2.1. How We Represent Complexity as Physical Structure

Code complexity is mapped directly to physical structure, creating organic, distinct shapes for different complexity patterns. This representation of complexity does not depend on color; it relies purely on geometry and spatial arrangement.

Physical Attribute	Code Metric (Heuristic)	Visual Result (The "Look")
Star's Size	Lines of Code (LOC) per File	Mass. Logarithmic scaling ensures that 10k+ LOC files appear as massive suns, while 10 LOC scripts remain small asteroids.
Star's Pulse Rate	Inbound References (Popularity)	Bioluminescence. Core utilities pulse with a white-hot "heartbeat." Unreferenced files remain dim and static.
Star's Shape	Control Flow Ratio (File Level)	Geometry. Morphs from a smooth Sphere (Declarative/Data) to a sharp Tetrahedron (Pure Algorithmic Logic).
Satellite Unit	Function Declaration	Moons. Every discrete function is materialized as a satellite orbiting its parent star.
Satellite Distance	Lines of Code (LOC) per Function	Orbital Reach. Long functions reach further into the void; small stubs orbit tightly near the star's surface.
Number of Satellites	Cyclomatic Complexity	Fractal Density. Highly complex functions spawn sub-clusters or dense swarms of satellites, creating a "thorny" silhouette.
Satellite Position	Control Flow Ratio (Function Level)	Branching Angle. Sharp, jagged angles (<45°) indicate complex control flow; 90° "Circuit Board" patterns indicate linear flow.
Satellite Size	Argument Count	Volume. Large moons represent "Heavy" functions with many inputs; small dots represent lightweight utilities.
Star's Rings	External Library Imports	Accretion Disks. Files tethered to many external dependencies manifest glowing rings, symbolizing a large "Gravity Well."
Star's Position	Semantic Affinity (Directory/Path)	Neighborhoods. Files are grouped into sectoral clusters based on folder structure, creating distinct "Auth," "UI," and "API" continents.