Legacy Logic Studio

Legacy Logic Studio — Business Logic Time Machine is a web application for exploring, analyzing, and modernizing legacy business logic. The UI walks through discovery, rule editing, modernization, and reporting, with the loan-approval COBOL system and its Java 17 + Maven counterpart bundled for a consistent end-to-end experience.

Repository layout

Path	Role
frontend/	React + TypeScript + Vite SPA: workflow, COBOL/Java viewers, editor, modernization, PDF report
backend/	FastAPI service: health checks, versioned JSON APIs for the SPA, IBM watsonx.ai integration for AI-assisted modernization
loan-approvals-COBOL/	Legacy COBOL sources, copybooks, and batch inputs used by the UI and parity tests
loan-approval-service/	Modern Java 17 + Maven service aligned with the COBOL rules (build with mvn verify)

Frontend

The SPA is built with Vite and React. It provides:

• Guided workflow — upload and project context, dependency and logic analysis, rule editing with before/after snapshots, modernization preview, and a structured report with optional PDF export.
• Bundled legacy and modern sources — COBOL programs and copybooks from loan-approvals-COBOL/, and Java sources from loan-approval-service/, are exposed to the client as static modules so navigation, search, and side-by-side comparison work without a separate asset server.
• Client-side session state — uploads and in-progress edits are held in the browser (e.g. session storage) so refreshes and multi-step flows stay coherent.

Run locally:

cd frontend
npm install
npm run dev

The dev server defaults to http://localhost:5173 (Vite). Point the SPA at the backend base URL via environment variable when you wire API calls (e.g. VITE_API_BASE_URL=http://127.0.0.1:8000).

Backend

FastAPI backs the SPA with CORS enabled for local Vite origins. The service is structured so the frontend can call stable, versioned endpoints and grow into full modernization orchestration.

Directory structure

backend/
├── requirements.txt
└── app/
    ├── main.py                 # FastAPI app, CORS, router mount
    ├── api/
    │   └── routes.py           # HTTP routes under /api/v1
    ├── schemas/
    │   └── frontend_contracts.py   # Request/response models shared with the SPA
    └── services/
        └── watsonx_modernization.py  # IBM watsonx.ai (Granite / code models) for legacy → modern suggestions

IBM watsonx.ai

Modernization assistance uses IBM watsonx.ai as the model layer: foundation models (for example Granite code-oriented models) interpret COBOL fragments and project context, then produce suggested modern code, explanations, or refactor hints. Configure credentials and project settings via environment variables (see backend/app/services/watsonx_modernization.py and watsonx.ai documentation). Until credentials are set, the API returns a clear configuration response so the UI can still be developed and tested.

API surface (v1)

Method	Path	Purpose
GET	/health	Liveness
GET	/	Service metadata
POST	/api/v1/modernize/suggest	Body: COBOL snippet + options → suggested modern code / stub when watsonx is not configured

Run locally:

cd backend
python -m venv .venv
.venv\Scripts\activate   # Windows
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000

Open http://127.0.0.1:8000/docs for interactive OpenAPI.

Legacy COBOL batch (optional)

From loan-approvals-COBOL/, run the GnuCOBOL batch driver if you want to regenerate golden outputs or validate parity outside the UI.

License

Use and modify under the license terms that apply to your distribution of this repository.