Four-Sided Triangle: Improvement Tasks

This document contains a detailed checklist of actionable improvement tasks for the Four-Sided Triangle project. Tasks are organized by category and logically ordered to ensure efficient implementation.

Architecture and Code Organization

  1. Fix typo in filename: Rename solver_leaning.py to solver_learning.py in the orchestrator module
  2. Standardize module naming conventions across the codebase (e.g., metacognitive_orchestrator.py vs core.py)
  3. Implement consistent error handling strategy across all modules
  4. Create interface documentation for all public APIs
  5. Refactor duplicate code in solver adapters
  6. Implement dependency injection pattern consistently throughout the codebase
  7. Create architectural decision records (ADRs) for major design decisions
  8. Implement configuration validation for all config files
  9. Standardize logging format and levels across all modules

Testing

  1. Implement integration tests for the orchestrator module
  2. Implement integration tests for the solver module
  3. Implement unit tests for all solver adapters
  4. Implement unit tests for the distributed computing components
  5. Set up continuous integration pipeline for automated testing
  6. Implement end-to-end tests for critical user flows
  7. Create test fixtures for common test scenarios
  8. Implement property-based testing for complex algorithms
  9. Add performance benchmarks for critical components

Documentation

  1. Create comprehensive API documentation for all modules
  2. Document configuration options and their effects
  3. Create user guides for common use cases
  4. Document the solver selection algorithm and criteria
  5. Create developer onboarding documentation
  6. Document the distributed computing architecture
  7. Create sequence diagrams for key workflows
  8. Document error codes and troubleshooting steps
  9. Create a glossary of domain-specific terms

Performance Optimization

  1. Profile the application to identify performance bottlenecks
  2. Optimize solver selection algorithm
  3. Implement caching for frequently accessed data
  4. Optimize database queries
  5. Implement asynchronous processing for non-blocking operations
  6. Optimize memory usage in the working memory module
  7. Implement batch processing for large datasets
  8. Optimize frontend rendering performance

Security

  1. Implement input validation for all API endpoints
  2. Add rate limiting to prevent abuse
  3. Implement proper authentication and authorization
  4. Secure sensitive configuration data
  5. Implement HTTPS for all communications
  6. Conduct security audit of third-party dependencies
  7. Implement proper error handling to prevent information leakage
  8. Add security headers to API responses

DevOps and Deployment

  1. Containerize all components for consistent deployment
  2. Implement infrastructure as code for deployment environments
  3. Set up monitoring and alerting for production environment
  4. Implement automated deployment pipeline
  5. Create backup and disaster recovery procedures
  6. Implement health checks for all services
  7. Set up log aggregation and analysis
  8. Implement feature flags for controlled rollout of new features

Frontend Improvements

  1. Implement responsive design for mobile compatibility
  2. Improve accessibility compliance
  3. Implement comprehensive error handling in UI
  4. Add loading indicators for asynchronous operations
  5. Implement client-side validation for forms
  6. Optimize bundle size for faster loading
  7. Implement progressive web app (PWA) capabilities
  8. Add comprehensive user documentation and help system

Data Management

  1. Implement data validation for all input/output operations
  2. Create data migration strategy for schema changes
  3. Implement data versioning for backward compatibility
  4. Optimize data storage for frequently accessed information
  5. Implement data archiving strategy for historical data
  6. Create data backup and recovery procedures

AI and Machine Learning

  1. Implement model versioning for LLM components
  2. Create evaluation metrics for model performance
  3. Implement A/B testing framework for model improvements
  4. Optimize prompt templates for better performance
  5. Implement feedback loop for continuous model improvement
  6. Create fallback mechanisms for model failures
  7. Implement explainability features for model decisions

User Experience

  1. Conduct usability testing and implement improvements
  2. Create user onboarding flow for new users
  3. Implement user feedback collection mechanism
  4. Improve error messages for better user understanding
  5. Create dashboard for system performance monitoring
  6. Implement customizable user preferences
  7. Add visualization tools for complex data

Scalability

  1. Implement horizontal scaling for compute-intensive components
  2. Optimize database schema for scalability
  3. Implement sharding strategy for large datasets
  4. Create load testing framework to identify scalability limits
  5. Implement circuit breakers for fault tolerance
  6. Optimize resource utilization in distributed computing
  7. Implement auto-scaling based on load metrics