diff --git a/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js b/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js
index ce738c33..6e98afb0 100644
--- a/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js
+++ b/Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js
@@ -1,21 +1,42 @@
 /**
  * Calculate the sum and product of integers in a list
  *
- * Note: the "sum" is every number added together
- * and the "product" is every number multiplied together
- * so for example: [2, 3, 5] would return
+ * For example: [2, 3, 5] returns
  * {
- *   "sum": 10, // 2 + 3 + 5
- *   "product": 30 // 2 * 3 * 5
+ *   sum: 10,     // 2 + 3 + 5
+ *   product: 30  // 2 * 3 * 5
  * }
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n)
+ * Space Complexity: O(1)
+ * Optimal Time Complexity: O(n)
  *
  * @param {Array<number>} numbers - Numbers to process
- * @returns {Object} Object containing running total and product
+ * @returns {Object} Object containing sum and product
  */
+
+export function calculateSumAndProduct(numbers) {
+  let sum = 0;
+  let product = 1;
+
+  for (const num of numbers) {
+    sum += num;
+    product *= num;
+  }
+
+  return {
+    sum: sum,
+    product: product,
+  };
+}
+
+// Time complexity is O(n) because we visit each element once.
+
+// Space complexity is O(1) because we use a fixed number of variables,
+// regardless of the length of the input array.
+
+// Optimal time complexity is O(n) because every element must be examined
+// to guarantee the correct sum and product.
 export function calculateSumAndProduct(numbers) {
   let sum = 0;
   for (const num of numbers) {
diff --git a/Sprint-1/JavaScript/findCommonItems/findCommonItems.js b/Sprint-1/JavaScript/findCommonItems/findCommonItems.js
index 5619ae5d..a39b3155 100644
--- a/Sprint-1/JavaScript/findCommonItems/findCommonItems.js
+++ b/Sprint-1/JavaScript/findCommonItems/findCommonItems.js
@@ -1,14 +1,17 @@
 /**
  * Finds common items between two arrays.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n + m)
+ * Space Complexity: O(n + m)
  *
  * @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))),
-];
+
+export function findCommonItems(firstArray, secondArray) {
+  const firstSet = new Set(firstArray);
+  const secondSet = new Set(secondArray);
+
+  return [...firstSet.intersection(secondSet)];
+}
diff --git a/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js b/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js
index dd2901f6..1503ff0a 100644
--- a/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js
+++ b/Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js
@@ -1,9 +1,9 @@
 /**
  * Find if there is a pair of numbers that sum to a given target value.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n²)
+ * Space Complexity: O(1)
+ * Optimal Time Complexity: O(n)
  *
  * @param {Array<number>} numbers - Array of numbers to search through
  * @param {number} target - Target sum to find
@@ -19,3 +19,33 @@ export function hasPairWithSum(numbers, target) {
   }
   return false;
 }
+
+// Time complexity is O(n²) because we use nested loops
+// to compare pairs of numbers in the array.
+
+// Space complexity is O(1) because we only use two variables,
+// i and j, regardless of the array size.
+
+// Optimal time complexity is O(n) because using a Set
+// allows us to find a matching pair in a single loop.
+
+//Improved solution-O(n)
+export function hasPairWithSum(numbers, target) {
+  const seen = new Set();
+
+  for (const num of numbers) {
+    const needed = target - num;
+
+    if (seen.has(needed)) {
+      return true;
+    }
+
+    seen.add(num);
+  }
+
+  return false;
+}
+
+// Time complexity: O(n)
+// