Sliding Window Patterns

Sliding Window pattern in DSA questions

1. Maximum Sum Subarray of Size K (easy)

Questions Details

Given an array of positive numbers and a positive number ‘k’, find the maximum sum of any contiguous subarray of size ‘k’.

</br> Example 1: </br> Input: [2, 1, 5, 1, 3, 2], k=3 </br> Output: 9 Explanation: Subarray with maximum sum is [5, 1, 3]. * Example 2: Input: [2, 3, 4, 1, 5], k=2 Output: 7 Explanation: Subarray with maximum sum is [3, 4].

Implementation

• Python
• js
• ruby

• def max_sub_array_of_size_k(k, arr):
    max_sum , window_sum = 0, 0
    window_start = 0
  
    for window_end in range(len(arr)):
      window_sum += arr[window_end]  # add the next element
      # slide the window, we don't need to slide if we've not hit 
      the required window size of 'k'
      if window_end >= k-1:
        max_sum = max(max_sum, window_sum)
        window_sum -= arr[window_start]  # subtract the element going out
        window_start += 1  # slide the window ahead
    return max_sum
  
  def main():
    print("Maximum sum of a subarray of size K: " + 
    str(max_sub_array_of_size_k(3, [2, 1, 5, 1, 3, 2])))
    print("Maximum sum of a subarray of size K: " + 
    str(max_sub_array_of_size_k(2, [2, 3, 4, 1, 5])))
  
  main()
  

• console.log('hello');
  

• pputs 'hello'
  

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## Heading 1. A numbered 2. list * With some * Sub bullets

1. Assert: Type(iterator) is Object.
2. Assert: completion is a Completion Record.
3. Let hasReturn be HasProperty(iterator, "return").
4. ReturnIfAbrupt(hasReturn).
   1. If hasReturn is true, then
      1. Let innerResult be Invoke(iterator, "return", ( )).
      2. If completion.[[type]] is not throw and innerResult.[[type]] is throw, then
         1. Return innerResult.
5. Return completion.