# soulmachine/acm-cheat-sheet

Acm Cheat Sheet

Repository: https://github.com/soulmachine/acm-cheat-sheet
Canonical: https://ross.abutalabs.com/products/acm-cheat-sheet
Language: TeX
License Family: other
Last push: 2022-09-11T09:04:06+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4890, "days_push": 1452, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1716, forks 531 (observed 2026-08-28T04:05:26.352249+00:00)

## What it is
A LaTeX-based cheat sheet of hand-written code for competitive programming, available in C, C++, and Java versions and compiled to PDF. It serves as a reference manual of common algorithms and data structures for ACM-style contests and coding interviews.

## Use cases
- prepare for ACM competitive programming contests
- review common algorithms and data structures before a coding interview
- find reference implementations of classic algorithms in C, C++, or Java
- compile a printable algorithm reference PDF from LaTeX source
- study handwritten-style code templates for online judges

## When to choose
- you want a compact, printable reference of classic algorithm implementations
- you prefer C, C++, or Java code samples for contest practice
- you want to build the PDF yourself with LaTeX or Docker

## When to avoid
- you need an executable library or tool rather than a document
- you want interactive tutorials or exercises instead of reference code
- you need up-to-date coverage of recent contest techniques, since updates are infrequent

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, pdf
- domain: education, tutorials
- platform: cross-platform
- tags: competitive-programming, cheat-sheet, latex, interview-preparation, data-structures, algorithms, docker

## Member repositories
- soulmachine/acm-cheat-sheet (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:26.352249+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 2026-08-30T03:34:15.981365+00:00, confidence not recorded.
  - readme: https://github.com/soulmachine/acm-cheat-sheet (fetched 2026-08-28T04:05:26.352249+00:00, sha 543c251ea1fa)
- Data as of 2026-08-30T08:39:29.467469+00:00.