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Architecture Documentation

This section contains technical architecture documentation for the BGSTM framework and its supporting systems.

Available Documentation

Data Model for AI Requirement-Test Case Linking

Comprehensive documentation of the data model that supports AI-powered requirement-to-test case traceability linking.

Contents: - Entity Relationship Diagrams (ERD) with detailed field specifications - Core entity documentation (Requirement, TestCase, Link, LinkSuggestion) - Design principles (Traceability, AI-Ready, Audit Trail, Flexibility) - AI integration points (embeddings, scoring, suggestion workflow) - Data flow diagrams (manual links, AI suggestions, traceability matrix) - Common queries and use cases with SQL and SQLAlchemy examples - Validation rules and constraints - Migration strategies and evolution patterns - Performance considerations and optimization strategies - Code examples and reference implementation

Key Features: - ✅ Supports both PostgreSQL and SQLite - ✅ Flexible JSONB fields for custom metadata - ✅ AI-ready with embedding storage and confidence scoring - ✅ Complete audit trails for compliance - ✅ Optimized for large-scale datasets (1M+ records)

Future Architecture Documentation

Additional architecture documentation will be added as the BGSTM framework evolves:

  • API Architecture: RESTful API design and endpoints
  • Frontend Architecture: Web and mobile application architecture
  • AI/ML Pipeline: Machine learning pipeline for link suggestions
  • Integration Architecture: External system integrations (Jira, Azure DevOps, TestRail)
  • Security Architecture: Authentication, authorization, and data protection
  • Deployment Architecture: Container orchestration and cloud deployment

Last Updated: February 2026
Maintained By: BGSTM Project Team