Welcome to Quick Sort

Quick Sort is one of the most efficient sorting algorithms. It uses a divide-and-conquer approach and typically runs in O(n log n) time, making it a favorite for production code.

What You’ll Learn

By the end of this tutorial, you’ll be able to:

• ✅ Explain quick sort and the divide-and-conquer approach
• ✅ Understand partitioning and how it works
• ✅ Implement quick sort with optimizations
• ✅ Analyze performance and understand complexity
• ✅ Choose pivot strategies for best performance

Tutorial Structure

This tutorial is divided into 7 interactive pages (about 30 minutes):

1. Introduction (4 min) - What is quick sort and why it’s fast
2. How It Works (5 min) - Divide-and-conquer approach
3. Partitioning (6 min) - The core of quick sort
4. Visualization (4 min) - See it in action
5. Implementation (5 min) - Code it yourself
6. Complexity & Optimizations (4 min) - Performance analysis
7. Practice & Quiz (2 min) - Test your knowledge

Interactive Features

Throughout this tutorial, you’ll use:

• 🎬 Animated Visualizations - Watch quick sort step-by-step
• 🎯 Interactive Sorters - Sort arrays yourself
• 📊 Animated Diagrams - See partitioning in action
• ✅ Knowledge Checks - Test your understanding
• 💻 Code Examples - Run and modify code

Prerequisites

Before starting, you should have:

• Basic understanding of arrays and recursion
• Familiarity with partitioning concepts
• Understanding of time complexity

Don’t worry if you’re not an expert - we’ll explain concepts as we go.

Estimated Time

⏱️ 30 minutes to complete all 7 pages

You can take breaks between pages and resume anytime. Your progress will be tracked as you navigate through the tutorial.

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What is Quick Sort?

Quick Preview: Quick Sort is a divide-and-conquer algorithm that picks a pivot element and partitions the array around it. Elements smaller than the pivot go left, larger go right. Then it recursively sorts the sub-arrays.

Why it matters: Quick Sort is one of the fastest general-purpose sorting algorithms, with O(n log n) average time complexity. It’s used in many standard library implementations.

Ready to start? Click the button above to begin!