Code to Flow

Parses source code into an abstract syntax tree (AST), traverses control flow structures (conditionals, loops, function calls), and generates a structured intermediate representation that maps to flowchart nodes and edges. The system identifies decision points, branches, and sequential operations to build a directed acyclic graph representation suitable for visualization. This approach preserves semantic meaning across multiple programming languages by normalizing language-specific syntax into a unified control flow model.

Leverages large language models (LLMs) to analyze parsed code structures and generate human-readable explanations of what each code block does, why it exists, and how it fits into the broader system. The system feeds the AST representation and control flow graph to an LLM with a prompt engineered to produce clear, non-technical summaries suitable for documentation or onboarding. This approach combines structural understanding (from AST analysis) with semantic understanding (from LLM reasoning) to produce contextually accurate explanations.

Renders parsed control flow as an interactive, zoomable, pannable flowchart where each node represents a code block or decision point and edges represent control flow transitions. The visualization engine uses a graph layout algorithm (likely force-directed or hierarchical) to position nodes for readability, and implements click-through navigation that highlights corresponding source code lines. The system maintains bidirectional linking — clicking a flowchart node highlights the source code, and clicking source code highlights the corresponding flowchart node.

Implements language-specific parsers (using tree-sitter or similar AST libraries) for multiple programming languages and normalizes their syntax trees into a unified control flow representation. Each language parser extracts control structures (if/else, loops, function calls, exception handling) and maps them to canonical node types in an intermediate representation. This abstraction layer allows the same visualization and analysis engine to work across JavaScript, Python, Java, C#, Go, TypeScript, and other languages without duplicating logic.

Accepts multiple source code files or an entire codebase directory, parses each file independently, generates flowcharts for each function or method, and produces a consolidated report or dashboard showing control flow patterns across the entire system. The system can identify cross-file dependencies, function call chains, and module-level interactions. This capability enables high-level codebase understanding without manually analyzing individual files.

Analyzes the control flow graph to calculate cyclomatic complexity (number of linearly independent paths through code), nesting depth, and other code quality metrics. The system traverses the AST to count decision points, loops, and branches, then computes metrics that indicate code maintainability and testability. These metrics are displayed alongside the flowchart to help developers identify overly complex code that may need refactoring.

Generates flowchart exports in multiple formats (PNG, SVG, PDF) and provides integrations with documentation platforms (Confluence, Notion, GitHub Wiki, etc.) to embed flowcharts directly into documentation. The system can also generate Markdown or HTML snippets suitable for inclusion in README files or technical documentation. This capability enables seamless integration of auto-generated flowcharts into existing documentation workflows.