Implement Incremental Knowledge Graph Updates

Problem

Currently, the knowledge graph system performs a complete rebuild of both code mapping and inference generation on any update, regardless of the change magnitude. This approach is computationally expensive and time-consuming, impacting system performance and resource utilization.

Proposed Solution

Develop an incremental update system for the knowledge graph that processes only the changed components rather than rebuilding the entire graph.

Requirements

Core Functionality

• Implement differential analysis to detect and isolate changes between versions
• Create an incremental update mechanism that preserves existing graph structure
• Develop a system to track and maintain relationship integrity during updates

Key Features

1. Change Detection

   • Identify modified, added, and deleted components
   • Determine affected relationships and dependencies
   • Map impact scope of changes

2. Relationship Management

   • Maintain accurate relationship tracking across updates
   • Handle cascading relationship updates
   • Preserve existing relationship metadata

3. Inference Handling

   • Generate inferences only for new/modified components
   • Preserve existing valid inferences
   • Update affected inference chains without full regeneration

4. Performance Optimization

   • Eliminate full graph reconstruction
   • Minimize parsing operations to affected components only
   • Optimize resource usage during updates

Technical Considerations

• Must maintain data consistency throughout incremental updates
• Need to implement versioning/tracking for incremental changes
• Requires robust error handling for partial updates
• Should include rollback capability for failed updates