# Testing Improvements

## 1. Test Coverage Gaps

### Current Issues

- **Incomplete UI Testing**: UI components have TODO placeholders instead of actual tests
- **Missing Integration Tests**: Some critical integration paths not covered
- **No Performance Testing**: No performance benchmarks or load testing
- **Insufficient Error Path Testing**: Error conditions not thoroughly tested
- **Missing Property-Based Testing**: No property-based testing for data validation

### Identified Coverage Gaps

#### UI Component Testing

```python
# tests/orchestrator/generator/test_ui_components.py
# Current TODO items that need implementation:

class TestTaskEditorUI:
    """Test the TaskEditor UI component with mock interactions."""

    def test_task_editor_initialization(self, sample_tasks: list) -> None:
        """Test task editor initialization."""
        # TODO: Refactor TaskEditorApp to separate business logic from UI rendering
        # - Extract task management logic into TaskManagerService
        # - Make TaskEditorApp a thin wrapper around the service
        # - Test the service logic independently of UI framework
        pass

    def test_compose_creates_tree_structure(self, sample_tasks: list) -> None:
        """Test that compose method creates proper tree structure."""
        # TODO: Refactor to separate tree structure logic from UI rendering
        # - Create TreeStructureBuilder service
        # - Test tree building logic independently
        # - Make compose method use the service
        pass
```

#### Missing Integration Tests

```python
# tests/integration/test_missing_integrations.py
import pytest
from arklex.orchestrator import AgentOrg
from arklex.env.tools.shopify import ShopifyTool
from arklex.env.tools.hubspot import HubSpotTool

class TestMissingIntegrationPaths:
    """Test integration paths that are currently missing coverage."""
    
    @pytest.mark.asyncio
    async def test_shopify_oauth_flow(self):
        """Test complete Shopify OAuth authentication flow."""
        # Test OAuth flow from start to finish
        # - Generate auth link
        # - Handle callback
        # - Exchange code for token
        # - Store token securely
        pass
    
    @pytest.mark.asyncio
    async def test_hubspot_contact_creation(self):
        """Test HubSpot contact creation with validation."""
        # Test contact creation with various data scenarios
        # - Valid contact data
        # - Invalid contact data
        # - Duplicate contact handling
        pass
    
    @pytest.mark.asyncio
    async def test_milvus_vector_search_performance(self):
        """Test Milvus vector search performance under load."""
        # Test vector search with large datasets
        # - Measure response times
        # - Test concurrent searches
        # - Validate result accuracy
        pass
```

## 2. Performance Testing Framework

### Current Issues

- **No Performance Benchmarks**: No baseline performance metrics
- **Missing Load Testing**: No load testing for API endpoints
- **No Memory Leak Detection**: No memory usage monitoring
- **No Response Time Tracking**: No response time benchmarks

