# jaehyunp/stanfordacm

Stanford ACM-ICPC related materials

Repository: https://github.com/jaehyunp/stanfordacm
Canonical: https://ross.abutalabs.com/products/stanfordacm
Language: HTML
License: MIT
License Family: permissive
Last push: 2020-12-24T01:43:34+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4458, "days_push": 2079, "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 1665, forks 495 (observed 2026-08-28T04:05:19.086039+00:00)

## What it is
A repository of Stanford ACM-ICPC team materials, including a contest team notebook of reference code and complete lecture slides for the CS 97SI programming contests course. Python scripts generate the notebook as PDF (via LaTeX) or HTML with syntax highlighting.

## Use cases
- prepare for ACM-ICPC programming contests
- build a printable team notebook of algorithm reference code
- learn competitive programming algorithms from lecture slides
- find tested implementations of common algorithms in C++, Java, and Python
- generate a syntax-highlighted PDF codebook for contests

## When to choose
- you are training for ICPC or similar competitive programming contests
- you want a curated, contest-legal reference code notebook
- you need structured lecture material on algorithms and data structures

## When to avoid
- you need a maintained software library or package for production use
- you want modern tooling or active development (last release 2020)
- you need algorithm implementations as installable, tested libraries

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: education, programming-languages, tutorials
- platform: python, cli, cross-platform
- tags: competitive-programming, acm-icpc, team-notebook, reference-code, latex, lecture-slides, algorithms

## Member repositories
- jaehyunp/stanfordacm (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:19.086039+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 2026-08-30T03:44:26.455527+00:00, confidence not recorded.
  - readme: https://github.com/jaehyunp/stanfordacm (fetched 2026-08-28T04:05:19.086039+00:00, sha 13a1f51bf54c)
- Data as of 2026-08-30T08:39:29.467469+00:00.