# jdah/doomenstein-3d

Wolfenstein/DOOM style software renderers

Repository: https://github.com/jdah/doomenstein-3d
Canonical: https://ross.abutalabs.com/products/doomenstein-3d
Language: C
License: MIT
License Family: permissive
Last push: 2023-03-10T11:30:14+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 91
- inputs: {"age_days": 1277, "days_push": 1272, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1062, forks 75 (observed 2026-08-28T04:03:26.086856+00:00)

## What it is
A pair of small C programs implementing Wolfenstein 3D and DOOM style software renderers from scratch. It serves as a compact, readable reference for classic raycasting and BSP-style rendering techniques.

## Use cases
- learn how doom-style software rendering works
- understand raycasting engines
- study retro fps renderer internals in c
- reference implementation of wolfenstein 3d renderer
- starting point for writing a software renderer

## When to choose
- you want minimal, readable C source code explaining classic FPS rendering
- you need a small educational codebase to study raycasting and doom-style rendering

## When to avoid
- you need a full playable game with levels, enemies, and assets
- you want a modern GPU-accelerated game engine

## Facets
- artifact type: learning-resource
- maturity: stable
- function: graphics, simulation
- domain: graphics
- platform: cpp, windows, cross-platform
- tags: software-renderer, raycasting, doom, wolfenstein-3d, c, educational, retro-gaming, game-development, algorithms, linux, macos

## Member repositories
- jdah/doomenstein-3d (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:26.086856+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:56:45.085033+00:00, confidence not recorded.
  - readme: https://github.com/jdah/doomenstein-3d (fetched 2026-08-28T04:03:26.086856+00:00, sha 62a52eab38c1)
- Data as of 2026-08-30T08:39:29.467469+00:00.