🔍 Algorithms
Explore efficient problem-solving techniques and computational methods
🧠 Algorithm Categories
Algorithms are step-by-step procedures for solving problems efficiently:
📊
Sorting Algorithms
Data Organization: Arrange elements in order
O(n log n)
O(n²)
- Bubble Sort, Quick Sort
- Merge Sort, Heap Sort
- Time complexity analysis
- Stability and adaptability
🔍
Search Algorithms
Data Retrieval: Find specific elements
O(log n)
O(n)
- Linear Search, Binary Search
- Hash table lookups
- Tree traversal methods
- Search optimization
🕸️
Graph Algorithms
Network Analysis: Navigate connected data
O(V + E)
O(V²)
- BFS and DFS traversal
- Shortest path algorithms
- Minimum spanning trees
- Network flow problems
💡
Dynamic Programming
Optimization: Break down complex problems
O(n²)
O(nm)
- Fibonacci sequence
- Knapsack problem
- Longest common subsequence
- Memoization techniques
Algorithm Category
Click on an algorithm category to learn about its applications and complexity.
📊 Interactive Sorting Visualizer
O(n log n)
Best Average Case for Comparison Sorts
Click "Generate Array" to start visualization
Sorting Algorithm
Select a sorting algorithm to see how it works step by step.
🔍 Search Algorithm Demonstrations
Learn how different search algorithms find elements in data structures:
Linear Search vs Binary Search
Search for a target value in the array below:
🕸️ Graph Traversal Visualization
Explore how graph algorithms navigate connected nodes:
Click "Generate Graph" to create a random graph for traversal
Graph Algorithm
Select a traversal algorithm to see how it explores the graph.
💡 Dynamic Programming Demo
O(n)
Fibonacci with Memoization vs O(2^n) Naive
⚖️ Algorithm Complexity Comparison
Compare the efficiency of different algorithms:
| Algorithm |
Best Case |
Average Case |
Worst Case |
Space Complexity |
Stable |
| Bubble Sort |
O(n) |
O(n²) |
O(n²) |
O(1) |
Yes |
| Quick Sort |
O(n log n) |
O(n log n) |
O(n²) |
O(log n) |
No |
| Merge Sort |
O(n log n) |
O(n log n) |
O(n log n) |
O(n) |
Yes |
| Binary Search |
O(1) |
O(log n) |
O(log n) |
O(1) |
- |
| Linear Search |
O(1) |
O(n) |
O(n) |
O(1) |
- |
🧠 Algorithms Quiz
Question 1: What is the time complexity of binary search?
A) O(n)
B) O(log n)
C) O(n²)
D) O(1)