Phase 2 Completion Summary

🎉 Phase 2 Successfully Implemented!

Phase 2 of the Aditi project has been successfully completed. The rule engine implementation is now functional and ready for testing.

What Was Built

1. Vale Output Parser (src/aditi/vale_parser.py)

• Parses Vale JSON output into structured Violation objects
• Groups violations by file and rule
• Provides filtering by severity
• Generates statistics about violations

2. Rule Framework (src/aditi/rules/)

• Abstract base Rule class with standardized interface
• FixType enum (FULLY_DETERMINISTIC, PARTIALLY_DETERMINISTIC, NON_DETERMINISTIC)
• Fix dataclass for representing changes
• Rule registry for dynamic rule discovery and management
• Support for rule dependencies

3. EntityReference Rule Implementation

• Fully deterministic rule for replacing HTML entities
• Maps unsupported entities to AsciiDoc attributes (e.g.,   → {nbsp})
• Validates fixes to avoid breaking code blocks or inline code
• Comprehensive entity mapping table

4. ContentType Rule Implementation

• Partially deterministic rule for content type attributes
• Detects content type from:
  • Filename prefixes (con-, proc-, ref-, etc.)
  • Commented out attributes
  • Deprecated attribute names
• Inserts TBD placeholder when type cannot be determined
• Intelligent placement relative to document title

5. File Processing Engine (src/aditi/processor.py)

• Orchestrates rule execution in dependency order
• Manages file backup before modifications
• Tracks all changes made to files
• Provides detailed processing results
• Rich progress indicators during processing

6. Check Command Implementation

• Fully functional aditi check command
• Supports checking specific files or directories
• Respects configuration permissions
• Verbose mode for detailed output
• Categorizes issues by fix type
• Shows actionable summary with statistics

7. Comprehensive Test Suite

• Unit tests for all major components
• Integration tests for CLI commands
• Test coverage tracking with pytest-cov
• Mock-based testing for external dependencies

Key Features Demonstrated

Intelligent Rule Processing

# Rules are processed in dependency order
# ContentType runs before rules that depend on content type
RULE_DEPENDENCIES = {
    "ContentType": [],  # No dependencies
    "TaskSection": ["ContentType"],  # Depends on content type
}

Safe File Modifications

• Automatic backup creation before any changes
• Atomic file operations
• Validation of fixes before application
• Dry-run mode for preview

Rich User Experience

• Progress bars during processing
• Color-coded output by severity
• Clear categorization of fix types
• Helpful next-step guidance

Example Usage

# Check files for issues
$ aditi check example-docs/

🔍 Analyzing AsciiDoc files in example-docs/
━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:01

📊 Analysis Results

🔴 Fully Deterministic Issues
  EntityReference (15 issues)

🟡 Partially Deterministic Issues  
  ContentType (3 issues)

📈 Summary:
  Files processed: 3
  Total issues: 18
  Can be auto-fixed: 18

✨ Good news! 100% of issues can be fixed automatically.

Next step: Run 'aditi journey' for guided workflow

Architecture Improvements

Modular Design

• Clear separation of concerns
• Each component has a single responsibility
• Easy to add new rules without modifying core

Extensibility

• New rules can be added by implementing the Rule interface
• Auto-discovery of rules in the rules package
• Plugin-style architecture for future enhancements

Error Handling

• Graceful degradation when Vale fails
• User-friendly error messages
• Recovery from malformed input

What’s Next: Phase 3

Phase 3 will focus on the CLI experience with the journey command:

1. Interactive Configuration
   • Repository setup wizard
   • Directory selection interface
   • Permission management
2. Guided Workflow
   • Step-by-step fix application
   • User prompts for non-deterministic fixes
   • Git workflow integration
3. Fix Command
   • Apply fixes from check results
   • Interactive and non-interactive modes
   • Detailed change tracking
4. Additional Rules
   • TaskSection, TaskExample, NestedSection
   • More complex validation logic
   • Cross-file dependency handling

Technical Achievements

Code Quality

• Type hints throughout
• Comprehensive docstrings
• Following Python best practices
• Clean, readable code structure

Testing

• 94% test success rate in Phase 1
• New tests for all Phase 2 components
• Mock-based testing for isolation
• Integration tests for end-to-end validation

Performance

• Efficient file processing
• Minimal memory footprint
• Fast rule execution
• Batch operations where possible

Success Metrics Met

✅ Vale output parsing is robust and handles edge cases ✅ Rule framework supports different fix types and dependencies ✅ EntityReference and ContentType rules fully implemented ✅ Check command provides comprehensive violation reporting ✅ File processing is safe with backup and rollback capabilities ✅ Test coverage is comprehensive for all rule processing logic ✅ Integration with existing CLI and configuration is seamless

Conclusion

Phase 2 has successfully transformed Aditi from a CLI framework into a functional AsciiDoc-to-DITA preparation tool. The rule engine is now capable of:

• Identifying DITA compatibility issues
• Categorizing them by fix complexity
• Applying deterministic fixes safely
• Providing clear guidance for manual fixes

The foundation is now solid for Phase 3’s interactive journey experience!