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Design and analysis of algorithms is a fundamental concept in computer science that involves developing efficient and effective methods for solving computational problems. This field encompasses a wide range of techniques and strategies, including algorithmic design paradigms, data structures, complexity theory, and optimization.

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Leni-Nikitaa/Design-and-Analysis-of-Algorithms

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Design and Analysis of Algorithms

This repository contains the implementation of algorithms and data structures covered in the course "Design and Analysis of Algorithms" (for educational purpose).

Table of Contents

  • Installation
  • Usage
  • Algorithms
  • Data Structures
  • Contributing
  • License

Installation

To use the code in this repository, you can simply clone the repository to your local machine:

git clone https://github.com/Leni-Nikitaa/Design-and-Analysis-of-Algorithms.git

Usage

You can use the code in this repository as a reference for implementing algorithms and data structures in your own projects.

Algorithms

This repository contains implementations of the following algorithms:

  • Linear Search
  • Binary Search
  • Bubble Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
  • Strassen Matrix Multiplication
  • Finding Maximum and Minimum in an Array
  • Convex Hull
  • Huffman code
  • Factorial Knapsack Problem
  • Longest Common Subsequence
  • Matrix Chain Multiplication
  • Depth First Search
  • Breadth First Search
  • N-Queens Problem
  • Randomized Quick Sort
  • Traveling Salesman Problem
  • Rabin Karp String Matching Algorithm

Data Structures

This repository contains implementations of the following data structures:

  • Linked List
  • Stack
  • Queue
  • Binary Tree
  • Binary Search Tree
  • Heap
  • Hash Table

Contributing

If you find any bugs or issues with the code, please open an issue or submit a pull request. Contributions are welcome!

About

Design and analysis of algorithms is a fundamental concept in computer science that involves developing efficient and effective methods for solving computational problems. This field encompasses a wide range of techniques and strategies, including algorithmic design paradigms, data structures, complexity theory, and optimization.

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