vurtun

Gilbert–Johnson–Keerthi (GJK) 3D distance algorithm

The Gilbert–Johnson–Keerthi (GJK) distance algorithm is a method of determining the minimum distance between two convex sets. The algorithm's stability, speed which operates in near-constant time, and small storage footprint make it popular for realtime collision detection.

Unlike many other distance algorithms, it has no requirments on geometry data to be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplices to the correct answer using the Minkowski sum (CSO) of two convex shapes.

RealNeGate

Complete stuff:
  https://xmonader.github.io/letsbuildacompiler-pretty/

Lexers + DFAs:
  https://gist.github.com/pervognsen/218ea17743e1442e59bb60d29b1aa725
 
Parsing:
  https://eli.thegreenplace.net/2012/08/02/parsing-expressions-by-precedence-climbing
 
Backend:

jakubtomsu

// Port of some collision functions to Odin by Jakub Tomšů.
//
// from Real-Time Collision Detection by Christer Ericson, published by Morgan Kaufmann Publishers, © 2005 Elsevier Inc
//
// This should serve as an reference implementation for common collision queries for games.
// The goal is good numerical robustness, handling edge cases and optimized math equations.
// The code isn't necessarily very optimized.
//
// There are a few cases you don't want to use the procedures below directly, but instead manually inline the math and adapt it to your needs.
// In my experience this method is clearer when writing complex level queries where I need to handle edge cases differently etc.