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algorithm-and-data-structures

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algorithm-and-data-structures

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SKILL.md

日本語版

Algorithms and Data Structures

Algorithms and data structures form the foundation of programming. This guide systematically covers complexity analysis, sorting algorithms, tree structures, graph algorithms, dynamic programming, and competitive programming techniques.

Target Audience

Engineers who want to systematically learn algorithms
Those preparing for coding interviews
Those interested in competitive programming

Prerequisites

Basic programming (loops, conditionals, functions)
Basic mathematics (logarithms, exponents, sets)

Study Guide

00-basics — Fundamentals

#	File	Description

01-sorting — Sorting Algorithms

#	File	Description

02-data-structures — Data Structures

#	File	Description

03-graph — Graph Algorithms

#	File	Description

04-advanced — Advanced Algorithms

#	File	Description

Quick Reference

Complexity Cheat Sheet:
  O(1)        — Hash table lookup
  O(log n)    — Binary search
  O(n)        — Linear search
  O(n log n)  — Merge sort, quicksort (average)
  O(n^2)      — Bubble sort, insertion sort
  O(2^n)      — Subset enumeration
  O(n!)       — Permutation enumeration

References

Cormen, T. et al. "Introduction to Algorithms." MIT Press, 2022.
Sedgewick, R. "Algorithms." Addison-Wesley, 2011.
Skiena, S. "The Algorithm Design Manual." Springer, 2020.

Maintainer

Gaku52 Core maintainer

Source details

Full Name: Gaku52/claude-code-skills
Branch: main
Path in repo: 01-cs-fundamentals/algorithm-and-data-structures
License: MIT License
Topics: claude-code ai-coding developer-tools knowledge-base software-engineering learning-resources

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