### Proposed Solutions

#### Performance Testing Framework

```python
# tests/performance/test_performance.py
import time
import psutil
import pytest
import asyncio
from typing import Dict, Any
from concurrent.futures import ThreadPoolExecutor

class PerformanceTester:
    def __init__(self):
        self.baseline_metrics = {}
        self.current_metrics = {}
    
    def measure_execution_time(self, func, *args, **kwargs) -> float:
        """Measure execution time of a function."""
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        return end_time - start_time
    
    def measure_memory_usage(self, func, *args, **kwargs) -> Dict[str, float]:
        """Measure memory usage during function execution."""
        process = psutil.Process()
        initial_memory = process.memory_info().rss
        
        result = func(*args, **kwargs)
        
        final_memory = process.memory_info().rss
        peak_memory = process.memory_info().rss  # This would need more sophisticated tracking
        
        return {
            "initial_memory_mb": initial_memory / 1024 / 1024,
            "final_memory_mb": final_memory / 1024 / 1024,
            "peak_memory_mb": peak_memory / 1024 / 1024,
            "memory_increase_mb": (final_memory - initial_memory) / 1024 / 1024
        }
    
    def load_test(self, endpoint_func, num_requests: int = 100, 
                  concurrent_requests: int = 10) -> Dict[str, Any]:
        """Perform load testing on an endpoint."""
        results = []
        start_time = time.time()
        
        with ThreadPoolExecutor(max_workers=concurrent_requests) as executor:
            futures = [executor.submit(endpoint_func) for _ in range(num_requests)]
            
            for future in futures:
                try:
                    result = future.result()
                    results.append(result)
                except Exception as e:
                    results.append({"error": str(e)})
        
        end_time = time.time()
        
        return {
            "total_requests": num_requests,
            "successful_requests": len([r for r in results if "error" not in r]),
            "failed_requests": len([r for r in results if "error" in r]),
            "total_time_seconds": end_time - start_time,
            "requests_per_second": num_requests / (end_time - start_time),
            "average_response_time": sum(r.get("response_time", 0) for r in results) / len(results)
        }

class TestPerformance:
    """Performance test suite."""
    
    def test_agent_response_time(self):
        """Test agent response time meets performance requirements."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        tester = PerformanceTester()
        
        # Test response time
        response_time = tester.measure_execution_time(
            agent.run, "What is the weather like?"
        )
        
        # Should respond within 5 seconds
        assert response_time < 5.0, f"Response time {response_time}s exceeds 5s limit"
    
    def test_memory_usage_stability(self):
        """Test that memory usage remains stable during operations."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        tester = PerformanceTester()
        
        # Measure memory usage during multiple operations
        memory_metrics = tester.measure_memory_usage(
            lambda: [agent.run("Test message") for _ in range(10)]
        )
        
        # Memory increase should be reasonable (< 100MB)
        assert memory_metrics["memory_increase_mb"] < 100, \
            f"Memory increase {memory_metrics['memory_increase_mb']}MB exceeds 100MB limit"
    
    def test_concurrent_requests(self):
        """Test system behavior under concurrent load."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        tester = PerformanceTester()
        
        # Test with 50 concurrent requests
        load_results = tester.load_test(
            lambda: agent.run("Test concurrent request"),
            num_requests=50,
            concurrent_requests=10
        )
        
        # Success rate should be > 95%
        success_rate = load_results["successful_requests"] / load_results["total_requests"]
        assert success_rate > 0.95, f"Success rate {success_rate} below 95% threshold"
        
        # Average response time should be < 3 seconds
        assert load_results["average_response_time"] < 3.0, \
            f"Average response time {load_results['average_response_time']}s exceeds 3s limit"
```

## 3. Property-Based Testing

### Current Issues

- **No Property-Based Testing**: No Hypothesis-based testing
- **Limited Edge Case Coverage**: Edge cases not systematically tested
- **No Data Validation Testing**: Input validation not thoroughly tested

### Proposed Solutions

#### Property-Based Testing Framework

```python
# tests/property/test_properties.py
from hypothesis import given, strategies as st
from hypothesis.strategies import text, integers, floats, booleans
from arklex.utils.graph_state import MessageState
from arklex.env.tools.RAG.retrievers.retriever_document import RetrieverDocument

class TestDataProperties:
    """Property-based tests for data structures."""
    
    @given(text(min_size=1, max_size=1000))
    def test_message_state_serialization(self, message_text: str):
        """Test that MessageState can be serialized and deserialized correctly."""
        state = MessageState(response=message_text)
        serialized = state.model_dump()
        deserialized = MessageState(**serialized)
        assert deserialized.response == message_text
    
    @given(text(min_size=1, max_size=100), text(min_size=1, max_size=100))
    def test_retriever_document_creation(self, title: str, content: str):
        """Test RetrieverDocument creation with various inputs."""
        doc = RetrieverDocument(
            title=title,
            content=content,
            doc_type="test"
        )
        assert doc.title == title
        assert doc.content == content
        assert doc.doc_type == "test"
    
    @given(st.lists(text(min_size=1, max_size=100), min_size=1, max_size=10))
    def test_document_collection_operations(self, documents: list[str]):
        """Test operations on document collections."""
        # Test that operations on document collections are consistent
        # regardless of order or size
        pass

class TestAPIProperties:
    """Property-based tests for API behavior."""
    
    @given(text(min_size=1, max_size=1000))
    def test_api_response_consistency(self, input_text: str):
        """Test that API responses are consistent for same inputs."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        
        # Same input should produce consistent results
        response1 = agent.run(input_text)
        response2 = agent.run(input_text)
        
        # Responses should be similar (allowing for non-deterministic LLM)
        # This is a simplified check - in practice you'd want more sophisticated comparison
        assert len(response1) > 0
        assert len(response2) > 0
    
    @given(st.integers(min_value=1, max_value=100))
    def test_pagination_consistency(self, page_size: int):
        """Test that pagination works correctly for various page sizes."""
        # Test pagination behavior with different page sizes
        # Ensure that results are consistent and complete
        pass
```

