Intuition behind using a monotonic stack

Question

I am solving a question on LeetCode.com:

Given an array of integers A, find the sum of min(B), where B ranges over every (contiguous) subarray of A. Since the answer may be large, return the answer modulo 10^9 + 7.

Input: [3,1,2,4]
Output: 17
Explanation: Subarrays are [3], [1], [2], [4], [3,1], [1,2], [2,4], [3,1,2], [1,2,4], [3,1,2,4]. Minimums are 3, 1, 2, 4, 1, 1, 2, 1, 1, 1. Sum is 17.

A highly upvoted solution is as below:

class Solution {
public:
  int sumSubarrayMins(vector<int>& A) {
    stack<pair<int, int>> in_stk_p, in_stk_n;
    // left is for the distance to previous less element
    // right is for the distance to next less element
    vector<int> left(A.size()), right(A.size());

    //initialize
    for(int i = 0; i < A.size(); i++) left[i] =  i + 1;
    for(int i = 0; i < A.size(); i++) right[i] = A.size() - i;

    for(int i = 0; i < A.size(); i++){
      // for previous less
      while(!in_stk_p.empty() && in_stk_p.top().first > A[i]) in_stk_p.pop();
      left[i] = in_stk_p.empty()? i + 1: i - in_stk_p.top().second;
      in_stk_p.push({A[i],i});

      // for next less
      while(!in_stk_n.empty() && in_stk_n.top().first > A[i]){
        auto x = in_stk_n.top();in_stk_n.pop();
        right[x.second] = i - x.second;
      }
      in_stk_n.push({A[i], i});
    }

    int ans = 0, mod = 1e9 +7;
    for(int i = 0; i < A.size(); i++){
      ans = (ans + A[i]*left[i]*right[i])%mod;
    }
    return ans;
  }
};

My question is: what is the intuition behind using a monotonically increasing stack for this? How does it help calculate the minimums in the various subarrays?

Answer 1

Visualize the array as a line graph, with (local) minima as valleys. Each value is relevant for a range that extends from just after the previous smaller value (if any) to just before the next smaller value (if any). (Even a value larger than its neighbors matters when considering the singleton subarray that contains it.) The variables left and right track that range.

Recognizing that a value shadows every value larger than it in each direction separately, the stack maintains a list of previous, unshadowed minima for two purposes: identifying how far back a new small number’s range extends and (at the same time) how far forward the invalidated minima’s ranges extend. The code uses a separate stack for each purpose, but there’s no need: each has the same contents after every iteration of the (outer) loop.