# BedirT/ACM-ICPC-Preparation

ACM-ICPC Preparation Guide

Repository: https://github.com/BedirT/ACM-ICPC-Preparation
Canonical: https://ross.abutalabs.com/products/acm-icpc-preparation
Language: Python
License: MIT
License Family: permissive
Topics: algorithm, curriculum, programming-language, acm-icpc, competitive-programming
Last push: 2026-08-19T18:33:02+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 3776, "days_push": 14, "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 2496, forks 696 (observed 2026-08-28T04:06:56.714460+00:00)

## What it is
A structured 20-week curriculum for learning algorithms and data structures aimed at ACM-ICPC competitive programming. It curates external resources, reference implementations, and practice problems from sites like Codeforces, Leetcode, and Hackerrank.

## Use cases
- prepare for the ACM-ICPC contest
- study algorithms and data structures week by week
- practice coding interview questions
- improve algorithmic thinking
- find curated competitive programming problems
- supplement college algorithms coursework

## When to choose
- you want a structured, week-by-week study plan for competitive programming
- you are preparing for technical interviews and need algorithm practice
- you prefer curated external resources plus reference code and problems

## When to avoid
- you need a complete curriculum now - only 8 of 20 weeks are finished
- you want an interactive judge or auto-graded exercises rather than links to external sites
- you need advanced topics beyond the listed data structures and algorithms

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: tutorials, education
- platform: cross-platform
- tags: competitive-programming, acm-icpc, curriculum, data-structures, interview-preparation, algorithms

## Member repositories
- BedirT/ACM-ICPC-Preparation (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:56.714460+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 2026-08-30T02:27:09.285964+00:00, confidence not recorded.
  - readme: https://github.com/BedirT/ACM-ICPC-Preparation (fetched 2026-08-28T04:06:56.714460+00:00, sha 89c55fc3c11b)
- Data as of 2026-08-30T08:39:29.467469+00:00.