## 4. Error Path Testing

### Current Issues

- **Insufficient Error Testing**: Error conditions not thoroughly tested
- **Missing Exception Handling Tests**: Exception handling not validated
- **No Recovery Testing**: System recovery from errors not tested

### Proposed Solutions

#### Comprehensive Error Testing

```python
# tests/error/test_error_handling.py
import pytest
from unittest.mock import Mock, patch
from arklex.utils.exceptions import ArklexError, AuthenticationError, RateLimitError

class TestErrorHandling:
    """Test error handling and recovery."""
    
    def test_authentication_error_handling(self):
        """Test handling of authentication errors."""
        from arklex.env.tools.shopify.utils import authorify_admin
        
        # Test with invalid credentials
        with pytest.raises(AuthenticationError):
            authorify_admin({
                "shop_url": "",
                "api_version": "",
                "admin_token": ""
            })
    
    def test_rate_limit_error_handling(self):
        """Test handling of rate limit errors."""
        # Mock rate limiter to simulate rate limit exceeded
        with patch('arklex.core.security.rate_limiter.RateLimiter.is_allowed') as mock_limiter:
            mock_limiter.return_value = False
            
            # Test that rate limit errors are properly handled
            pass
    
    def test_database_connection_error_recovery(self):
        """Test recovery from database connection errors."""
        from arklex.utils.mysql import mysql_pool
        
        # Test with invalid database connection
        with patch('mysql.connector.connect') as mock_connect:
            mock_connect.side_effect = Exception("Connection failed")
            
            # Test that connection errors are handled gracefully
            pass
    
    def test_llm_api_error_handling(self):
        """Test handling of LLM API errors."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        
        # Mock LLM API to return errors
        with patch('langchain_openai.ChatOpenAI.invoke') as mock_invoke:
            mock_invoke.side_effect = Exception("API Error")
            
            # Test that LLM errors are handled gracefully
            result = agent.run("Test message")
            assert "error" in result.lower() or "unavailable" in result.lower()
    
    def test_malformed_input_handling(self):
        """Test handling of malformed inputs."""
        from arklex.orchestrator import AgentOrg
        
        agent = AgentOrg()
        
        # Test with various malformed inputs
        malformed_inputs = [
            "",  # Empty string
            None,  # None value
            "   ",  # Whitespace only
            "a" * 10000,  # Very long string
            "🎉🎊🎈",  # Unicode characters
        ]
        
        for input_text in malformed_inputs:
            try:
                result = agent.run(input_text)
                # Should handle gracefully without crashing
                assert isinstance(result, str)
            except Exception as e:
                # Should be a controlled exception, not a crash
                assert isinstance(e, (ArklexError, ValueError))
```

## 5. Integration Test Improvements

### Current Issues

- **Incomplete Integration Coverage**: Some integration paths not tested
- **No End-to-End Testing**: No complete workflow testing
- **Missing External Service Testing**: External service integration not fully tested

