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LeetCode
  • Overview
  • Mixed / Design
    • Two Sum (4 Qs)
      • 0001. Two Sum
      • 0167. Two Sum II - Input array is sorted
      • 0170. Two Sum III - Data structure design
      • 0653. Two Sum IV - Input is a BST
    • 0015. 3Sum
    • 0208. Implement Trie (Prefix Tree)
  • String
    • 0014. Longest Common Prefix
    • 0028. Implement strStr()
    • 0344. Reverse String
    • 0151. Reverse Words in a String
    • 0557. Reverse Words in a String III
    • 0067. Add Binary
    • 0415. Add Strings
    • 0038. Count and Say
    • 0394. Decode String
    • 0953. Verifying an Alien Dictionary
    • 0020. Valid Parentheses
  • Linked List
    • 0002. Add Two Numbers
    • 0445. Add Two Numbers II
    • 0021. Merge Two Sorted Lists
    • 0023. Merge k Sorted Lists
    • 0206. Reverse Linked List
    • 0019. Remove Nth Node From End of List
  • Tree
    • 0098. Validate BST
    • 0100. Same Tree
    • 0101. Symmetric Tree
    • 0226. Invert Binary Tree
    • 0110. Balanced Binary Tree
    • 0250. Count Univalue Subtrees
    • 0654. Maximum Binary Tree
    • Binary Tree Traversal (7 Qs)
      • 0144. Preorder Traversal
      • 0145. Postorder Traversal
      • 0094. Inorder Traversal
      • 0102. Level Order Traversal
      • 0104. Maximum Depth
      • 0111. Minimum Depth
      • 1302. Deepest Leaves Sum
      • 0993. Cousins in Binary Tree
    • N-ary Tree Traversal (4 Qs)
      • 0589. Preorder Traversal
      • 0590. Postorder Traversal
      • 0429. Level Order Traversal
      • 0559. Maximum Depth
    • Convert to BST (2 Qs)
      • 0108. Convert Sorted Array to Binary Search Tree
      • 0109. Convert Sorted List to Binary Search Tree
  • Binary Search
    • 0704. Binary Search
    • 0035. Search Insert Position
    • 0278. First Bad Version
    • 0367. Valid Perfect Square
    • 0069. Sqrt(x)
    • 0875. Koko Eating Bananas
    • 1011. Capacity To Ship Packages Within D Days
    • 0410. Split Array Largest Sum
    • 0004. Median of Two Sorted Arrays
  • Two Pointer
    • 0075. Sort Colors
    • 0088. Merge Sorted Array
    • 0283. Move Zeroes
    • 0125. Valid Palindrome
    • 0011. Container With Most Water
    • 0026. Remove Duplicates from Sorted Array
  • Sliding Window
    • 0003. Longest Substring Without Repeating Characters
  • Sorting
    • 0148. Sort List
    • 0912. Sort an Array
    • 0215. Kth Largest in Array
  • Dynamic Programming
    • 0509. Fibonacci Number
    • 1137. N-th Tribonacci Number
    • 0055. Jump Game
    • 0053. Maximum Subarray
    • 0022. Generate Parentheses
    • 0005. Longest Palindromic Substring
    • 0072. Edit Distance
    • Buy and Sell Stock (6 Qs)
      • 0122. Best Time to Buy and Sell Stock II
      • 0714. Best Time to Buy and Sell Stock with Transaction Fee
      • 0121. Best Time to Buy and Sell Stock
      • 0309. Best Time to Buy and Sell Stock with Cooldown
      • 0123. Best Time to Buy and Sell Stock III
      • 0188. Best Time to Buy and Sell Stock IV
  • DFS / BFS
    • 0200. Number of Islands
  • Math
    • 0007. Reverse Integer
    • 0009. Palindrome Number
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  1. Two Pointer

0088. Merge Sorted Array

Easy | Array + Two Pointers | 16ms (98.22%), 13.3 MB (94.73%)

Previous0075. Sort ColorsNext0283. Move Zeroes

Last updated 3 years ago

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Source: GitHub:

You are given two integer arrays nums1 and nums2, sorted in non-decreasing order, and two integers m and n, representing the number of elements in nums1 and nums2 respectively.

Merge nums1 and nums2 into a single array sorted in non-decreasing order.

The final sorted array should not be returned by the function, but instead be stored inside the array nums1. To accommodate this, nums1 has a length of m + n, where the first m elements denote the elements that should be merged and the last n elements are set to 0 and should be ignored. nums2 has a length of n.

Constraints:

  • nums1.length == m + n

  • nums2.length == n

  • 0 <= m, n <= 200

  • 1 <= m + n <= 200

  • -10^9 <= nums1[i], nums2[j] <= 10^9

Input: nums1 = [1,2,3,0,0,0], m = 3, nums2 = [2,5,6], n = 3
Output: [1,2,2,3,5,6]
Explanation: The arrays we are merging are [1,2,3] and [2,5,6].
The result of the merge is [1,2,2,3,5,6] with the underlined elements coming from nums1.

Input: nums1 = [1], m = 1, nums2 = [], n = 0
Output: [1]
Explanation: The arrays we are merging are [1] and [].
The result of the merge is [1].

Input: nums1 = [0], m = 0, nums2 = [1], n = 1
Output: [1]
Explanation: The arrays we are merging are [] and [1].
The result of the merge is [1].
Note that because m = 0, there are no elements in nums1. The 0 is only there to ensure the merge result can fit in nums1.

Three-pointer is required for placing numbers reversely from the end of array1:

  1. place-pointer: starting from the end, which value is m + n - 1.

  2. array1-pointer: starting from the last element in array 1.

  3. array2-pointer: starting from the last element in array 2.

Note that since the above pointers move forward (index is decreasing in each iteration), if array2-pointer reaches the beginning p2 < 0, we could return directly because array1 is already sorted correctly. On the other hand, we also need to check whether array1-pointer reaches the beginning by p1 >= 0.

class Solution:
    def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
        #  (base case)
        if n == 0: return
        if m == 0: 
            for i in range(n): nums1[i] = nums2[i]
        
        # ==================================================
        #  Array + Three Pointers        (Start from End)  =
        # ==================================================        
        # time  : O(m+n)
        # space : O(1)
        
        p1, p2, placeP = m - 1, n - 1, m + n - 1
        while placeP >= 0:
            if p2 < 0: return
            
            if p1 >= 0 and nums1[p1] >= nums2[p2]:
                nums1[placeP] = nums1[p1]
                p1 -= 1
            else:
                nums1[placeP] = nums2[p2]
                p2 -= 1
                
            placeP -= 1
class Solution {
    /**  
     * @time  : O(m+n)
     * @space : O(1)
     */

    public void merge(int[] nums1, int m, int[] nums2, int n) {
        /* base case */
        if(n == 0) return;
        if(m == 0) {
            for(int i=0 ; i<n ; i++) nums1[i] = nums2[i];
            return;
        }
        
        int p1 = m - 1, p2 = n - 1, placeP = m + n - 1;
        while(placeP >= 0) {
            if(p2 < 0) return;
            
            if(p1 >= 0 && nums1[p1] >= nums2[p2]) {
                nums1[placeP] = nums1[p1];
                p1--;
            } else {
                nums1[placeP] = nums2[p2];
                p2--;
            }
            
            placeP--;
        }
    }
}
LeetCode - Merge Sorted Array
Solution / Performance