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How to Scaffold Compilable Spring Boot from Legacy COBOL

Most legacy modernization efforts fail because they feed raw, monolithic COBOL directly into an LLM. This leads to architectural hallucinations, memory leaks, and Java code that simply does not compile.

GitGalaxy flips this paradigm. It uses deterministic mathematical parsing to generate a structurally perfect, 100% Maven-compilable Java Spring Boot architecture first. It maps the memory, wires the REST controllers, and builds the configuration files without human or AI intervention.

Once the scaffolding is perfectly compiled, GitGalaxy delegates the highly specific, isolated internal business logic to LLM agents via strict JSON job tickets, ensuring zero architectural drift.

The Java Translation Controller

The cobol_to_java_controller.py ingests the JSON Intermediate Representation (IR) generated by the GitGalaxy COBOL Refractor and orchestrates a suite of specialized Java Forges.

1. Execute the Spring Boot Forge

Point the controller at the _gitgalaxy_clean directory generated during the initial COBOL refraction phase.

python gitgalaxy/tools/cobol_to_java_controller.py /path/to/legacy_repo_gitgalaxy_clean_20260419 --pkg "com.enterprise.modernized"

2. The Deterministic Translation Pipeline

The engine rapidly constructs a modern microservice architecture through five distinct, deterministic forges:

  1. The Build System Forge: Auto-generates a production-ready Maven pom.xml, a Spring Boot application.yml (configured for PostgreSQL), and the Main Application class.
  2. The Entity & Memory Forge: Translates complex COBOL byte-maps into strict JPA @Entity classes. It perfectly translates decimal precision, arrays (OCCURS into List<>), and creates transient aliases for memory overlays (REDEFINES).
  3. The API Contract Forge: Detects batch vs. transactional paradigms and generates modern @RestController endpoints, auto-wiring them to newly minted @Service layers.
  4. The EBCDIC Decoder Forge: Automatically generates the EbcdicDecoderUtil necessary to read raw mainframe byte streams. It includes strict hex-boundary validations to safely unpack legacy COMP-3 (Packed Decimal) data without runtime crashes.
  5. The Mock Service Shield: If the legacy code calls an external mainframe subsystem that hasn't been migrated yet, the engine generates a dummy @Service interface. This allows the Spring Context to load successfully without crashing due to missing dependencies.

3. Review the Audit Report

Because the architecture is deterministically generated, the output is guaranteed to compile. 

==========================================================
 GITGALAXY JAVA SPRING BOOT MIGRATION AUDIT
==========================================================
  • Source Clean Room         : legacy_repo_gitgalaxy_clean_20260419
  • Target Artifact           : legacy_repo
  • Target Package            : com.enterprise.modernized
  • Corporate Header Applied  : Yes

[1] GENERATED CLOUD SCAFFOLDING
----------------------------------------------------------
  • Build & Config Files Forged : 4
  • JPA Entities Generated      : 18
  • REST Controllers Generated  : 12
  • AI Agent Tickets Generated  : 45
==========================================================

You can immediately navigate into the output directory and run mvn clean compile. The system will build successfully on the first try.

4. The AI Boundary (Agent Task Forge)

Instead of asking an LLM to "rewrite this COBOL file in Java," GitGalaxy bounds the AI mathematically.

The Agent Task Forge extracts isolated business rules from the legacy monolith and packages them into strict JSON job tickets (06_ai_agent_jobs/XYZ_java_service_job.json). The LLM is dispatched purely as a logic translator. It is instructed to fill in the pre-wired methods inside the generated @Service classes, strictly utilizing the DTOs and database entities that GitGalaxy has already proven are structurally sound.

5. Stress Testing at Scale

To prove this pipeline works across diverse legacy codebases without human intervention, GitGalaxy includes a Batch Test Harness.

You can point the harness at a directory containing dozens of distinct legacy repositories. It will orchestrate the Refractor, execute the Java Forge, inject a Java 17 environment, and run the Maven compiler across all of them automatically, capturing granular error logs to mathematically prove the success rate of the deterministic scaffolding.

Read the full technical specifications: > * Spring Boot Scaffolding * Entity & Memory Mapping