Tag: 알고리즘
-
코딩테스트 완벽 대비 가이드: 알고리즘 유형부터 문제 풀이 전략까지
Solve Two Sum in O(n) with hash maps instead of O(n²) brute force. Compare 3 approaches with time complexity proof and LeetCode patterns.
-
백트래킹(Backtracking) 실전 풀이 전략 – N-Queen부터 순열/조합 생성까지
Solve N-Queen, permutations, and Sudoku with backtracking. Python implementations with pruning strategies that actually speed things up.
-
다이나믹 프로그래밍(DP) 패턴별 완전 정복 – Knapsack부터 비트마스킹 DP까지
Master DP patterns that solve 80% of coding interviews: Knapsack, LIS, LCS, and bitmask DP with Python code and O(n) optimizations.
-
BFS/DFS 완전 정복 – 그래프 탐색 알고리즘 구현부터 실전 응용까지
BFS vs DFS: when to use each, how they differ in time complexity, and 5 graph problems you can't solve without mastering both algorithms.
-
슬라이딩 윈도우 패턴: O(N²)에서 O(N)으로 최적화
Speed up subarray problems from O(n²) to O(n) using sliding window. Fixed vs variable size, two pointers, and 4 LeetCode patterns solved.
-
동적 계획법(DP) 코딩테스트 완전 정복: 개념부터 실전 문제까지
Master dynamic programming for coding interviews: derive recurrence relations, optimize space complexity, solve knapsack and LIS in Python.
-
투 포인터(Two Pointers) 알고리즘 완벽 가이드 – 배열 탐색 O(n) 최적화의 정석
Two Pointers drops array search from O(n²) to O(n). Master same-direction and opposite-direction patterns with 6 LeetCode problems solved.
-
코딩테스트 필수 유형: 투 포인터(Two Pointers) 완벽 가이드 – 연습 문제와 상세 풀이
Two Pointers solves sum problems in O(N) vs brute-force O(N²). Master two-sum, subarray sum, and three-sum with step-by-step Python solutions.