complexity-analyzer

Solid

Automated Big-O complexity analysis of code and algorithms. Performs static analysis of loop structures, recursive call trees, space complexity estimation, and amortized analysis with detailed derivation documents.

AI & Automation 1,160 stars 71 forks Updated today MIT

Install

View on GitHub

Quality Score: 96/100

Stars 20%

100

Recency 20%

100

Frontmatter 20%

Documentation 15%

100

Issue Health 10%

License 10%

100

Description 5%

100

Skill Content

# complexity-analyzer A specialized skill for automated analysis of algorithm time and space complexity, providing Big-O notation analysis, detailed derivations, and optimization recommendations. ## Purpose Analyze code and algorithms to determine: - Time complexity (Big-O, Big-Omega, Big-Theta) - Space complexity (auxiliary and total) - Amortized complexity for data structure operations - Complexity derivation with step-by-step reasoning - Optimization opportunities and bottleneck identification ## Capabilities ### Core Analysis Features 1. **Static Analysis** - Loop structure analysis (nested loops, dependent bounds) - Recursive call tree analysis - Function call graph traversal - Branch condition impact analysis 2. **Complexity Types** - **Time Complexity**: Worst, average, and best case analysis - **Space Complexity**: Stack space, heap allocations, auxiliary space - **Amortized Analysis**: Aggregate, accounting, and potential methods - **Recurrence Relations**: Master theorem, substitution method 3. **Output Formats** - Big-O notation with detailed derivation - Complexity comparison tables - Visual complexity graphs - Optimization recommendations ### Supported Languages - Python (primary) - C++ (full support) - Java (full support) - JavaScript/TypeScript (full support) - Go, Rust, C (partial support) ## Integration Options ### MCP Servers **AST MCP Server** - Advanced code structure analysis: ```bash # Provides AST parsing...