# ropalma/ICMC-USP

"If You're Going Through Hell, Keep Going" - Winston Churchill :turtle: :squirrel:

Repository: https://github.com/ropalma/ICMC-USP
Canonical: https://ross.abutalabs.com/products/icmc-usp
Language: C
License Family: other
Last push: 2019-03-22T06:47:07+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": 2717, "days_push": 2721, "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 1095, forks 343 (observed 2026-08-28T04:03:34.292086+00:00)

## What it is
A curated list of learning resources for computer science students, originally built around the ICMC-USP curriculum. It collects links to courses, books, videos, and practice sites covering algorithms, data structures, C programming, and software engineering roadmaps.

## Use cases
- find resources to learn algorithms and data structures
- study plan for computer science self-taught learners
- practice coding problems for interviews
- learn C programming from scratch
- find Big O and complexity explanations
- discover coding practice platforms like HackerRank and Project Euler

## When to choose
- you are a CS student or self-learner wanting a curated starting point
- you want Portuguese and English learning resources for algorithms and C
- you need a roadmap for software engineering fundamentals

## When to avoid
- you need runnable software or a library
- you want an actively maintained, comprehensive awesome list
- you need structured course content rather than links

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: education, developer-tools, programming-languages
- platform: cross-platform
- tags: awesome-list, curated-resources, computer-science, study-guide, brazilian-portuguese, usp, algorithms, data-structures

## Member repositories
- ropalma/ICMC-USP (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:34.292086+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 2026-08-30T06:47:17.086965+00:00, confidence not recorded.
  - readme: https://github.com/ropalma/ICMC-USP (fetched 2026-08-28T04:03:34.292086+00:00, sha 15c5a73b8ae4)
- Data as of 2026-08-30T08:39:29.467469+00:00.