awesome-competitive-programming vs ACM-ICPC-Algorithms

Competitive programming resources compared

awesome-competitive-programming is a curated directory of learning materials, practice platforms, tools, and communities. ACM-ICPC-Algorithms is a topic-organized collection of algorithm and data structure implementations, with a focus on reference examples.

awesome-competitive-programmingACM-ICPC-Algorithms
Language—C++
LicenseCC-BY-4.0—
Stars14.2k2.3k
Forks2.6k1.3k
Last analyzedOct 10, 2026Oct 22, 2026

Key differences

  • awesome-competitive-programming links to resources across learning, practice, contest planning, tools, and communities; ACM-ICPC-Algorithms focuses on algorithm and data structure examples.
  • awesome-competitive-programming includes courses, books, judges, calendars, and references; ACM-ICPC-Algorithms covers techniques such as graph algorithms, dynamic programming, and data structures.
  • awesome-competitive-programming is a discovery directory rather than a course or practice platform; ACM-ICPC-Algorithms organizes implementations by topic for consultation.
  • awesome-competitive-programming has a CC-BY-4.0 license; ACM-ICPC-Algorithms has no license specified in the supplied metadata.
  • awesome-competitive-programming lists C/C++ and Java references among other resources; ACM-ICPC-Algorithms lists C++ as its repository language, while its README describes a collection spanning several languages.
  • awesome-competitive-programming's latest reported push was in 2024; ACM-ICPC-Algorithms' last reported push was in 2022.

Choose awesome-competitive-programming if you…

  • need a directory of courses, books, practice platforms, and contest-planning resources.
  • want to browse tools, communities, and references across multiple programming topics and languages.
Read the awesome-competitive-programming analysis →

Choose ACM-ICPC-Algorithms if you…

  • want topic-organized reference implementations for common contest algorithms and data structures.
  • are studying standard techniques for ICPC-style contests and prefer examples grouped by problem area.
Read the ACM-ICPC-Algorithms analysis →

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