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Algorithms & Data Structures

Osama Zinhom

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Binary Search

Visualize the efficiency of binary search in sorted datasets. Step through interactive examples to understand its logarithmic time complexity and practical applications.

Time Complexity: O(log n)
Space Complexity: O(1)

Key Features

  • Interactive Visualization
  • Step-by-Step Breakdown
  • Code Explanation & Examples
Selection Sort

Grasp the fundamentals of sorting algorithms with Selection Sort. Observe its step-by-step process and analyze its quadratic time complexity in action.

Time Complexity: O(n²)
Space Complexity: O(1)

Key Features

  • Animated Sorting Process
  • Visual Step Tracking
  • Algorithm Walkthrough
Recursion in Action

Explore the power of recursion through interactive examples. Understand how recursive functions work and visualize the call stack in action.

Key Features

  • Factorial Calculation Example
  • Fibonacci Sequence Visualization
  • Call Stack Exploration
Big O Complexity

Visually compare different time complexities and their growth rates. Gain an intuitive understanding of Big O notation and its importance in algorithm analysis.

Key Features

  • Interactive Complexity Comparison
  • Visual Growth Charts
  • Real-World Complexity Scenarios
Array Operations

Explore array operations and their performance characteristics. Visualize access, insertion, and deletion to understand array efficiency and limitations.

Time Complexity: O(1) Access, O(n) Insert/Delete
Space Complexity: O(n)

Key Features

  • Visual Operation Comparison
  • Performance Metrics Display
  • Real-time Array Manipulation
Linked Lists

Implement and visualize linked lists, a dynamic data structure. Compare singly and doubly linked lists and understand their advantages over arrays.

Time Complexity: O(1) Insert/Delete (known), O(n) Search
Space Complexity: O(n)

Key Features

  • Interactive Node Manipulation
  • Pointer Visualization
  • Array vs. Linked List Comparison
Divide & Conquer Recursion

Master divide and conquer algorithms using recursion. Visualize Merge Sort and understand how breaking problems down leads to efficient solutions.

Time Complexity: O(n log n) Merge Sort
Space Complexity: O(n) Merge Sort

Key Features

  • Merge Sort Visualization
  • Recursive Tree Exploration
  • Step-by-Step Execution Analysis
Memory Visualization

Visualize memory allocation for different data structures. Compare contiguous and linked memory and understand memory fragmentation and usage patterns.

Key Features

  • Contiguous vs. Linked Memory
  • Fragmentation Demonstration
  • Memory Usage Pattern Analysis
Quicksort Visualization

Visualize Quicksort, a highly efficient sorting algorithm. Observe its partitioning process and analyze its average and worst-case time complexities.

Time Complexity: O(n log n) Avg, O(n²) Worst
Space Complexity: O(log n)

Key Features

  • Animated Pivot Selection
  • Partitioning Process Visualization
  • Performance Comparison
Hash Tables

Implement and visualize Hash Tables and their key operations. Understand hash functions, collision resolution, and the efficiency of hash-based data retrieval.

Time Complexity: O(1) Avg, O(n) Worst (Insert/Search/Delete)
Space Complexity: O(n)

Key Features

  • Interactive Hash Function Demo
  • Collision Resolution Visualization
  • Performance Analysis
Graph Representations

Compare different graph representations in data structures. Visualize adjacency lists and matrices and understand their trade-offs in space and time.

Key Features

  • Interactive Graph Creation
  • Adjacency List vs. Matrix Conversion
  • Space & Time Requirement Comparison
Graph Traversal (BFS & DFS)

Visualize graph traversal algorithms, Breadth-First Search (BFS) and Depth-First Search (DFS). Step through animations and understand their pathfinding strategies.

Time Complexity: O(V + E) (BFS & DFS)
Space Complexity: O(V)

Key Features

  • Step-by-Step Traversal Animation
  • Path Highlighting
  • Queue/Stack Visualization (BFS/DFS)