Edge Cases & Other Features - Miscellaneous Functionality

[mathiasrw]

Priority: 5-7 (Low)
Impact: Vendor-Specific Extensions
Test Files: Various test files covering edge cases and miscellaneous features
Test Count: 79 tests

Problem Description

Multiple test files contain skipped tests for edge cases, error handling, and miscellaneous AlaSQL features that don't fit into other categories. These include special scenarios, boundary conditions, and unique functionality that enhances robustness and completeness.

Specific Test Cases

Edge Cases and Error Handling

• Boundary Conditions: Empty datasets, null values, extreme numbers
• Error Scenarios: Invalid syntax, type mismatches, constraint violations
• Memory Limits: Large result sets, memory pressure scenarios
• Data Type Edge Cases: Unicode, special characters, type conversions

Miscellaneous Features

• Advanced Functions: Complex expressions and calculations
• Special Syntax: AlaSQL-specific extensions and shortcuts
• Compatibility Features: Cross-database compatibility
• Utility Functions: Helper functions and convenience features

Performance Edge Cases

• Large Datasets: Performance with millions of records
• Complex Queries: Nested queries and deep recursion
• Memory Management: Efficient resource usage
• Concurrency: Multi-user scenarios

Expected Behavior

AlaSQL should handle edge cases and provide:

1. Robust Error Handling: Graceful failure and clear error messages
2. Boundary Condition Support: Handle empty, null, and extreme values
3. Memory Efficiency: Manage large datasets without crashes
4. Type Safety: Proper type conversion and validation
5. Feature Completeness: Support for advanced and edge-case scenarios

Current Status

• Test Status: All skipped (it.skip)
• Error: Unknown (tests not executed)
• Root Cause: Edge cases and miscellaneous features not fully implemented

Implementation Requirements

1. Error Handling System

Implement comprehensive error handling:

-- Graceful error handling
TRY {
    SELECT * FROM table WHERE column = 'invalid';
} CATCH (error) {
    -- Handle error appropriately
}

-- Type validation
SELECT CAST('invalid' AS INTEGER); -- Should handle gracefully
SELECT CONVERT('text' AS NUMBER);   -- Proper error reporting

-- Constraint validation
INSERT INTO table (required_column) VALUES (NULL); -- Clear error message

2. Boundary Condition Support

• Empty Datasets: Handle queries on empty tables
• Null Values: Proper NULL handling in all operations
• Extreme Values: Very large/small numbers, long strings
• Unicode Support: Full UTF-8 and special character support

3. Memory Management

• Large Result Sets: Stream processing for big data
• Memory Limits: Detect and handle memory pressure
• Garbage Collection: Optimize object lifecycle
• Resource Cleanup: Proper cleanup of resources

4. Type System Enhancements

• Type Conversion: Safe and explicit type casting
• Type Validation: Runtime type checking
• Custom Types: Support for user-defined types
• Precision Handling: Decimal and floating-point precision

5. Advanced Functionality

• Complex Expressions: Nested functions and calculations
• Recursive Queries: Handle deep recursion safely
• Dynamic SQL: Runtime query generation
• Meta-programming: Query introspection and manipulation

AlaSQL-Specific Features Involved

• Advanced error handling and reporting
• Boundary condition processing
• Memory optimization techniques
• Type system enhancements
• Miscellaneous utility functions
• Edge case handling algorithms

Dependencies

• AlaSQL parser (src/alasqlparser.jison)
• Error handling system
• Type validation engine
• Memory management system
• Query execution engine

Acceptance Criteria

Error Handling (25 tests)

• All error handling tests enabled and passing
• Graceful failure for invalid syntax
• Clear error messages for type mismatches
• Constraint violation handling
• Runtime error recovery
• Debug information provision

Boundary Conditions (20 tests)

• All boundary condition tests enabled and passing
• Empty dataset handling
• NULL value processing
• Extreme number handling
• Unicode and special character support
• Type edge cases

Memory Management (15 tests)

• All memory management tests enabled and passing
• Large dataset processing
• Memory limit detection
• Resource cleanup
• Garbage collection optimization
• Streaming data processing

Advanced Features (19 tests)

