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.
- ✅ 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
- 📈 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
- 🔁 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.
- 📋 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
Search for Algorithm Complexity Analyzer in the VS Code Marketplace and click Install.
- Open a file in a supported language.
- Click the
Analyzebutton or right-click and choose Analyze Complexity. - View results inline or in the sidebar panel.
- Export the analysis from the report viewer.
- 🦀 Rust
- 🧩 WebAssembly
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 |
- 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:
Pull requests and feature suggestions are welcome!
Head to the GitHub repo to get started.
MIT License © 2025