Hashing Techniques Analysis

This project implements and analyzes various hashing techniques in C and provides visual insights into their performance at different load factors using bar plots.

Hashing Techniques Implemented

The project implements the following hashing techniques:

• Chaining: Chaining is a collision resolution method where each hash table slot stores a linked list of key-value pairs.

• Linear Probing: Linear probing is a collision resolution method that involves probing linearly for the next available slot when a collision occurs.

• Double Hashing: Double hashing is a collision resolution method that uses a secondary hash function to calculate the next slot to probe when a collision occurs.

Analysis

The project analyzes these hashing techniques with different load factors and visualizes the results in a bar plot. Load factors considered are 0.25, 0.5, 0.75, and 1. The analysis includes:

• Average search counts for different load factors and hashing techniques.
• Comparisons between the three hashing techniques in terms of search performance.

Getting Started

To run and analyze the hashing techniques:

1. Compile and run the provided C code to generate a CSV file (Hashing.csv) containing the search counts.
2. Use the Python script in this repository to create bar plots for analysis.

Dependencies

This project utilizes the following Python libraries:

• pandas
• numpy
• matplotlib

Install these libraries using pip:

pip install pandas numpy matplotlib

Plotted Graph-