• All advanced feature tests enabled and passing
• Complex expression evaluation
• Recursive query handling
• Dynamic SQL support
• Meta-programming capabilities
• Performance edge cases

Implementation Strategy

Phase 1: Error Handling Foundation

1. Error Detection: Comprehensive error identification
2. Error Reporting: Clear and helpful error messages
3. Graceful Degradation: Handle errors without crashes
4. Debug Support: Provide debugging information

Phase 2: Boundary Condition Support

1. Empty Data Handling: Process empty datasets correctly
2. NULL Processing: Consistent NULL value handling
3. Type Safety: Robust type conversion and validation
4. Unicode Support: Full international character support

Phase 3: Memory Optimization

1. Large Data Handling: Stream processing capabilities
2. Memory Monitoring: Detect memory pressure
3. Resource Management: Efficient resource usage
4. Performance Optimization: Memory-efficient algorithms

Phase 4: Advanced Features

1. Complex Expressions: Nested function support
2. Dynamic Capabilities: Runtime query generation
3. Meta-programming: Query introspection
4. Edge Case Coverage: Comprehensive scenario handling

Test Implementation Examples

-- Error handling
SELECT * FROM nonexistent_table; -- Clear error message
INSERT INTO table (col) VALUES (invalid_type); -- Type mismatch error

-- Boundary conditions
SELECT COUNT(*) FROM empty_table; -- Should return 0
SELECT SUM(NULL) FROM table; -- Should handle NULL gracefully
SELECT 1e308 * 1e308; -- Handle overflow

-- Memory management
SELECT * FROM very_large_table; -- Stream processing
SELECT * FROM table WHERE complex_calculation(); -- Efficient evaluation

-- Advanced features
SELECT EVAL('SELECT COUNT(*) FROM ?') AS dynamic_query;
SELECT META('table_name') AS table_info;
SELECT RECURSIVE_CTE('hierarchy_query') AS results;

Performance Considerations

• Error Overhead: Minimal performance impact for error checking
• Memory Efficiency: Optimize for large datasets
• Type Conversion: Fast and safe type operations
• Boundary Handling: Efficient edge case processing
• Resource Usage: Minimal memory footprint

Edge Cases to Handle

Data Edge Cases

• Empty Results: Queries returning no data
• Single Values: Scalar result handling
• Large Numbers: Very big/small numeric values
• Special Characters: Unicode, emojis, special symbols
• Mixed Types: Heterogeneous data handling

Query Edge Cases

• Deep Nesting: Very complex nested queries
• Long Queries: Extremely long SQL statements
• Many Parameters: Queries with many parameters
• Recursive Depth: Deep recursive query limits
• Concurrent Access: Multi-user scenarios

System Edge Cases

• Memory Limits: Running out of memory
• Disk Space: Storage limitations
• Network Issues: Remote database connectivity
• Time Limits: Long-running query timeouts
• Resource Contention: Competing for system resources

Error Categories

Syntax Errors

• Invalid Tokens: Unrecognized SQL syntax
• Malformed Queries: Incomplete or incorrect structure
• Reserved Words: Conflicts with keywords
• Quoting Issues: String and identifier quoting

Runtime Errors

• Type Mismatches: Incompatible data types
• Constraint Violations: Rule violations
• Resource Limits: Memory, disk, or time limits
• Access Errors: Permission or connectivity issues

Logical Errors

• Division by Zero: Mathematical errors
• Null References: Operations on NULL values
• Invalid Operations: Unsupported combinations
• Data Integrity: Consistency violations

Integration Points

• Parser: Syntax error detection and reporting
• Type System: Runtime type validation
• Memory Manager: Resource monitoring and cleanup
• Query Engine: Runtime error handling
• Storage Engine: Data integrity validation

Notes

Edge cases and miscellaneous features are essential for production readiness:

• Robustness: Handle unexpected scenarios gracefully
• Usability: Clear error messages and debugging support
• Performance: Efficient handling of large and complex data
• Compatibility: Support for various data types and scenarios
• Reliability: Consistent behavior across all conditions

These features ensure AlaSQL can handle real-world usage scenarios and provide a professional database experience.