Sorting Visualizer
A comprehensive web-based tool for visualizing sorting algorithms in action, designed to make abstract algorithmic concepts concrete through interactive animations.
Project Overview
The Sorting Visualizer is an educational web application that transforms abstract algorithmic concepts into tangible, visual experiences. Built to help students, educators, and developers understand how different sorting algorithms work through real-time animated visualizations.
The project serves as a comprehensive learning tool that makes complex algorithms accessible by showing the step-by-step process of how arrays get sorted, allowing users to see comparisons and swaps in real-time with detailed performance metrics.
Why I Built This
While learning algorithms, I kept memorizing time complexities but couldn't see what was actually happening during execution. I wanted a tool that would make the invisible visible—showing every comparison and swap in real time so the differences between O(n²) and O(n log n) became intuitive, not just theoretical.
This visualizer is for students preparing for technical interviews, educators demonstrating algorithm behavior, and anyone who learns better by watching code execute step by step rather than reading pseudocode.
Problem & Solution
The Problem
- • Sorting algorithms are abstract and hard to visualize
- • Students struggle to understand algorithm efficiency
- • Limited interactive tools for algorithm learning
- • Difficulty comparing different sorting approaches
The Solution
- • Interactive real-time algorithm visualization
- • Side-by-side comparison of multiple algorithms
- • Detailed performance metrics and timing
- • Educational content with algorithm explanations
Constraints & Decisions
- Pause/resume without desynchronization: Required careful state management to maintain exact execution position across animations
- Deterministic stepping for fair comparisons: Each algorithm needed to yield consistent steps for accurate side-by-side metrics
- Merge sort visualization model: Unlike swap-based algorithms, merge sort required a different approach to show auxiliary array operations
- Lightweight state management: Chose Zustand over Redux to avoid boilerplate while maintaining predictable state updates
- Animation fidelity vs. performance: Balanced smooth 60fps animations with accurate operation counting, especially on mobile devices
Key Features
Interactive Visualization
Real-time, animated visualization of sorting processes with color-coded states
8 Sorting Algorithms
Bubble, Selection, Insertion, Quick, Merge, Heap, Cocktail, and Comb Sort
Performance Metrics
Track swaps, comparisons, and execution time for each algorithm
Side-by-Side Comparison
Compare multiple algorithms simultaneously to understand differences
Customizable Controls
Adjustable speed, custom arrays, and detailed algorithm information
Responsive Design
Optimized for desktop, tablet, and mobile devices
Technical Implementation
Technology Stack
Key Technical Challenges
Async Generator Functions
Implemented sorting algorithms as async generator functions to allow step-by-step execution and visualization control, enabling precise animation timing.
Animation Synchronization
Coordinated visual animations with algorithm logical steps using custom CSS animations and styled components for smooth, accurate representations.
Merge Sort Visualization
Special handling for merge sort which doesn't use in-place swapping, requiring custom container components and visualization logic.
Architecture Highlights
State Management Architecture
Zustand-based dual-store system for predictable state updates:
- • Controls store: speed, isRunning, currentStep, selectedAlgorithms
- • Data store: array state, per-algorithm metrics, element color states
Execution Model
Algorithms implemented as async generators that yield discrete steps (compare, swap, overwrite, markSorted). The UI scheduler consumes these steps and updates the visualization bars and operation counters in sync.
Performance & Metrics
Measured Metrics
Performance Tracking
- • Execution time for each algorithm
- • Number of element comparisons
- • Number of element swaps
- • Animation speed control (1x to 10x)
Visual Feedback
- • Color-coded element states
- • Progress indicators
- • Completion status badges
- • Side-by-side algorithm comparison
Results & Outcomes
Technical Achievements
- • Pause/resume functionality works without skipping steps or desyncing animations
- • Smooth 60fps performance with arrays from 5 to 30 elements across all screen sizes
- • Operation counts verified against expected behavior on test arrays
- • TailwindCSS-based responsive design with Styled Components for animation layers
Real-World Impact
- • Used as a quick refresher before technical interviews
- • Helps visualize why certain algorithms perform better in specific scenarios
- • Makes time complexity differences tangible and memorable
- • Enables hands-on comparison without writing any code
Educational Impact
Learning Objectives
Algorithm Understanding
- • Visualize step-by-step sorting processes
- • Understand algorithm efficiency differences
- • Learn time and space complexity concepts
Interactive Learning
- • Hands-on algorithm experimentation
- • Real-time performance comparison
- • Custom array input and testing
What I Learned
- Async generators for algorithm visualization: Using generator functions to yield execution steps enabled precise control over animation timing and pause/resume functionality
- Animation synchronization is hard: Coordinating visual state with logical algorithm steps required careful timing management and state tracking
- Not all sorting algorithms are equal visually: Merge sort broke my swap-based mental model—it required rethinking how to represent auxiliary array operations
- Performance tradeoffs matter: Balancing animation smoothness with operation accuracy meant optimizing render cycles and minimizing unnecessary state updates
- State modeling impacts maintainability: Separating control state from data state made debugging easier and enabled independent feature development
- Responsive visualizations need adaptive data: Dynamic array sizing based on screen dimensions ensured consistent user experience across devices
Next Iteration
Enhanced Features
- • Additional algorithms (Radix, Shell Sort): to show non-comparison-based sorting behavior
- • Sound effects for audio feedback: making comparisons and swaps audible for multi-sensory learning
- • Save/share configurations: enabling users to bookmark interesting array states or edge cases
Educational Enhancements
- • Step-by-step explanations: inline descriptions of what's happening at each algorithm step
- • Interactive tutorials: guided walkthroughs for first-time users
- • Custom test cases: pre-configured worst-case, best-case, and already-sorted scenarios
Skills Demonstrated
Technical Skills
Frontend Development
- • React component architecture and hooks
- • Advanced JavaScript (async generators, promises)
- • CSS animations and responsive design
- • State management with Zustand
Algorithm Implementation
- • 8 different sorting algorithms
- • Performance optimization techniques
- • Visual representation of complex logic
- • Educational content creation
Soft Skills
Ready to Explore?
Experience the power of visual algorithm learning with interactive sorting demonstrations.