Need and Motivation · What It Does · System Features · Setup · Transformation Pipeline · Screenshots
Version: v1.3.3
Status: Functional Prototype
MDD-HQC is a model-driven platform for designing hybrid quantum-classical systems. It transforms iStar 2.0 models into traceable UVL and UML artifacts enriched with QuantumUML stereotypes, with advisory LLM support.
Hybrid quantum-classical (HQC) systems combine classical and quantum components, using each paradigm where it offers the greatest benefit.
The main challenge is one of design: deciding when, where, and how quantum modules should be integrated into classical systems. These decisions are still expert-dependent and weakly traceable from early requirements to architectural decisions.
Without a structured process, hybrid solutions are harder to justify, evaluate, and maintain.
MDD-HQC supports HQC design through a model-driven flow from CIM to PIM and PSM.
Starting from iStar 2.0 goal models, the platform derives traceable UVL and UML artifacts enriched with QuantumUML stereotypes. Each level constrains the next one, narrowing the space of possible solutions and strengthening vertical traceability.
LLM support helps identify information gaps, ambiguities, or misplaced elements during model refinement. It is strictly advisory and never makes decisions on behalf of the user.
The following table summarizes the main capabilities considered in the proposed system.
Status legend: ⬤ implemented, ◐ partial, ◯ not implemented.
| Capability | Status |
|---|---|
| Goal-oriented capture of HQC requirements | ⬤ |
| Interview-based elicitation for CIM modeling | ◐ |
| CIM model generation and refinement | ◐ |
| CIM to PIM transformation | ⬤ |
| PIM to PSM transformation | ⬤ |
| Bidirectional or multi-entry process support | ◯ |
| Variability management for HQC design | ⬤ |
| Vertical traceability across modeling levels | ⬤ |
| Semantic loss assessment across transformations | ◯ |
| Code-oriented downstream generation | ◯ |
| Project analysis from local folders or GitHub repositories | ◯ |
| AI-assisted interpretation and refinement | ◐ |
The following must be installed before starting:
- Docker (version 20.10 or higher)
- Docker Compose (version 2.0 or higher)
- Git (for cloning the repository)
Note
The system is designed to run in containerized environments using Docker Compose for compatibility and ease of deployment.
-
Clone the repository:
git clone [email protected]:JessusTM/MDD-HQC.git cd MDD-HQC
-
Create the backend environment file at the repository root:
cp .env.example .env
-
Create the frontend environment file:
cp mdd-hqc-frontend/.env.example mdd-hqc-frontend/.env
[!NOTE] The backend reads variables from the root
.env, while the React frontend readsREACT_APP_*variables frommdd-hqc-frontend/.env. -
Build and start the services:
docker compose up --build
This command builds the backend and frontend images and starts both services.
-
Access the application:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- API Documentation (Swagger): http://localhost:8000/docs
-
Stop the services:
docker compose down
Caution
Ensure that ports 3000 and 8000 are available on the system before running the containers. If these ports are in use, they can be modified in the docker-compose.yml file.
The system implements a three-level transformation flow:
- CIM (Computation Independent Model): Computation-independent model based on iStar 2.0
- PIM (Platform Independent Model): Platform-independent model using UVL (Universal Variability Language)
- PSM (Platform Specific Model): Platform-dependent model with UML artifacts enriched with QuantumUML stereotypes
Each transformation maintains traceability between levels, allowing elements to be followed from the business model to the platform-specific implementation.
Main interface |
Embedded examples panel |
Guided interaction |
Transformation results |
Editor workflow |
