Algorithms and Data Structures

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

01-sorting — Sorting Algorithms

02-data-structures — Data Structures

03-graph — Graph Algorithms

04-advanced — Advanced Algorithms

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

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