0 but Process Failed
  • 10.3 Integration Test Fails with Timeout
  • 10.4 E2E Test is Flaky
  • ...
• docker-troubleshooting.md -- Docker
  • 1. Assessing Docker Container Needs for a Project
  • 2. Selecting Appropriate Base Images
  • 3. Applying Docker Best Practices
  • 4. Configuring Multi-Service Environments
  • ...
• quick-reference.md -- Quick reference & checklist
  • Pattern Selection Guide
  • Exit Codes
  • Output Format
  • Error Handling
  • ...

Error Handling

Fail-fast: failures propagate immediately, no fallbacks. See troubleshooting.md and docker-troubleshooting.md in Resources.