# Alloy Language Interpreter Test Suite

A comprehensive unit test suite for the Alloy language interpreter that systematically tests all implemented language features.

## 📁 Test Files Overview

### 1. `test_alloy_features.py` - Main Comprehensive Tests
**Purpose**: Tests all core language features with execution
**Coverage**:
- ✅ Variable assignment (basic, reassignment, computed values)
- ✅ Primitive types (strings, numbers, booleans, arrays, objects)
- ✅ Arithmetic and comparison operations
- ✅ Control flow (when/then/otherwise, for loops, while loops)
- ✅ Tool system (definition, calling, parameters, return values)
- ✅ Agent system (clean syntax, commands, blocks, built-in alloy agent)
- ✅ Tuple assignment (Result pattern for error handling)
- ✅ Complex integration scenarios
- ✅ Edge cases and boundary conditions

**Mock System**: Uses `MockInterpreter` class to avoid real API calls during testing.

### 2. `test_parser_only.py` - Pure Syntax Tests
**Purpose**: Tests parsing and AST generation without execution
**Coverage**:
- ✅ Basic syntax parsing (assignments, literals, expressions)
- ✅ Tool definition syntax
- ✅ Control flow syntax
- ✅ Clean agent definition syntax
- ✅ Agent command and block syntax
- ✅ Tuple assignment syntax
- ✅ AST structure validation
- ✅ Complex nested structures

**Focus**: Grammar validation and parser correctness.

### 3. `test_error_cases.py` - Error Handling Tests
**Purpose**: Tests error conditions and graceful failure handling
**Coverage**:
- ✅ Syntax errors (unclosed strings, mismatched braces)
- ✅ Runtime errors (undefined variables, tools, agents)
- ✅ Type errors and invalid operations
- ✅ Agent API failures and missing configuration
- ✅ Variable scoping errors
- ✅ Result pattern error handling
- ✅ Edge cases (empty inputs, large data, special characters)

**Philosophy**: Ensure robust error handling and prevent crashes.

### 4. `test_examples.py` - Specification Examples
**Purpose**: Tests real-world usage scenarios from the language specification
**Coverage**:
- ✅ All primitive type examples from spec
- ✅ Tool definition and usage examples
- ✅ Control flow examples
- ✅ Agent system examples (definitions, commands, blocks)
- ✅ Complete program examples (data processing pipeline, research assistant)
- ✅ Result pattern examples
- ✅ Mixed deterministic/AI workflows

**Realistic Mocking**: Uses sophisticated mocks that return realistic responses based on command context.

### 5. `run_all_tests.py` - Test Runner
**Purpose**: Orchestrates test execution and provides comprehensive reporting
**Features**:
- ✅ Colored output with emoji indicators
- ✅ Detailed test results and timing
- ✅ Comprehensive test report generation
- ✅ Option to run specific test modules
- ✅ Quick validation before running full suite
- ✅ Detailed failure reporting

## 🚀 Running the Tests

### Run All Tests
```bash
python run_all_tests.py
```

### Run Specific Test Modules
```bash
python run_all_tests.py parser    # Parser tests only
python run_all_tests.py features  # Core features tests
python run_all_tests.py errors    # Error handling tests
python run_all_tests.py examples  # Specification examples
```

### Run Individual Test Files
```bash
python test_alloy_features.py     # Main feature tests
python test_parser_only.py        # Parser-only tests
python test_error_cases.py        # Error handling tests
python test_examples.py           # Specification examples
```

### Validate Test Setup
```bash
python validate_tests.py          # Check if tests are set up correctly
```

## 📊 Test Structure

Each test follows this pattern:
```python
def test_feature_name(self):
    """Test description"""
    code = '''
    # Alloy code here
    '''
    
    # Parse test
    ast = parser.parse(code)
    self.assertIsNotNone(ast)
    
    # Execution test
    interpreter = Interpreter()
    interpreter.interpret(ast)
    
    # Validation
    result = interpreter.global_env.get('expected_variable')
    self.assertEqual(result, expected_value)
```

## 🎭 Mock System

### MockInterpreter Class
- Extends the real `Interpreter` class
- Overrides `execute_agent()` to return predictable responses
- Avoids real API calls while maintaining realistic behavior
- Returns contextual responses based on agent commands and blocks

### Mock Response Strategy
- **Analysis commands**: Return structured data with insights and statistics
- **Research commands**: Return findings, sources, and recommendations  
- **Formatting commands**: Return formatted content
- **Agent blocks**: Return responses based on must/should statements
- **Error simulation**: Can simulate API failures and missing configuration

## 🔍 Test Categories

### Happy Path Tests
- ✅ Everything works as expected
- ✅ Valid syntax parses correctly
- ✅ Valid programs execute successfully
- ✅ Expected results are produced

