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🚀 Algorithm Complexity Analyzer
A powerful Visual Studio Code extension that analyzes the algorithmic complexity (Big O notation) of your code using a high-performance Rust WebAssembly (WASM) engine. Get instant insights into your code's performance with interactive visualizations , inline feedback , and detailed reports .
✨ Features
🔍 Comprehensive Analysis
✅ Multi-language support : JavaScript, TypeScript, Python, Java, C, C++, Rust
✅ Function-level analysis : Determine complexity for each function
✅ Overall file complexity : Identify the worst-case complexity per file
✅ Confidence scoring : See how reliable each analysis is
📊 Rich Visualizations
📈 Interactive doughnut charts : Visualize complexity distribution
📊 Bar graphs : Compare function complexities side-by-side
💡 Inline decorations : View complexity directly in your code
🧠 Hover tooltips : Get instant analysis explanations on hover
🎯 Smart Detection
🔁 Loop analysis : Understand nested loops, single loops, and loop patterns
🔄 Recursion detection : Identify tail recursion, divide-and-conquer, exponential patterns
🧰 Built-in functions : Recognizes standard library function complexities
📚 Algorithm patterns : Detects binary search, sorting, dynamic programming, etc.
📈 Professional Reports
📋 Detailed reports : Full breakdown of complexity factors and patterns
💾 Export formats : JSON, HTML, Markdown, and CSV
🔐 Confidence indicators : Visual display of analysis confidence
⚠️ Warnings system : Alerts for analysis limitations or ambiguities
⚙️ Rust + WebAssembly : Ultra-fast performance and memory efficiency
📦 Memory-optimized : Designed for large codebases
🔁 Real-time feedback : See updates as you code
🛠️ Configurable : Customize file size limits and analysis thresholds
📦 Installation
Search for Algorithm Complexity AnalyzerVS Code Marketplace and click Install .
🛠 Usage
Open a file in a supported language.
Click the Analyze button or right-click and choose Analyze Complexity .
View results inline or in the sidebar panel.
Export the analysis from the report viewer.
🧠 Powered By
🎨 Complexity Color Coding
Color-coded complexity for quick visual understanding:
Complexity
Color
Performance
O(1)🟢 Green
Excellent
O(log n)🟢 Teal
Very Good
O(n)🟡 Yellow
Good
O(n log n)🟠 Orange
Acceptable
O(n²)🔴 Red
Poor
O(n³)🟣 Purple
Very Poor
O(n^k)🟡 Pink
Extremely Poor
O(2ⁿ)⚫ Dark Gray
Unacceptable
O(n!)⚫ Black
Only for Tiny Inputs
🛠 Usage
Open a file in any supported language (JavaScript, TypeScript, Python, Java, C, C++, Rust) Select code (optional) or leave it unselected to analyze the entire file.Click the extension icon labeled "Complexity Analyzer" from the activity bar or title bar.The analysis report will be generated in the panel below , showing complexity metrics, graphs, and detailed explanations.
📊 Example Report Panel:
📣 Contribute
Pull requests and feature suggestions are welcome!GitHub repo to get started.
📝 License
MIT License © 2025
