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🤖 Competitive Programming Solutions (C/C++)

This repository serves as a portfolio of my competitive programming journey and proficiency in algorithmic problem-solving using C and C++. It tracks my foundational training, dedicated study of core Data Structures, and implementation of various Graph and Optimization Algorithms.

Language Total Problems Solved Status
C/C++ 204 Ongoing Development

📁 Repository Structure and Focus Areas

The solutions are divided into three main categories, reflecting a sequential learning path:

Folder Problem Count Primary Focus
Initial_Training_Solutions 104 C/C++ syntax, basic implementation, mathematical logic.
Data_Structure_Training_Solutions 66 Foundational Data Structures and their efficient C++ implementation.
Algorithms_Training_Solutions 34 Core Graph, Search, and Optimization Algorithms.

1. Initial Training Solutions (104 Files)

This folder contains the solutions from my initial training phase, primarily focused on establishing fluency in C and C++ syntax, control structures (loops, conditionals), and basic mathematical problem implementation.

  • Goal: Master the core language features and translate beginner-level problems into functional code.
  • Content Includes: Basic I/O, simple mathematical formulas, loops, and conditional logic problems.
  • Organization: Files are generally organized chronologically by the order they were solved.

2. Data Structure Training Solutions (66 Files)

This section demonstrates dedicated practice in implementing and utilizing essential data structures, which are foundational to efficient problem-solving.

  • Goal: Deepen understanding of how to implement and choose the correct data structure for maximizing runtime efficiency.
  • Key Data Structures Covered:
    • Singly Linked Lists
    • Doubly Linked Lists
    • Vectors/Dynamic Arrays
    • Queues and Priority Queues
    • Stacks
    • Binary Search Trees (BST)
    • Heaps
    • Sets and Maps

3. Algorithms Training Solutions (34 Files)

This folder showcases proficiency in advanced algorithms necessary for competitive programming and complex engineering problems.

  • Goal: Implement and apply standard graph traversal, shortest path, and optimization algorithms to solve problems.
  • Key Algorithms Covered:
    • Shortest Path: Dijkstra's Algorithm, Bellman-Ford Algorithm, Floyd-Warshall Algorithm
    • Graph Traversal: Breadth-First Search (BFS), Depth-First Search (DFS)
    • Set Operations: Disjoint Set Union (DSU) / Union-Find
    • Optimization: Dynamic Programming (DP), Knapsack Problem Variations