What is the best approach to solve Merge Sorted Array?

The optimal approach for Merge Sorted Array is the "Optimal — Three Pointers From the Back" technique. It runs in O(m+n) time and uses O(1) space. Since nums1 has space at the end, fill from back to front. Compare the largest remaining elements from nums1 (pointer p1=m-1) and nums2 (pointer p2=n-1), placing the larger at position p (starts at m+

What is the time complexity of Merge Sorted Array?

The optimal solution for Merge Sorted Array has a time complexity of O(m+n) and a space complexity of O(1), achieved using the Two Pointers pattern.

Is Merge Sorted Array a Easy LeetCode problem?

Yes, LeetCode #88 (Merge Sorted Array) is rated Easy. It uses the Two Pointers pattern and is commonly asked in interviews at Microsoft, Amazon, Google.

How to solve Merge Sorted Array in Python, Java, C++, and JavaScript?

LumiChats provides complete solutions for Merge Sorted Array in Python, Java, C++, and JavaScript, along with step-by-step visual animations and time/space complexity analysis. All solutions are free to view.

#88EasyTwo Pointers

Merge Sorted Array

Merge two sorted arrays in-place by filling from the back.

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Problem Statement

You are given two integer arrays nums1 and nums2, sorted in non-decreasing order, and two integers m and n. Merge nums2 into nums1 in-place. nums1 has a length of m + n, where the last n elements are 0 (placeholders).

Examples

Example 1

Input:nums1=[1,2,3,0,0,0], m=3, nums2=[2,5,6], n=3

Output:[1,2,2,3,5,6]

Example 2

Input:nums1=[1], m=1, nums2=[], n=0

Output:[1]

Constraints

nums1.length == m + n
0 ≤ m, n ≤ 200
1 ≤ m + n ≤ 200
-10⁹ ≤ nums1[i], nums2[j] ≤ 10⁹

Solutions

Copy and Sort

TimeO((m+n) log(m+n))SpaceO(1)

Copy nums2 elements into nums1 after the first m elements, then sort. Simple but doesn't use the sorted property.

Visual Animation

def merge(nums1, m, nums2, n) -> None:
    nums1[m:] = nums2
    nums1.sort()

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