### Error Scenario Tests
- ✅ Invalid syntax produces appropriate errors
- ✅ Runtime errors are handled gracefully
- ✅ Agent failures are managed properly
- ✅ Missing dependencies are detected

### Edge Case Tests
- ✅ Boundary conditions (empty inputs, large data)
- ✅ Special characters and unicode
- ✅ Deeply nested structures
- ✅ Mixed type operations

### Integration Tests
- ✅ Complete Alloy programs work end-to-end
- ✅ Multiple language features work together
- ✅ Realistic usage scenarios
- ✅ Tool and agent interactions

## 📈 Coverage Areas

### Core Language Features
- [x] Variable assignment and scoping
- [x] Primitive types and literals
- [x] Basic operations (arithmetic, comparison)
- [x] Control flow structures
- [x] Tool definition and calling
- [x] Error handling patterns

### Agent System
- [x] Clean agent definition syntax
- [x] Agent command execution
- [x] Agent blocks with must/should semantics
- [x] Built-in alloy agent
- [x] Tool validation for agents

### Advanced Features
- [x] Tuple assignment (Result pattern)
- [x] Error propagation
- [x] Complex data structures
- [x] Nested expressions and statements

### Error Handling
- [x] Syntax error recovery
- [x] Runtime error handling
- [x] API failure management
- [x] Graceful degradation

## 🎯 Success Criteria

### Technical Validation
- [x] Complete programs parse and execute correctly
- [x] AI agents integrate seamlessly with deterministic code
- [x] Error handling works consistently
- [x] All language features are properly tested

### Quality Assurance
- [x] Tests are comprehensive and systematic
- [x] Mock system provides realistic testing environment
- [x] Edge cases and error conditions are covered
- [x] Specification compliance is verified

## 🔧 Extending the Test Suite

### Adding New Tests
1. Choose the appropriate test file based on the feature
2. Follow the established naming convention: `test_feature_description`
3. Include both positive and negative test cases
4. Add comprehensive docstrings
5. Use the helper methods for common operations

### Adding New Test Categories
1. Create a new test file following the naming pattern
2. Import it in `run_all_tests.py`
3. Add it to the test modules list
4. Update this README

### Mock Enhancements
1. Extend `MockInterpreter` for new agent behaviors
2. Add realistic response patterns for new commands
3. Simulate error conditions appropriately
4. Maintain consistency with real API responses

## 📝 Test Documentation

Each test includes:
- **Clear description** of what it tests
- **Expected behavior** specification
- **Setup requirements** if any
- **Comments** explaining complex test logic
- **Assertions** that validate expected outcomes

## 🏗️ Architecture

```
test_alloy_features.py     # Main comprehensive tests
├── MockInterpreter        # Mock system for agent testing
├── Core Language Tests    # Variables, types, operations
├── Tool System Tests      # Tool definition and calling
├── Agent System Tests     # Agent definitions and commands
├── Control Flow Tests     # Conditionals and loops
└── Integration Tests      # Complex scenarios

test_parser_only.py        # Pure syntax validation
├── Basic Syntax Tests     # Assignments, literals
├── Tool Definition Tests  # Tool syntax parsing
├── Control Flow Tests     # Control structure syntax
├── Agent Syntax Tests     # Agent definition syntax
└── AST Structure Tests    # AST validation

test_error_cases.py        # Error handling validation
├── Syntax Error Tests     # Invalid syntax handling
├── Runtime Error Tests    # Execution error handling
├── Agent Error Tests      # Agent failure handling
└── Edge Case Tests        # Boundary conditions

test_examples.py           # Specification compliance
├── Basic Examples         # Simple feature examples
├── Tool Examples          # Tool usage examples
├── Agent Examples         # Agent usage examples
└── Complete Programs      # End-to-end examples

run_all_tests.py           # Test orchestration
├── Test Discovery         # Find and load tests
├── Test Execution         # Run tests with reporting
├── Result Analysis        # Analyze and report results
└── Error Reporting        # Detailed failure analysis
```

## 🌟 Benefits

### For Development
- **Regression Prevention**: Catch breaking changes early
- **Feature Validation**: Ensure new features work correctly
- **Refactoring Safety**: Safely modify code with confidence
- **Documentation**: Tests serve as living documentation

### For Quality
- **Comprehensive Coverage**: All language features tested
- **Edge Case Handling**: Boundary conditions validated
- **Error Resilience**: Robust error handling verified
- **Specification Compliance**: Implementation matches spec

### For Maintenance
- **Automated Validation**: Quick verification of changes
- **Clear Feedback**: Detailed reporting of issues
- **Incremental Testing**: Run specific test subsets
- **Future-Proof**: Foundation for testing new features

---

This test suite provides a solid foundation for ensuring the Alloy language interpreter works correctly and will continue to work as new features are added.