Mastering Data Structures and Algorithms

Welcome to my personal study repository for Data Structures and Algorithms! This repository serves as a comprehensive catalog of my learning journey, where I implement and explore key concepts in Java, JavaScript, and TypeScript. The content is organized into learning modules, covering essential topics such as Complexity Analysis (Big O), Search and Sort Algorithms, Dynamic Programming, and Graph Theory.

This project is a reflection of my progress through various courses and self-study efforts, aimed at deepening my understanding of algorithmic problem-solving and preparing for real-world applications.

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📖 Overview

This repository is designed to document my implementations and notes as I progress through my study of Data Structures and Algorithms. Each module is carefully structured to include explanations, code implementations, and examples to solidify my understanding of fundamental and advanced concepts.

The primary goals of this repository are:

• To catalog my learning progress in an organized and accessible way.
• To serve as a reference for revisiting key concepts and implementations.
• To practice writing clean, efficient, and well-documented code in multiple programming languages.

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📚 Learning Modules

The repository is organized (but not limited) into the following core modules, each focusing on a specific area of Data Structures and Algorithms:

1. Complexity Analysis (Big O Notation)

   • Understanding time and space complexity.
   • Analyzing the efficiency of algorithms using Big O, Omega, and Theta notations.
   • Practical examples of complexity in real-world algorithms.

2. Search and Sort Algorithms

   • Implementation of common algorithms like Binary Search, Quick Sort, Merge Sort, and more.
   • Comparative analysis of sorting techniques.
   • Optimization techniques for search and sort operations.

3. Dynamic Programming

   • Solving problems using memoization and tabulation.
   • Classic problems like Fibonacci, Knapsack, and Longest Common Subsequence.
   • Techniques to optimize recursive solutions.

4. Graph Theory

   • Representations of graphs (adjacency lists, matrices).
   • Algorithms like Depth-First Search (DFS), Breadth-First Search (BFS), Dijkstra’s, and more.
   • Applications in real-world problems like network traversal and shortest paths.

Each module may contain:

• Source code implementations in Java, JavaScript, and TypeScript.
• Detailed comments explaining the logic and approach.
• Example problems and their solutions.

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🛠 Technologies Used

• Java: For object-oriented and robust implementations.
• JavaScript: For dynamic and flexible scripting.
• TypeScript: For type-safe and scalable solutions.
• Git: For version control and tracking progress.
• Markdown: For documentation and notes within the repository.
• Coding: I'll be using IntelliJ IDEA and Visual Studio Code (VS Code).

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🚀 Getting Started

To explore or use this repository locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/luizgdsmdev/mastering_data_structure_and_algorithm.git

2. Navigate to the project directory:

   cd mastering_data_structure_and_algorithm

3. Run the code:

   • For Java, compile and run using a JDK (e.g., javac File.java && java File).
   • For JavaScript, use Node.js (e.g., node file.js).
   • For TypeScript, compile with tsc file.ts and run the generated JavaScript.

4. Explore the modules:

   • Each module is organized in its own directory (e.g., complexity_analysis, search_sort, etc.).
   • Refer to the comments and documentation in each file for detailed explanations.

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📈 Progress and Updates

This repository is a living project, updated regularly as I progress through my learning journey. New algorithms, optimizations, and explanations will be added as I complete new courses and tackle more complex problems.

Feel free to check back for updates or follow the repository to stay informed about new content!

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🤝 Contributing

While this is a personal study repository, I welcome feedback, suggestions, or improvements! If you have ideas for better implementations, optimizations, or additional problems to explore, please:

1. Open an Issue to discuss your ideas.
2. Submit a Pull Request with your proposed changes.

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📬 Contact

If you have questions, suggestions, or just want to connect, feel free to reach out:

• GitHub: luizgdsmdev
• Linkedin: luizgdsm

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🙏 Acknowledgments

This repository is inspired by various online courses, books, and resources on Data Structures and Algorithms. Special thanks to the open-source community and educators who make learning accessible to everyone.

Happy coding! 🚀