DFG Demo Lab

Deterministic Fragment Graph Demonstration
Visual proof of graph-based data fragmentation and reconstruction

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Deterministic Fragment Graph

DFG Demo Lab demonstrates the concept of a Deterministic Fragment Graph (DFG).

Instead of treating data as a fragile single file, DFG models data as a graph of deterministic fragments that can be reconstructed even when fragments are lost.

Traditional systems
→ files stored as continuous blocks

DFG model
→ data represented as a recoverable graph

This repository provides a visual and interactive explanation of that concept.

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System Overview

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Live Demo Preview

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Why This Matters

Modern data systems face critical challenges:

• file corruption
• distributed storage failures
• fragmented infrastructure
• unreliable recovery systems

DFG introduces a different model:

Data is represented as nodes in a deterministic fragment graph, enabling reconstruction even when fragments are missing.

Key advantages

✔ resilient data representation
✔ recoverable graph structures
✔ deterministic reconstruction
✔ visual verification of integrity

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🚀 60-Second Quickstart

Clone the repository.

git clone https://github.com/raajmandale/dfg-demo-lab.git
cd dfg-demo-lab

Open the interactive demo:

docs/interactive/dfg_live_demo.html

No installation required.
The demo runs directly in your browser.

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🧠 Architecture

The system models data as a Deterministic Fragment Graph (DFG).

Component	Responsibility
Fragment Node	represents deterministic fragment
Graph Structure	connects fragments
Loss Model	simulates fragment loss
Reconstruction Engine	restores graph integrity

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🔗 Fragment Graph Example

Example fragment relationships:

Data
 ↓
Fragment Nodes
 ↓
Graph Links
 ↓
Recoverable Structure

Each node participates in reconstruction logic.

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⚙️ Reconstruction Flow

Recovery pipeline:

Fragments
 ↓
Graph Mapping
 ↓
Integrity Check
 ↓
Reconstruction
 ↓
Recovered Data

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🖥 Interactive Graph Demo

This repository includes a live browser demo.

Open locally:

docs/interactive/dfg_live_demo.html

Or view on GitHub:

https://github.com/raajmandale/dfg-demo-lab/blob/main/docs/interactive/dfg_live_demo.html

Demo capabilities:

• create deterministic fragment graph
• simulate fragment loss
• reconstruct graph integrity
• visualize node state transitions

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📊 Visual Report

Open locally:

docs/report/dfg_visual_report.html

GitHub preview:

https://github.com/raajmandale/dfg-demo-lab/blob/main/docs/report/dfg_visual_report.html

Report includes:

• fragmentation process
• graph structure
• reconstruction timeline
• integrity validation

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📂 Project Structure

dfg-demo-lab
│
├ docs
│  ├ svg
│  │  ├ fragment_graph.svg
│  │  ├ fragment_loss.svg
│  │  ├ memory_graph.svg
│  │  └ reconstruction_flow.svg
│  │
│  ├ report
│  │  └ dfg_visual_report.html
│  │
│  └ interactive
│     └ dfg_live_demo.html
│
├ examples
│
└ README.md

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🔬 What This Demonstrates

DFG Demo Lab demonstrates how:

• data can be modeled as graphs
• graph structures enable recovery
• deterministic fragments improve resilience
• visual models simplify complex systems

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🗺 Roadmap

Current stage

v0 — DFG visualization demo

Next stages

v1 — fragment engine prototype
v2 — reconstruction algorithm
v3 — distributed fragment graph
v4 — production storage integration

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📊 Status

Research / demonstration repository.

This project focuses on concept clarity and visualization, not production storage.

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👤 Author

Raaj Mandale
Founder — ERANEST Technoware Pvt Ltd

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📄 License

MIT License

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📚 Citation

@software{mandale_dfg_demo_2026,
  author  = {Raaj Mandale},
  title   = {Deterministic Fragment Graph Demo Lab},
  year    = {2026},
  url     = {https://github.com/raajmandale/dfg-demo-lab},
  version = {v0.1}
}