Maximum Subarray
The maximum subarray problem asks for the contiguous segment with the largest sum. Kadane's algorithm solves it in O(n).
이 멘탈 모델부터 시작하세요
The maximum subarray problem asks for the contiguous segment with the largest sum. Kadane's algorithm solves it in O(n).
불필요한 전문용어 없이 동작 방식 이해하기
At each position decide whether to extend the previous segment or start fresh from the current value.
Track both the best segment ending here and the best seen globally.
알고리즘을 연속된 의사결정으로 읽기
Define the state precisely.
Write the transition/choice from smaller states.
Set base cases, then decide memoization, tabulation or backtracking.
Read a tiny input by hand and write down the state after every important operation. For Maximum Subarray, the goal is to make the invariant visible rather than to memorize code.
function maxSubarray(a) {
let ending = a[0];
let best = a[0];
for (let i = 1; i < a.length; i++) {
ending = Math.max(a[i], ending + a[i]);
best = Math.max(best, ending);
}
return best;
}문법을 외우지 마세요. 각 줄에서 바뀌는 상태를 따라가고 위에서 설명한 불변식과 연결하세요.
O(n) with Kadane
Do not quote this complexity mechanically.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.
적합한 경우
- Use DP when subproblems overlap and optimal solutions can be composed from smaller optimal states.
보통 어디에서 문제가 생기는가
- Writing recurrence before defining state.
- Using DP when state space is larger than the original problem.
전문적인 답변 구조
Explain the local decision behind Kadane, not only the two variable names. Also handle the all-negative case correctly.
What problem does Maximum Subarray solve?
The maximum subarray problem asks for the contiguous segment with the largest sum. Kadane's algorithm solves it in O(n).
복잡도에 대해 무엇을 언급해야 하나요?
Its typical cost here is O(n) with Kadane, but a complete answer should connect that cost to the representation, input constraints and the dominant operations.
가장 흔한 실수는 무엇인가요?
Writing recurrence before defining state.