53. Maximum Subarray

Problem

Tags: Array, Divide and Conquer, Dynamic Programming

Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.

A subarray is a contiguous part of an array.

Example 1:

Input: nums = [-2,1,-3,4,-1,2,1,-5,4]
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.

Example 2:

Input: nums = [1]
Output: 1

Example 3:

Input: nums = [5,4,-1,7,8]
Output: 23

Constraints:

• 1 <= nums.length <= 10^5
• -10^4 <= nums[i] <= 10^4

Follow up: If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle.

Code

JS

// 53. Maximum Subarray (12/30/53712)
// Runtime: 88 ms (76.98%) Memory: 48.77 MB (94.79%) 

/**
 * @param {number[]} nums
 * @return {number}
 */
function maxSubArray(nums) {
    let max = nums[0],
        current = nums[0];
    nums.shift();
    for (const n of nums) {
        current = Math.max(n, current + n);
        max = Math.max(max, current);
    }
    return max;
}