053. Maximum Subarray.md

Difficulty	Related Topics	Similar Questions
Easy	Array Divide and Conquer Dynamic Programming https://leetcode.com/tag/array https://leetcode.com/tag/divide-and-conquer https://leetcode.com/tag/dynamic-programming	Best Time to Buy and Sell Stock Maximum Product Subarray Degree of an Array https://leetcode.com/problems/best-time-to-buy-and-sell-stock https://leetcode.com/problems/maximum-product-subarray https://leetcode.com/problems/degree-of-an-array

53. Maximum Subarray

Problem:

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

Example:

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

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.

Solution:

DP.

Define f(i) to be the largest sum of a contiguous subarray that ends with nums[i].

If f(i-1) is negative, then nums[i] must be greater than f(i-1) + nums[i].

f(0) = nums[0]
f(i) = max( f(i-1), 0 ) + nums[i]

Then return the largest one.

/**
 * @param {number[]} nums
 * @return {number}
 */
var maxSubArray = function(nums) {
  const len = nums.length
  if (len <= 0) { return 0 }
  const dp = [nums[0]]
  for (let i = 1; i < len; i++) {
    dp[i] = Math.max(dp[i-1], 0) + nums[i]
  }
  return Math.max(...dp)
};

We can also compress the dp array:

/**
 * @param {number[]} nums
 * @return {number}
 */
var maxSubArray = function(nums) {
  let dp = nums[0]
  let max = dp || 0
  for (let i = 1; i < nums.length; i++) {
    max = Math.max(max, dp = Math.max(dp, 0) + nums[i])
  }
  return max
};

Template generated via Leetmark.