Computer Science Visualized

Master Complex Algorithms

Interactive, step-by-step visualizers to help you build intuition about sorting, graph pathways, backtracking, and optimization.

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Sorting Algorithms

Analyze how elements shuffle into order. Includes Bubble, Selection, Insertion, Merge, Quick, and Heap Sort with array structures visualization.

Explore Visualizer

Pathfinding on Maps

Find the shortest path on a map grid using Dijkstra, Bellman-Ford, and Floyd-Warshall, rendering paths dynamically on an interactive node-map.

Explore Visualizer

Backtracking & NP

See recursion in action with N-Queens constraint satisfaction and Graph Coloring optimization, tracing decisions and backtracks.

Explore Visualizer

Sorting Algorithms

Observe comparisons, swaps, and partitioning of list elements in real time.

Array Data Representation Diagram

A visual breakdown of the current array structure, index mapping, and element states.

Sorting Algorithm Code Reference

Complexity & Properties

Time Complexity (Worst) O(n²)
Time Complexity (Average) O(n²)
Time Complexity (Best) O(n)
Space Complexity (Auxiliary) O(1)
Stable Sorting Yes

Algorithm Explanation

Select an algorithm to view details.

Shortest Path Routing on Map

Find the shortest path between nodes using standard pathfinding algorithms rendered on a glowing topological city map.

Start End Visited Shortest Path

Algorithm Code Reference

Algorithm details

Dijkstra's Algorithm

Time: O((V + E) log V) Space: O(V)

Execution Live Logs

Click "Run" to view distance calculation steps.

Backtracking & Constraint Satisfaction

Explore algorithms that search systematically through configuration spaces, solving NP-hard optimization problems.

N-Queens Implementation

N-Queens Problem

The goal is to place N chess queens on an \(N \times N\) chessboard such that no two queens threaten each other.

This requires that no two queens share the same row, column, or diagonal lines.

Time: O(N!) Space: O(N)

Backtracking Traversal Log

Click "Solve" to start the backtracking algorithm.

Graph Coloring Algorithm Implementation

Graph Coloring Concept

An assignment of colors to the vertices of a graph such that no two adjacent vertices share the same color.

The smallest number of colors needed to color a graph is called its Chromatic Number \(\chi(G)\).

Time: O(m^V) Space: O(V)

Coloring Step Logs

Click "Color Graph" to begin coloring vertices.