How we used FalkorDB, Graph Theory (WCC, Betweenness, PageRank), and Multi-Agent simulation to catch breaking ecosystem changes before merge

Description and use

ShadowGraph uses FalkorDB and graph algorithms to detect and prevent breaking changes in Home Assistant integrations, enabling developers to catch issues before merging.

Problem

A refactor that moved sensor entity classes into a separate module broke 32 custom integrations that depended on internal symbols, risking runtime failures for users.

Outcome

ShadowGraph enabled early detection of 32 integration breakages, provided migration patches, and extended impact analysis beyond core tests.

Workflow

• Build dependency graph via Python AST analysis
• Create isolated graph copy in FalkorDB
• Simulate removal/change of symbols
• Identify integrations that fail during import vs. runtime
• Use AI agents to verify potential breakages
• Generate draft patches for maintainers

Evidence

32 custom integrations depended on internal symbols that the refactor stopped exposing.

Source

ShadowGraph helps developers understand the impact of a code change before merging it.

Source