Understanding Legacy Code Through Graphs
When migrating a legacy application, understanding the full dependency landscape is the single most critical step. A missed dependency can cascade into runtime failures, broken business logic, or silent data corruption.
PhoenixCode builds a comprehensive Knowledge Graph using Neo4j to map every relationship in your codebase: form-to-unit dependencies, database table references, API call chains, shared global state, and implicit coupling through naming conventions.
What the Graph Captures
Our graph schema models 12 node types and 18 relationship types:
- Nodes: Files, Classes, Methods, Properties, Database Tables, Stored Procedures, Forms, Components, Services, Routes, APIs, Business Rules
- Relationships: DEPENDS_ON, CALLS, INHERITS, IMPLEMENTS, READS_FROM, WRITES_TO, RENDERS, ROUTES_TO, VALIDATES, TRANSFORMS, TRIGGERS, CONTAINS
How It Enables Migration
With the full graph in place, the migration pipeline can:
- Determine the optimal migration order (leaf nodes first, high-coupling nodes last)
- Identify circular dependencies that need refactoring before migration
- Map business rules to their implementation locations across forms, units, and stored procedures
- Generate accurate effort estimates based on graph complexity metrics
The Result
Instead of guessing what depends on what, PhoenixCode gives you a complete, queryable map of your legacy system. This is what makes our 74-step pipeline deterministic rather than probabilistic.