### Proposed Solutions

#### Enhanced Integration Testing

```python
# tests/integration/test_complete_workflows.py
import pytest
from unittest.mock import Mock, patch
from arklex.orchestrator import AgentOrg

class TestCompleteWorkflows:
    """Test complete end-to-end workflows."""
    
    @pytest.mark.asyncio
    async def test_customer_service_workflow(self):
        """Test complete customer service workflow."""
        # Test complete customer service flow:
        # 1. Customer inquiry
        # 2. Intent classification
        # 3. Tool selection
        # 4. Response generation
        # 5. Follow-up handling
        
        agent = AgentOrg()
        
        # Mock external services
        with patch('arklex.env.tools.shopify.get_order') as mock_get_order:
            mock_get_order.return_value = {"order_id": "123", "status": "shipped"}
            
            # Test complete workflow
            response = agent.run("What's the status of my order 123?")
            
            # Verify response contains order information
            assert "shipped" in response.lower()
            assert "123" in response
    
    @pytest.mark.asyncio
    async def test_rag_document_search_workflow(self):
        """Test complete RAG document search workflow."""
        # Test complete RAG workflow:
        # 1. User question
        # 2. Document retrieval
        # 3. Context generation
        # 4. Answer synthesis
        
        agent = AgentOrg()
        
        # Mock RAG components
        with patch('arklex.env.tools.RAG.retrievers.milvus_retriever.MilvusRetriever.search') as mock_search:
            mock_search.return_value = [
                {"content": "Product information", "score": 0.9}
            ]
            
            response = agent.run("What are the features of your product?")
            
            # Verify response is based on retrieved documents
            assert len(response) > 0
    
    @pytest.mark.asyncio
    async def test_human_in_the_loop_workflow(self):
        """Test complete HITL workflow."""
        # Test complete HITL workflow:
        # 1. Automated processing
        # 2. Confidence assessment
        # 3. Human intervention when needed
        # 4. Result integration
        
        agent = AgentOrg()
        
        # Mock HITL components
        with patch('arklex.env.workers.hitl_worker.HITLWorker.verify_literal') as mock_verify:
            mock_verify.return_value = (True, "Human intervention needed")
            
            response = agent.run("I want to make a large purchase")
            
            # Verify HITL was triggered
            assert "confirmation" in response.lower() or "verify" in response.lower()
```

## 6. Test Infrastructure Improvements

### Current Issues

- **No Test Data Management**: No systematic test data management
- **Missing Test Utilities**: Limited test utility functions
- **No Test Parallelization**: Tests run sequentially
- **Insufficient Test Reporting**: Limited test reporting capabilities

### Proposed Solutions

#### Test Infrastructure Framework

```python
# tests/conftest.py improvements
import pytest
import asyncio
from typing import Generator, Dict, Any
from unittest.mock import Mock

# Enhanced fixtures
@pytest.fixture(scope="session")
def test_data() -> Dict[str, Any]:
    """Provide comprehensive test data."""
    return {
        "shopify": {
            "orders": [
                {"id": "123", "status": "shipped", "total": "100.00"},
                {"id": "456", "status": "pending", "total": "200.00"}
            ],
            "customers": [
                {"id": "1", "email": "test@example.com", "name": "Test User"}
            ]
        },
        "hubspot": {
            "contacts": [
                {"id": "1", "email": "contact@example.com", "firstname": "John"}
            ],
            "deals": [
                {"id": "1", "amount": "5000", "stage": "qualified"}
            ]
        },
        "rag": {
            "documents": [
                {"title": "Product Guide", "content": "Product features and benefits"},
                {"title": "FAQ", "content": "Common questions and answers"}
            ]
        }
    }

@pytest.fixture(scope="session")
def mock_external_services():
    """Mock all external services for testing."""
    with patch('arklex.env.tools.shopify.utils.make_query') as mock_shopify:
        with patch('arklex.env.tools.hubspot.utils.make_query') as mock_hubspot:
            with patch('arklex.env.tools.RAG.retrievers.milvus_retriever.MilvusRetriever.search') as mock_milvus:
                yield {
                    'shopify': mock_shopify,
                    'hubspot': mock_hubspot,
                    'milvus': mock_milvus
                }

@pytest.fixture(scope="function")
def clean_database():
    """Provide clean database for each test."""
    # Setup clean database
    yield
    # Cleanup after test

# Test utilities
class TestUtils:
    @staticmethod
    def create_mock_response(content: str, status_code: int = 200) -> Mock:
        """Create a mock response object."""
        mock_response = Mock()
        mock_response.content = content
        mock_response.status_code = status_code
        return mock_response
    
    @staticmethod
    def assert_response_structure(response: Dict[str, Any]):
        """Assert that response has expected structure."""
        assert isinstance(response, dict)
        assert "status" in response
        assert "response" in response
    
    @staticmethod
    def assert_error_response(response: Dict[str, Any], expected_error: str):
        """Assert that response contains expected error."""
        assert "error" in response
        assert expected_error.lower() in response["error"].lower()
```

