Add Comprehensive End-to-End Testing with Temporary Database

[danstis]

Add Comprehensive End-to-End Testing with Temporary Database

User Story

As a developer, I want comprehensive end-to-end tests that validate the complete synchronization workflow using an isolated temporary database, so I can confidently deploy changes without breaking the ADO-Asana sync functionality.

Description

Implement a full end-to-end testing suite that creates a temporary, isolated database environment and validates all synchronization scenarios between Azure DevOps and Asana. This test suite should emulate real-world usage patterns and catch integration issues before they reach production.

Acceptance Criteria

Test Environment Setup

• Create temporary database instance for each test run
• Mock ADO and Asana API endpoints with realistic response data
• Set up test configuration files with sample project mappings
• Implement proper cleanup of temporary resources after test completion

Core Synchronization Scenarios

• Task Creation Sync: Verify new tasks created in ADO appear correctly in Asana
• Task Update Sync: Validate status changes, field updates, and assignments sync bidirectionally
• Task Deletion Handling: Test soft/hard deletion scenarios and proper cleanup
• Pull Request Linking: Verify PR creation in ADO links to corresponding Asana tasks
• Bidirectional Updates: Ensure changes in either system propagate correctly to the other

Edge Cases and Error Scenarios

• API Rate Limiting: Test behavior when APIs return rate limit responses
• Network Failures: Validate retry logic and graceful degradation
• Data Conflicts: Test resolution when both systems have conflicting updates
• Invalid Configurations: Verify proper error handling for malformed config files
• Partial Sync Failures: Ensure incomplete syncs can be resumed/retried

Data Integrity Validation

• Field Mapping Accuracy: Verify custom field mappings work correctly across projects
• Status Translation: Confirm status mappings between ADO and Asana are accurate
• Assignment Preservation: Ensure user assignments are maintained during sync
• Timestamp Handling: Validate creation/modification dates are preserved correctly

Performance and Reliability

• Bulk Operations: Test performance with large datasets (100+ tasks/PRs)
• Concurrent Updates: Verify handling of simultaneous changes in both systems
• Memory Usage: Ensure tests don't have memory leaks during extended runs
• Execution Time: Validate tests complete within reasonable timeframes

Technical Requirements

Test Infrastructure

• Use pytest framework with fixtures for database setup/teardown
• Implement mock servers for ADO and Asana APIs using responses or similar
• Create test data factories for generating realistic task and PR data
• Set up parallel test execution to reduce overall test time

Test Data Management

• Generate representative test datasets covering various project configurations
• Include edge cases like special characters, long descriptions, and complex hierarchies
• Implement data cleanup utilities to reset state between test runs

Reporting and Monitoring

• Generate detailed test reports with coverage metrics
• Include performance benchmarks and timing information
• Provide clear failure diagnostics with actionable error messages

Definition of Done

• All test scenarios pass consistently across multiple runs
• Test suite can be executed in CI/CD pipeline
• Documentation explains how to run and extend the test suite
• Code coverage for sync logic reaches minimum 85%
• Performance benchmarks are established and monitored
• Test artifacts (logs, reports) are properly cleaned up

Dependencies

• Temporary database setup utilities
• Mock API framework integration
• Test data generation scripts
• CI/CD pipeline configuration updates