This code provides a (flawed) attempt at solving the problem...

This code provides a (flawed) attempt at solving the problem of finding the number of continuous subarrays in an array nums whose sum equals k. It is incomplete and incorrect for the general problem. Here's an analysis of what the code is doing:

1. Inputs:

   • nums: A vector of integers.
   • k: An integer representing the target sum.

2. Variable Initialization:

   • cnt is initialized to 0. This variable will keep track of the number of subarrays whose sum is equal to k.

3. Edge Case Check:

   • If nums has a single element and that element equals k, increment cnt by 1. This checks for a single-element array where the element equals the target sum k.

4. Loop Through Pairs of Elements:

   • The for loop starts at index i = 1 and iterates through the rest of the nums array.
   • At each iteration, check:
     • If the sum of the current element (nums[i]) and the previous element (nums[i-1]) equals k.
     • If the current element (nums[i]) on its own is equal to k.
   • If either condition is true, increment cnt.

5. Return the Count:

   • After the loop, return cnt as the result.

Issues with the Code

This code is not solving the problem correctly because:

1. It only considers subarrays of size 1 and size 2. The problem generally requires finding all subarrays, regardless of their size, that sum to k.
2. The logic is incomplete for capturing larger subarrays.

Example Walkthrough

Let's assume nums = [1, 1, 1] and k = 2:

• The correct answer is 2, because the subarrays [1, 1] (at positions [0, 1] and [1, 2]) both sum to 2.
• With the given code:
  • It checks pairs of elements and misses the overlapping parts of larger subarrays.
  • The code would only count the pair [1, 1] once and fail for other cases.

Correct Solution Idea

To properly solve this problem, you can use a prefix sum and a hashmap to efficiently find the number of subarrays summing to k. This ensures all subarray sizes are considered.