hamdiheb · hamdiheb · Jul 15, 2026 · Jul 15, 2026 · Jul 15, 2026 · Jul 15, 2026
diff --git a/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js b/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js
@@ -5,30 +5,36 @@
  * and the "product" is every number multiplied together
  * so for example: [2, 3, 5] would return
  * {
- *   "sum": 10, // 2 + 3 + 5
- *   "product": 30 // 2 * 3 * 5
+ *   "sum": 10,
+ *   "product": 30
  * }
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n)
+ * The function loops through the array once, processing each element exactly once.
+ *
+ * Space Complexity: O(1)
+ * Only two variables (sum and product) are used, regardless of the input size.
+ *
+ * Optimal Time Complexity: O(n)
+ * This is the optimal time complexity because every element must be read at least
+ * once to calculate both the sum and the product.
  *
  * @param {Array<number>} numbers - Numbers to process
  * @returns {Object} Object containing running total and product
  */
 export function calculateSumAndProduct(numbers) {
-  let sum = 0;
-  for (const num of numbers) {
-    sum += num;
-  }
+  let sum = 0
+  let product = 1
 
-  let product = 1;
+  // Refactored to use a single loop instead of two.
+  // This reduces the number of iterations but keeps the time complexity at O(n).
   for (const num of numbers) {
-    product *= num;
+    sum += num
+    product *= num
   }
 
   return {
-    sum: sum,
-    product: product,
-  };
+    sum,
+    product,
+  }
 }
diff --git a/Sprint-1/JavaScript/findCommonItems/findCommonItems.js b/Sprint-1/JavaScript/findCommonItems/findCommonItems.js
@@ -1,14 +1,21 @@
 /**
  * Finds common items between two arrays.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n × m)
+ * The function loops through the first array and uses `includes()` to search
+ * the second array for each element.
+ *
+ * Space Complexity: O(n)
+ * A new array is created to store the matching items.
+ *
+ * Optimal Time Complexity: O(n × m)
+ * The complexity cannot be reduced without using an additional lookup
+ * data structure such as a Set or a hash map.
  *
  * @param {Array} firstArray - First array to compare
  * @param {Array} secondArray - Second array to compare
  * @returns {Array} Array containing unique common items
  */
 export const findCommonItems = (firstArray, secondArray) => [
   ...new Set(firstArray.filter((item) => secondArray.includes(item))),
-];
+]
diff --git a/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js b/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js
@@ -1,21 +1,29 @@
 /**
  * Find if there is a pair of numbers that sum to a given target value.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Original Time Complexity: O(n²)
+ * The original code uses nested loops to compare every possible pair of numbers.
+ *
+ * Space Complexity: O(n)
+ * A Set is used to store numbers that have already been seen.
+ *
+ * Optimal Time Complexity: O(n)
+ * The array is traversed once, and Set lookups are O(1) on average.
  *
  * @param {Array<number>} numbers - Array of numbers to search through
  * @param {number} target - Target sum to find
  * @returns {boolean} True if pair exists, false otherwise
  */
 export function hasPairWithSum(numbers, target) {
-  for (let i = 0; i < numbers.length; i++) {
-    for (let j = i + 1; j < numbers.length; j++) {
-      if (numbers[i] + numbers[j] === target) {
-        return true;
-      }
+  const seen = new Set()
+
+  for (const num of numbers) {
+    if (seen.has(target - num)) {
+      return true
     }
+
+    seen.add(num)
   }
-  return false;
+
+  return false
 }
diff --git a/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs b/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
@@ -1,36 +1,19 @@
 /**
- * Remove duplicate values from a sequence, preserving the order of the first occurrence of each value.
+ * Remove duplicate items from a sequence.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Original Time Complexity: O(n²)
+ * The original code uses a nested loop to compare every item with the
+ * previously collected unique items.
  *
- * @param {Array} inputSequence - Sequence to remove duplicates from
- * @returns {Array} New sequence with duplicates removed
+ * Space Complexity: O(n)
+ * A new collection is created to store unique items.
+ *
+ * Optimal Time Complexity: O(n)
+ * A Set allows constant-time lookups, so each item only needs to be checked once.
+ *
+ * @param {Array} inputSequence - Sequence containing possible duplicates
+ * @returns {Array} Sequence containing only unique items
  */
 export function removeDuplicates(inputSequence) {
-  const uniqueItems = [];
-
-  for (
-    let currentIndex = 0;
-    currentIndex < inputSequence.length;
-    currentIndex++
-  ) {
-    let isDuplicate = false;
-    for (
-      let compareIndex = 0;
-      compareIndex < uniqueItems.length;
-      compareIndex++
-    ) {
-      if (inputSequence[currentIndex] === uniqueItems[compareIndex]) {
-        isDuplicate = true;
-        break;
-      }
-    }
-    if (!isDuplicate) {
-      uniqueItems.push(inputSequence[currentIndex]);
-    }
-  }
-
-  return uniqueItems;
+  return [...new Set(inputSequence)]
 }