알고리즘 읽기 노트

Graph Breadth-First Search

BFS explores a graph level by level using a queue. In an unweighted graph it finds shortest paths by number of edges.

유형알고리즘카테고리Graphs깊이초급일반적인 복잡도O(V+E)

짧은 면접 답변

이 멘탈 모델부터 시작하세요

BFS explores a graph level by level using a queue. In an unweighted graph it finds shortest paths by number of edges.

간단한 설명

불필요한 전문용어 없이 동작 방식 이해하기

Enqueue the start and mark it visited.

Repeatedly dequeue one node and enqueue unseen neighbors.

실행

알고리즘을 연속된 의사결정으로 읽기

Define directed/undirected and weighted/unweighted assumptions.

Choose the graph representation.

Track algorithm state and handle disconnected/cyclic cases explicitly.

기억해 둘 작은 예제

Read a tiny input by hand and write down the state after every important operation. For Graph Breadth-First Search, the goal is to make the invariant visible rather than to memorize code.

읽기 쉬운 JavaScript 구현JavaScript

function bfs(graph, start) {
  const seen = new Set([start]);
  const queue = [start];
  let head = 0;
  while (head < queue.length) {
    const node = queue[head++];
    for (const next of graph[node] ?? []) {
      if (!seen.has(next)) {
        seen.add(next);
        queue.push(next);
      }
    }
  }
  return seen;
}

이 코드를 읽는 방법

문법을 외우지 마세요. 각 줄에서 바뀌는 상태를 따라가고 위에서 설명한 불변식과 연결하세요.

복잡도

O(V+E)

Do not quote this complexity mechanically. Ask which operation or input dimension it describes, then derive the cost from the loops, recursion depth, data-structure operations and any preprocessing assumptions.

언제 사용하는가

적합한 경우

Use the algorithm only when its graph assumptions match the problem.

흔한 실수

보통 어디에서 문제가 생기는가

Forgetting disconnected components.
Mixing weighted and unweighted shortest-path algorithms.
Not protecting against revisits/cycles.

면접에서 설명하는 방법

전문적인 답변 구조

The queue is not an implementation detail—it creates level order, which is exactly why unweighted shortest paths work.

문제→핵심 아이디어→불변식 / 상태→Big-O→트레이드오프

빠른 면접 체크

What problem does Graph Breadth-First Search solve?

BFS explores a graph level by level using a queue. In an unweighted graph it finds shortest paths by number of edges.

복잡도에 대해 무엇을 언급해야 하나요?

Its typical cost here is O(V+E), but a complete answer should connect that cost to the representation, input constraints and the dominant operations.

가장 흔한 실수는 무엇인가요?

Forgetting disconnected components.

계속 읽기Graph representationDFS/BFSPriority queues

function bfs(graph, start) { const seen = new Set([start]); const queue = [start]; let head = 0; while (head < queue.length) { const node = queue[head++]; for (const next of graph[node] ?? []) { if (!seen.has(next)) { seen.add(next); queue.push(next); } } } return seen; }