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The Data Structures and Algorithm Analysis repository is a collection of data structures and algorithms implemented in various programming languages. It serves as an educational resource for students, developers, and enthusiasts to understand and master fundamental concepts in computer science.

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Data Structures and Algorithm Analysis

Welcome to the Data Structures and Algorithm Analysis repository. This repository contains a collection of data structures and algorithms implemented in various programming languages. It is designed to help students and developers understand, practice, and master the fundamentals of data structures and algorithms.

Table of Contents

Introduction

Data structures and algorithms are essential for writing efficient and effective code. This repository aims to provide a comprehensive resource for learning and implementing these concepts. Each data structure and algorithm is accompanied by explanations, use cases, and code examples.

Features

  • Implementations of various data structures (e.g., arrays, linked lists, stacks, queues, trees, graphs, hash tables).
  • Implementations of common algorithms (e.g., sorting, searching, dynamic programming, graph algorithms).
  • Code examples in multiple programming languages.
  • Detailed explanations and use cases for each data structure and algorithm.
  • Unit tests for each implementation to ensure correctness.

Getting Started

To get started with the code in this repository, follow these steps:

  1. Clone the repository:

    git clone https://github.com/agneepradeep/Data-Structures-And-Algorithm-Analysis.git
    cd Data-Structures-And-Algorithm-Analysis
  2. Navigate to the relevant directory: Each data structure and algorithm is organized into separate directories. Navigate to the desired directory to find the implementation and related files.

  3. Run the code: Follow the instructions in the specific directory's README or comments in the code files to compile and run the implementations.

Data Structures

The repository includes the following data structures:

  • Arrays: Dynamic arrays, multi-dimensional arrays.
  • Linked Lists: Singly linked list, doubly linked list, circular linked list.
  • Stacks: Array-based stack, linked list-based stack.
  • Queues: Array-based queue, linked list-based queue, circular queue, priority queue.
  • Trees: Binary tree, binary search tree, AVL tree, red-black tree, segment tree, trie.
  • Graphs: Adjacency list, adjacency matrix, graph traversal algorithms.
  • Hash Tables: Hash functions, collision resolution techniques (chaining, open addressing).

Algorithms

The repository includes implementations of the following algorithms:

Sorting Algorithms

  • Bubble Sort
  • Selection Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
  • Heap Sort
  • Radix Sort

Searching Algorithms

  • Linear Search
  • Binary Search
  • Depth-First Search (DFS)
  • Breadth-First Search (BFS)

Dynamic Programming

  • Fibonacci Sequence
  • Knapsack Problem
  • Longest Common Subsequence
  • Matrix Chain Multiplication

Graph Algorithms

  • Dijkstra's Algorithm
  • Kruskal's Algorithm
  • Prim's Algorithm
  • Floyd-Warshall Algorithm

Contributing

Contributions are welcome! If you have any improvements, bug fixes, or new implementations to add, please fork the repository and create a pull request. Ensure that your code follows the repository's coding standards and includes appropriate documentation and tests.

License

This repository is licensed under the MIT License. See the LICENSE file for more details.

Contact

If you have any questions, suggestions, or feedback, feel free to contact me.

Happy coding!

Agneepradeep Verma

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The Data Structures and Algorithm Analysis repository is a collection of data structures and algorithms implemented in various programming languages. It serves as an educational resource for students, developers, and enthusiasts to understand and master fundamental concepts in computer science.

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