boyter/scc
Scc
Scc is a codebase analysis tool written in Go that calculates source lines of code, blank lines, and comments across hundreds of programming and markup languages. It functions as a source code metric engine, software complexity analyzer, and cost estimator.
The project differentiates itself by providing a COCOMO cost estimator to predict development effort and financial costs, alongside tools to estimate the cost of regenerating a codebase using large language models. It also includes a Git repository metrics tool that correlates commit history with codebase metrics to identify hotspots, track author contributions, and visualize language evolution.
The tool provides quantitative analysis for cyclomatic complexity and code uniqueness to identify technical debt. It generates visual reports through HTML infographics and SVG badges and can export metrics in JSON, CSV, SQL, and OpenMetrics formats.
Scc integrates with the Model Context Protocol to allow language models to programmatically retrieve metrics and trigger code analysis.
Features
- Physical Line Counters - Calculates source lines, blank lines, and comments across hundreds of programming and markup languages.
- Line Counting - Calculates source lines of code, blank lines, and comments across hundreds of programming and markup languages.
- Source Code Volume Analysis - Scc processes source code across hundreds of programming and markup languages by identifying file extensions and markers.
- Cyclomatic Complexity Approximators - Estimates cyclomatic complexity by scanning source code for language-specific control flow keywords.
- Commit History Analysis - Correlates codebase metrics with Git commit logs to identify hotspots and track author contributions.
- File Extension Language Mappings - Maps file extensions to programming language rules to determine the appropriate counting logic.
- Git Repository Analysis - Identifies defect-prone files by correlating code complexity with change frequency in the commit history.
- Git Repository Analyzers - Tracks author contributions, identifies hotspots, and visualizes language evolution through commit history.
- Marker-Based Language Remapping - Assigns language counting rules to files without extensions using shebangs or internal string markers.
- Git Repository Analytics - Analyzes repository data to provide insights into contributor activity, code churn, and project health.
- COCOMO Models - Provides a COCOMO cost estimator to predict development effort and financial costs.
- Code Complexity Metrics - Calculates cyclomatic complexity by scanning for branch and loop statements to identify technical debt.
- Cyclomatic Complexity Analyzers - Estimates cyclomatic complexity and technical debt to identify files requiring refactoring.
- Project Contribution Analysis - Determines the bus factor and attributes code ownership by analyzing commit history.
- Software Development Cost Estimators - Predicts development effort and financial cost by calculating software complexity using COCOMO estimates.
- Software Development Effort Estimators - Predicts development effort and financial costs by applying COCOMO and LOCOMO formulas to line counts.
- Technical Debt Analyzers - Approximates cyclomatic complexity and computes uniqueness to identify technical debt and duplication.
- Shebang-Based Language Detectors - Determines the programming language of files lacking extensions by inspecting shebangs or internal markers.
- LLM Code Regeneration Cost Estimators - Calculates token requirements and financial costs to regenerate a codebase using a large language model.
- Model Context Protocol Servers - Provides a Model Context Protocol server enabling AI models to programmatically trigger codebase analysis.
- Visual Badges - Produces SVG images representing code counts and cost estimates for use in project documentation.
- Analysis Result Exporters - Serializes analysis results into structured formats including JSON, CSV, SQL, and OpenMetrics.
- Analysis Exclusions - Prevents specific files or directories from being counted during a scan using a configuration file.
- Minified File Detectors - Identifies minified or generated files by calculating average byte length per line.
- Visual Reporting - Generates HTML infographics and SVG badges to visualize project health, ownership, and size.
- Dependency Filtering via Gitignore - Skips files and directories that should not be analyzed by respecting .gitignore rules.
- Metric-Based Content Filters - Excludes files from counts based on configurable byte size or line count thresholds.
- Codebase Infographics - Creates self-contained HTML infographics summarizing metrics, author timelines, and complexity estimates.
- Code Uniqueness Analyzers - Computes unique lines of code and dryness percentages to identify duplication and boilerplate density.
- Language Evolution Trackers - Plots the trajectory of language adoption and shifts over time using repository commit history.
- File Management - Count lines of code, blank lines, comment lines, and physical lines of source code.
- Software Tools - Fast code counter with complexity estimation.
