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Data Structures and Algorithms (DSA) Projects

Welcome to my DSA repository! This repository showcases my implementation of various data structures and container classes in C++. It is a testament to my understanding of fundamental and advanced programming concepts, as well as my ability to develop efficient and scalable solutions.

🚀 About the Repository

This repository demonstrates a comprehensive exploration of data structures and their operations. Each project is designed to highlight my proficiency in implementing core concepts of data organization and manipulation. The codebase is written with clarity and efficiency, making it a valuable resource for understanding and applying DSA concepts.

📂 Projects Included

1. Containers

I have implemented a variety of containers, each supporting all standard operations and emphasizing robustness and performance:

  • Matrix: A two-dimensional container supporting mathematical and structural operations.
  • Bag: A collection allowing duplicate elements, with efficient insertion and frequency-based operations.
  • SortedBag: An ordered variant of the Bag, maintaining elements in sorted order.
  • Set: A collection of unique elements with fast membership checks and set operations.
  • Queue: A FIFO (First-In-First-Out) container for managing sequential tasks.
  • Map: A key-value store with fast lookups and updates.
  • SortedMap: A Map variant maintaining keys in sorted order.

2. Core Data Structures

Each data structure is implemented from scratch, showcasing dynamic memory management and efficient algorithms:

  • Dynamic Array: A resizable array with optimized memory allocation.
  • Linked List: Traditional linked list with dynamic memory allocation and pointer-based operations.
  • Linked List on Array: A hybrid structure combining the flexibility of a linked list with the compactness of an array.
  • HashTable: A hash-based data store with collision handling for fast data access.
  • Binary Search Tree: A tree-based structure for sorted data storage and logarithmic time complexity operations.

💡 Key Highlights

  • Comprehensive implementation of all standard operations for each container and data structure.
  • Use of dynamic memory allocation for efficient and flexible data handling.
  • Optimized algorithms ensuring high performance and scalability.
  • Well-structured and documented code for ease of understanding and extensibility.

🛠️ Technologies Used

  • Programming Language: C++
  • Key Concepts: Dynamic Memory Management, Algorithm Design, and Optimization.

📜 Purpose

This repository serves as a portfolio of my skills in data structures and algorithms, showcasing my ability to implement, analyze, and optimize various solutions. It also provides a learning resource for others who wish to deepen their understanding of DSA concepts.

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