## REMOVED Requirements
### Requirement: Unreachable Dead Code
Unreachable code blocks after return statements SHALL be removed from `plan_source_processing` and `_create_empty_source_result` functions.

#### Scenario: Dead code removal in plan_source_processing
- **GIVEN** `plan_source_processing` function with unreachable code after line 586
- **WHEN** lines 588-618 are examined
- **THEN** the unreachable block SHALL be completely removed
- **AND** function SHALL only contain reachable, functional code

#### Scenario: Dead code removal in _create_empty_source_result
- **GIVEN** `_create_empty_source_result` function with unreachable code after line 820
- **WHEN** lines 822-852 are examined
- **THEN** the unreachable block SHALL be completely removed
- **AND** undefined variable references SHALL be eliminated

## MODIFIED Requirements
### Requirement: Performance Optimization for Key Matching
The `select_rows_by_keys_common` function SHALL use O(1) set-based key lookup instead of O(n) list membership check.

#### Scenario: Single column key matching improvement
- **GIVEN** single column key matching with 1M+ rows
- **WHEN** `select_rows_by_keys_common` is called with large key_set
- **THEN** O(1) set lookup SHALL be used instead of O(n) list lookup
- **AND** performance SHALL improve by 10-100x for large datasets

#### Scenario: Multi-column key matching improvement
- **GIVEN** multi-column key matching with large datasets
- **WHEN** `select_rows_by_keys_common` processes composite keys
- **THEN** efficient set-based operations SHALL be used
- **AND** redundant single-column checks SHALL be removed

### Requirement: SQL Injection Protection
File paths SHALL be validated before SQL interpolation in DuckDB methods to prevent injection attacks.

#### Scenario: Path validation prevents injection
- **GIVEN** DuckDB method processing file paths
- **WHEN** a path contains malicious SQL characters (`'`, `--`, `;`)
- **THEN** ValueError SHALL be raised with clear error message
- **AND** dangerous paths SHALL be rejected before SQL execution

#### Scenario: Safe path processing
- **GIVEN** DuckDB method processing legitimate file paths
- **WHEN** paths contain only safe characters
- **THEN** normal processing SHALL continue
- **AND** no false positives SHALL be triggered

### Requirement: Architecture Consistency
DuckDB backend SHALL inherit from BaseDatasetHandler as specified in the design document.

#### Scenario: DuckDB inherits from base class
- **GIVEN** DuckDB dataset operations
- **WHEN** class structure is examined
- **THEN** `DuckDBDatasetIO` SHALL inherit from `BaseDatasetHandler`
- **AND** duplicated methods SHALL be removed in favor of inherited implementations

#### Scenario: Abstract method implementation
- **GIVEN** DuckDB backend inheriting from BaseDatasetHandler
- **WHEN** abstract methods are called
- **THEN** all required abstract methods SHALL be properly implemented
- **AND** filesystem property SHALL return the connection filesystem

## ADDED Requirements
### Requirement: Standardized Exception Handling
Exception handling SHALL use specific exception types and proper logging instead of broad `except Exception`.

#### Scenario: Specific exception handling
- **GIVEN** operations that may fail with known exception types
- **WHEN** errors occur during processing
- **THEN** specific exception types SHALL be caught instead of broad Exception
- **AND** proper logging SHALL be included with context information

#### Scenario: Graceful error recovery
- **GIVEN** operations that encounter recoverable errors
- **WHEN** specific exceptions are caught
- **THEN** appropriate fallback behavior SHALL be executed
- **AND** meaningful error messages SHALL be logged

### Requirement: Import Pattern Standardization
PyArrow imports SHALL follow consistent TYPE_CHECKING patterns across the codebase.

#### Scenario: Consistent import patterns
- **GIVEN** functions using PyArrow functionality
- **WHEN** import statements are examined
- **THEN** consistent TYPE_CHECKING imports SHALL be used
- **AND** local imports SHALL be eliminated in favor of module-level imports

## VALIDATION Requirements
### Requirement: Functional Correctness Verification
All fixes SHALL maintain functional correctness while resolving identified issues.

#### Scenario: Unit test validation
- **GIVEN** fixed functions with unit tests
- **WHEN** tests are executed
- **THEN** all tests SHALL pass without modifications
- **AND** no regressions SHALL be introduced

#### Scenario: Integration test validation
- **GIVEN** both PyArrow and DuckDB backends
- **WHEN** integration tests are executed
- **THEN** both backends SHALL produce identical results
- **AND** performance improvements SHALL be measurable

#### Scenario: Performance validation
- **GIVEN** large datasets for key matching operations
- **WHEN** performance benchmarks are run
- **THEN** key matching SHALL show measurable performance improvement
- **AND** memory usage SHALL not increase significantly

#### Scenario: Security validation
- **GIVEN** malicious file path scenarios
- **WHEN** path validation is tested
- **THEN** dangerous paths SHALL be rejected
- **AND** legitimate paths SHALL be processed normally