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Growing a Dynamic Array

Simulate how a dynamic array doubles its capacity and count the reallocations and copied elements.

배우게 될 내용

  • See how a vector doubles its capacity
  • Count copies made during reallocation
  • Understand why appending stays fast on average

문제

번역본 보기

A dynamic array such as C++ std::vector stores its elements in one block of memory. When the block is full and a new element arrives, it allocates a block twice as large, copies the existing elements over, and frees the old one.

Start with an empty array of capacity initial_capacity and push pushes elements one by one. Before each push, if size == capacity, reallocate: count one reallocation, add the current size to the copied elements, and double the capacity.

Implement dynamic_array_growth(pushes, initial_capacity).

Input

pushes: How many elements are pushed.

initial_capacity: The capacity of the empty array.

Output

Return [reallocations, copied_elements, final_capacity].

제약 조건

0 ≤ pushes ≤ 10^7

1 ≤ initial_capacity ≤ 10^6

예시

예시 1
입력:
pushes = 5
initial_capacity = 1

예상 출력:
expected = [3, 7, 8]
입력:
long long pushes = 5;
long long initial_capacity = 1;

예상 출력:
std::vector<long long> expected = {3, 7, 8};
입력:
long pushes = 5;
long initial_capacity = 1;

예상 출력:
long[] expected = new long[] {3, 7, 8};

설명

Capacity grows 1 → 2 → 4 → 8 when pushing the 2nd, 3rd and 5th elements, copying 1 + 2 + 4 = 7 elements: [3, 7, 8].

예시 2
입력:
pushes = 4
initial_capacity = 4

예상 출력:
expected = [0, 0, 4]
입력:
long long pushes = 4;
long long initial_capacity = 4;

예상 출력:
std::vector<long long> expected = {0, 0, 4};
입력:
long pushes = 4;
long initial_capacity = 4;

예상 출력:
long[] expected = new long[] {0, 0, 4};

설명

All four elements fit in the first block, so nothing is reallocated: [0, 0, 4].

접근 방법

먼저 스스로 풀어 본 뒤 힌트를 하나씩 열어 보세요.

힌트 1

A reallocation happens only when the array is full.

힌트 2

Each time, all current elements are copied and the capacity doubles.

힌트 3

You can jump from one doubling to the next instead of simulating every push.

예상 복잡도

O(log pushes) time, O(1) extra space

참고 자료

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