https://github.com/doantrunghuy/exercises-and-solutions-to-algorithmic-problems

Accepted solutions, doing topics on: Introductory Problems, Sorting and Searching, Dynamic Programming, Graph Algorithms, Range Queries, Tree Algorithms, Mathematics, String Algorithms, Geometry.
https://github.com/doantrunghuy/exercises-and-solutions-to-algorithmic-problems

advanced-techniques dynamic-programming geometry graph mathematics range-query string tree

Last synced: 10 days ago
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Accepted solutions, doing topics on: Introductory Problems, Sorting and Searching, Dynamic Programming, Graph Algorithms, Range Queries, Tree Algorithms, Mathematics, String Algorithms, Geometry.

• Host: GitHub
• URL: https://github.com/doantrunghuy/exercises-and-solutions-to-algorithmic-problems
• Owner: DoanTrungHuy
• Created: 2023-08-06T10:19:27.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-07-13T08:49:56.000Z (6 months ago)
• Last Synced: 2024-07-14T06:26:21.272Z (6 months ago)
• Topics: advanced-techniques, dynamic-programming, geometry, graph, mathematics, range-query, string, tree
• Language: C++
• Homepage: https://cses.fi/user/83959
• Size: 10.3 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Exercises and Solutions to Algorithmic Problems

This repository contains a curated collection of algorithmic problems along with their accepted solutions. The problems are organized into key topics that cover a wide range of algorithmic challenges. Whether you're a beginner or looking to deepen your understanding of algorithms, this repository provides a comprehensive resource for practicing and mastering various algorithms.

## Topics Covered

The exercises are categorized into the following core topics:

### 1. **Introductory Problems**

   - Fundamental problems designed for beginners to get started with basic algorithmic techniques.

### 2. **Sorting and Searching**

   - Various sorting algorithms (Quick Sort, Merge Sort, etc.) and searching techniques (Binary Search, Linear Search, etc.).

### 3. **Dynamic Programming**

   - Classic dynamic programming problems that teach you how to optimize solutions by solving subproblems and storing intermediate results.

### 4. **Graph Algorithms**

   - Algorithms to solve graph-based problems, including traversal techniques like DFS, BFS, and algorithms for shortest paths, minimum spanning trees, and more.

### 5. **Range Queries**

   - Problems that deal with querying ranges of data efficiently, such as segment trees and binary indexed trees.

### 6. **Tree Algorithms**

   - Problems involving binary trees, binary search trees, AVL trees, and various tree traversal algorithms.

### 7. **Mathematics**

   - Algorithmic problems focused on mathematical concepts such as number theory, combinatorics, and prime factorization.

### 8. **String Algorithms**

   - A collection of problems related to string manipulation, pattern matching, and string processing algorithms like KMP and Rabin-Karp.

### 9. **Geometry**

   - Algorithms related to computational geometry, including problems on points, lines, and polygons.

## Features

- **Well-documented solutions**: Each problem is accompanied by a detailed explanation of the approach, time complexity, and edge cases.

- **Optimized solutions**: Solutions are implemented with an emphasis on efficiency and scalability.

- **Comprehensive test cases**: Every solution is tested with multiple test cases to ensure correctness.