Implement sliding window algorithms for fixed and dynamic sizes with tests (#1765)

* feat: implement sliding window algorithms for fixed and dynamic sizes with tests

* update directory file for sliding windows

Sliding-Windows/MaxSumSubarrayFixed.js

@@ -0,0 +1,26 @@
+/**
+ * Function to find the maximum sum of a subarray of fixed size k.
+ *
+ * @param {number[]} arr - The input array of numbers.
+ * @param {number} k - The fixed size of the subarray.
+ * @returns {number} - The maximum sum of any subarray of size k.
+ * @throws {RangeError} - If k is larger than the array length or less than 1.
+ */
+export function maxSumSubarrayFixed(arr, k) {
+  if (k > arr.length || k < 1) {
+    throw new RangeError(
+      'Subarray size k must be between 1 and the length of the array'
+    )
+  }
+  let maxSum = 0
+  let windowSum = 0
+  for (let i = 0; i < k; i++) {
+    windowSum += arr[i]
+  }
+  maxSum = windowSum
+  for (let i = k; i < arr.length; i++) {
+    windowSum += arr[i] - arr[i - k]
+    maxSum = Math.max(maxSum, windowSum)
+  }
+  return maxSum
+}