This document outlines the comprehensive testing strategy for HelixAgent, covering all 6 test types with a goal of achieving 100% test coverage across all modules. The strategy follows a 6-tier testing approach to ensure maximum quality and reliability.
Test individual functions, methods, and components in isolation to verify correct behavior.
- All Go functions and methods
- Individual service components
- Utility functions
- Data transformation logic
- Error handling paths
# Test directories
/tests/unit/services/
/internal/services/*_test.go
# Coverage targets
- services/debate_service.go: 100%
- services/memory_service.go: 100%
- services/provider_registry.go: 100%
- services/ensemble.go: 100%
- services/context_manager.go: 100%# Test directories
/tests/unit/providers/
/internal/llm/providers/*/*_test.go
# Coverage targets
- All 7+ LLM providers: 100% each
- Provider registry: 100%
- Health check mechanisms: 100%# Test directories
/tests/unit/handlers/
/internal/handlers/*_test.go
# Coverage targets
- API endpoints: 100%
- Request validation: 100%
- Response formatting: 100%- Go testing package
- Testify for assertions
- GoMock for mocking
- Coverage analysis tools
- Minimum 95% coverage for new code
- 100% coverage for critical paths
- All edge cases covered
- Error conditions validated
Test interactions between different components and services to ensure they work together correctly.
- Service-to-service communication
- Database integration
- External API integration
- Message queue integration
- Cache integration
# Test directories
/tests/integration/database/
/internal/database/*_test.go
# Test scenarios
- Connection establishment
- Query execution
- Transaction handling
- Error recovery
- Connection pooling# Test directories
/tests/integration/services/
/internal/services/*_integration_test.go
# Test scenarios
- Provider registry interactions
- Ensemble service coordination
- Memory service integration
- Context manager interactions# Test directories
/tests/integration/providers/
/internal/llm/providers/*_integration_test.go
# Test scenarios
- API endpoint connectivity
- Authentication validation
- Request/response handling
- Error condition simulation
- Rate limiting behavior- Docker for test environments
- Testcontainers for database testing
- WireMock for API mocking
- Integration test frameworks
- All service boundaries tested
- Database transactions validated
- External API interactions verified
- Error propagation confirmed
Test complete user workflows and business processes to ensure the system works as expected from end to end.
- Complete user journeys
- API scenario validation
- Multi-service workflows
- Data flow validation
- Business rule enforcement
# Test directories
/tests/e2e/api/
/tests/e2e/scenarios/
# Test scenarios
- Health check endpoints
- Model listing
- Completion requests
- Chat completions
- Ensemble requests
- Streaming responses# Test directories
/tests/e2e/ai_debate/
/tests/e2e/workflows/
# Test scenarios
- Simple debate initiation
- Multi-round discussions
- Consensus building
- Cognee integration
- Memory utilization# Test directories
/tests/e2e/configuration/
/tests/e2e/management/
# Test scenarios
- Configuration loading
- Provider registration
- Health monitoring
- Performance metrics
- Error reporting- Resty for HTTP testing
- Ginkgo for BDD testing
- Selenium for UI testing (if applicable)
- Newman for Postman collections
- All critical user workflows tested
- Data integrity validated
- Performance baselines established
- Error handling verified
Identify and mitigate security vulnerabilities to ensure the system is secure against common attack vectors.
- Authentication and authorization
- Input validation and sanitization
- Data protection and encryption
- Session management
- Error handling and information leakage
- API security
- Dependency security
# Test directories
/tests/security/auth/
/tests/security/jwt/
# Test scenarios
- JWT token validation
- Session management
- Password policies
- Account lockout mechanisms
- Multi-factor authentication# Test directories
/tests/security/input/
/tests/security/validation/
# Test scenarios
- SQL injection attempts
- Cross-site scripting (XSS)
- Command injection
- Path traversal
- Buffer overflow attempts# Test directories
/tests/security/data/
/tests/security/encryption/
# Test scenarios
- Data encryption at rest
- Data encryption in transit
- Sensitive data exposure
- Key management
- Backup security- OWASP ZAP for vulnerability scanning
- GoSec for static security analysis
- Bandit for Python security testing
- Nmap for network security testing
- SSL Labs for TLS testing
- OWASP Top 10 coverage achieved
- Zero critical vulnerabilities
- All security findings addressed
- Regular security scans implemented
Validate system performance and stability under high load conditions to ensure it can handle production workloads.