#### Test Parallelization Configuration

```python
# pytest.ini improvements
[pytest]
# Existing configuration...

# Parallel testing
addopts = 
    --verbose
    --cov=arklex
    --cov-report=term-missing
    --cov-report=html
    --no-cov-on-fail
    -n auto  # Enable parallel testing
    --dist=loadfile  # Distribute tests by file

# Test markers for parallel execution
markers =
    unit: marks tests as unit tests (fast)
    integration: marks tests as integration tests (slower)
    performance: marks tests as performance tests (very slow)
    security: marks tests as security tests
    slow: marks tests as slow running tests

# Test grouping
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*

# Parallel execution groups
# Unit tests can run in parallel
# Integration tests should run sequentially
# Performance tests should run in isolation
```

## 7. Test Reporting and Monitoring

### Current Issues

- **Limited Test Reporting**: Basic test reporting only
- **No Test Metrics**: No test performance metrics
- **Missing Test Documentation**: Test documentation incomplete

### Proposed Solutions

#### Enhanced Test Reporting

```python
# tests/utils/test_reporter.py
import json
import time
from typing import Dict, List, Any
from datetime import datetime

class TestReporter:
    def __init__(self):
        self.test_results = []
        self.start_time = None
    
    def start_test_session(self):
        """Start a test session."""
        self.start_time = time.time()
        self.test_results = []
    
    def record_test_result(self, test_name: str, status: str, duration: float, 
                          error: str = None, metadata: Dict[str, Any] = None):
        """Record a test result."""
        result = {
            "test_name": test_name,
            "status": status,
            "duration": duration,
            "timestamp": datetime.utcnow().isoformat(),
            "error": error,
            "metadata": metadata or {}
        }
        self.test_results.append(result)
    
    def generate_report(self) -> Dict[str, Any]:
        """Generate comprehensive test report."""
        if not self.start_time:
            return {"error": "No test session started"}
        
        total_duration = time.time() - self.start_time
        passed_tests = [r for r in self.test_results if r["status"] == "passed"]
        failed_tests = [r for r in self.test_results if r["status"] == "failed"]
        
        return {
            "summary": {
                "total_tests": len(self.test_results),
                "passed_tests": len(passed_tests),
                "failed_tests": len(failed_tests),
                "success_rate": len(passed_tests) / len(self.test_results) if self.test_results else 0,
                "total_duration": total_duration
            },
            "test_results": self.test_results,
            "performance_metrics": self._calculate_performance_metrics(),
            "coverage_metrics": self._calculate_coverage_metrics()
        }
    
    def _calculate_performance_metrics(self) -> Dict[str, Any]:
        """Calculate performance metrics from test results."""
        durations = [r["duration"] for r in self.test_results]
        return {
            "average_duration": sum(durations) / len(durations) if durations else 0,
            "max_duration": max(durations) if durations else 0,
            "min_duration": min(durations) if durations else 0
        }
    
    def _calculate_coverage_metrics(self) -> Dict[str, Any]:
        """Calculate coverage metrics."""
        # This would integrate with coverage.py
        return {
            "line_coverage": 0.95,  # Placeholder
            "branch_coverage": 0.90,  # Placeholder
            "function_coverage": 0.98  # Placeholder
        }
```

## 8. Implementation Priority

### High Priority (Immediate - 1-2 weeks)

1. **Complete UI Component Testing**
2. **Error Path Testing Implementation**
3. **Performance Testing Framework**
4. **Test Infrastructure Improvements**

### Medium Priority (1-2 months)

1. **Property-Based Testing Implementation**
2. **Enhanced Integration Testing**
3. **Test Parallelization**
4. **Comprehensive Test Reporting**

### Low Priority (3-6 months)

1. **Advanced Performance Testing**
2. **Security Testing Integration**
3. **Test Documentation**
4. **Continuous Test Monitoring**

## 9. Success Metrics

- [ ] 100% test coverage for all active code
- [ ] All UI components have working tests (no TODO placeholders)
- [ ] Performance benchmarks established and tracked
- [ ] Error paths thoroughly tested
- [ ] Property-based testing implemented for data validation
- [ ] Integration tests cover all critical workflows
- [ ] Test execution time under 10 minutes
- [ ] Parallel test execution implemented
- [ ] Comprehensive test reporting and monitoring
