🌀 NormFlow – Database Normalization Engine

NormFlow is an interactive tool designed to bridge the gap between database theory and practical implementation. It performs step-by-step normalization from 1NF to BCNF, allowing users to visualize how complex relational schemas decompose into clean, efficient structures.

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🚀 Features

• Attribute Closure Computation: Automatically calculate the closure for any set of attributes.
• Candidate Key Detection: Identify all possible candidate keys for a given relation.
• Minimal Cover Generation: Simplify functional dependencies to their most basic form.
• Multi-Stage Validation: Real-time checks for 1NF, 2NF, 3NF, and BCNF.
• Lossless Join Decomposition: Ensures data integrity is maintained throughout the process.
• Interactive UI: Built with Streamlit for a seamless, web-based user experience.

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🧠 Concepts Implemented

The engine utilizes several core relational database algorithms:

• Functional Dependencies (FDs)
• Key Discovery using attribute closure properties
• Decomposition Logic (resolving transitive and partial dependencies)
• Lossless Join & Dependency Preservation checks

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⚙️ Tech Stack

• Language: Python
• Framework: Streamlit

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🖥️ How It Works

1. Input: Define your attributes (e.g., A, B, C, D) and Functional Dependencies (e.g., A -> B, B -> C).
2. Analyze: The engine computes candidate keys and identifies the current Normal Form.
3. Decompose: If violations are found, the engine triggers a step-by-step decomposition.
4. Result: View the final set of tables that satisfy the target Normal Form.

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▶️ Run Locally

pip install streamlit
streamlit run assignment.py

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📸 Preview

Schema & Key Analysis

Normalization Output (1NF → BCNF)

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📌 Example Use Case

• Analyze a relation with given functional dependencies
• Identify candidate keys
• Automatically normalize step-by-step
• Understand decomposition logic visually

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📚 Learning Value

This project demonstrates:

• Algorithmic Thinking: Implementing discrete math and set theory for attribute closures.
• Database Integrity: Understanding the rigorous requirements of lossless joins.
• Practical Implementation: Translating theoretical concepts into functional code.mplementing discrete math and set theory for attribute closures.
• Database Integrity: Understanding the rigorous requirements of lossless joins.
• Practical Implementation: Translating theoretical concepts into functional code.