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Baekjoon Algorithm Training

License

This repository contains solutions and notes for algorithm training. It is organized to help track progress and manage solution files effectively. Each directory corresponds to a category of algorithms, and each solution is named according to its problem ID on Baekjoon Site or Progammers Site.

📂 Repository Structure

The repository is organized as follows:

  • Sorting: Contains problems related to sorting algorithms.
  • Graph Theory: Contains problems involving graphs, traversals, and graph-related algorithms.
  • Dynamic Programming: Solutions for dynamic programming problems.
  • Data Structures: Contains implementations and problem solutions related to data structures.
  • Greedy Algorithms: Solutions for greedy algorithm problems.
  • Mathematics: Mathematical problems including number theory, combinatorics, etc.

Each directory includes:

  • Solution Files: .java or .py files containing solution code.
  • Explanation Files: .md files explaining the problem approach and solution details.
graph TD
    A[baekjoon-algorithm-training]
    A --> B[Sorting]
    A --> C[Graph Theory]
    A --> D[Dynamic Programming]
    A --> E[Data Structures]
    A --> F[Greedy Algorithms]
    A --> G[Mathematics]
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🚀 Getting Started

Prerequisites

  • Ensure you have Java (or Kotlin) installed on your system to run the solution files.
  • Basic knowledge of algorithms and data structures is recommended for a better understanding.

Installation

  1. Clone the repository from GitHub.
  2. Navigate to the project directory.

📘 Usage

  1. Navigate to a specific algorithm category folder.
  2. Open the solution file for a particular problem to see the solution code and explanations.

📈 Progress Tracker

The following is the approximate distribution of problems solved in each algorithm category:

  • Baekjoon Online Judge: 50%
  • Progammers: 50%

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

📬 Contact

For any questions or suggestions, please reach out to [email protected]

Happy coding and good luck with your algorithm training on Baekjoon!