- High concurrency testing
- Resource utilization monitoring
- Performance under load validation
- Bottleneck identification
- Scalability validation
# Test directories
/tests/stress/load/
/tests/stress/concurrency/
# Test scenarios
- Concurrent request handling
- Request rate limiting
- Response time under load
- Throughput measurement
- Resource consumption monitoring# Test directories
/tests/stress/performance/
/tests/stress/benchmark/
# Test scenarios
- Response time profiling
- Memory usage analysis
- CPU utilization monitoring
- Database query performance
- Cache hit/miss ratios# Test directories
/tests/stress/capacity/
/tests/stress/scalability/
# Test scenarios
- Maximum concurrent users
- Data volume handling
- Long-running process stability
- Resource exhaustion scenarios
- Recovery from high load- K6 for load testing
- JMeter for performance testing
- Vegeta for HTTP load testing
- Prometheus for metrics collection
- Grafana for visualization
- Response times under 100ms (95th percentile)
- Handle 1000+ concurrent requests
- Resource utilization within limits
- Graceful degradation under overload
Test system resilience and fault tolerance by injecting failures and observing recovery behavior.
- Network partition simulation
- Service dependency failures
- Database connection failures
- Resource exhaustion scenarios
- Recovery time measurements
# Test directories
/tests/chaos/infrastructure/
/tests/chaos/network/
# Test scenarios
- Network latency injection
- Packet loss simulation
- Service unavailability
- DNS failures
- Load balancer issues# Test directories
/tests/chaos/application/
/tests/chaos/services/
# Test scenarios
- Service crashes
- Memory leaks
- CPU starvation
- Disk space exhaustion
- Database connection failures# Test directories
/tests/chaos/data/
/tests/chaos/storage/
# Test scenarios
- Data corruption
- Partial data loss
- Backup restoration
- Replication failures
- Consistency issues- Chaos Monkey for random failures
- Gremlin for controlled chaos
- Litmus for Kubernetes chaos
- Istio for service mesh chaos
- Custom failure injection tools
- Graceful degradation under failures
- Recovery within acceptable timeframes
- Data integrity maintained
- No cascading failures
# GitHub Actions Pipeline Stages
stages:
- code_quality: # Run on every commit
- go_fmt
- go_vet
- go_lint
- security_scan
- unit_tests: # Run on every commit
- unit_test_execution
- coverage_analysis
- code_complexity_check
- integration_tests: # Run on PR creation
- service_integration
- database_integration
- api_integration
- security_tests: # Run weekly
- vulnerability_scanning
- dependency_checking
- penetration_testing
- e2e_tests: # Run nightly
- api_scenarios
- user_workflows
- business_processes
- stress_tests: # Run before releases
- load_testing
- performance_benchmarking
- capacity_planning
- chaos_tests: # Run in staging
- failure_injection
- resilience_testing
- recovery_validation| Module | Minimum Coverage | Target Coverage | Critical Paths |
|---|---|---|---|
| Core Services | 95% | 100% | 100% |
| LLM Providers | 90% | 100% | 100% |
| Handlers/API | 95% | 100% | 100% |
| Database Layer | 90% | 100% | 100% |
| Cache Layer | 85% | 95% | 100% |
| Security Layer | 95% | 100% | 100% |
| Utilities | 90% | 100% | 100% |
- Use fixtures for consistent test data
- Implement data cleanup strategies
- Separate test and production data
- Use test databases/containers
- Implement data anonymization
- Real-time test execution reporting
- Coverage trend analysis
- Performance benchmarking
- Security vulnerability tracking
- Flaky test detection and elimination
# Pre-commit validation
- go fmt ./...
- go vet ./...
- go test -short ./...
- golangci-lint run# Pull request validation
- All unit tests pass
- Coverage meets minimum threshold
- No critical security issues
- Code review approval# Release candidate validation
- Full test suite execution
- Security scan completion
- Performance benchmark validation
- Chaos test results review- Local testing with mocks
- Docker-compose for service dependencies
- Environment variable configuration
- Test data seeding
- Isolated test environments
- Automated environment provisioning
- Test data management
- Resource cleanup
- Production-like infrastructure
- Real external service integration
- Load testing capabilities
- Chaos engineering setup
- Regular test refactoring
- Flaky test elimination
- Test performance optimization
- Coverage gap identification
- Test case documentation
- Test environment setup guides
- Troubleshooting guides
- Performance baseline documentation
- Regular test suite reviews
- Performance optimization
- New test type exploration
- Tool and framework updates
Last Updated: December 27, 2025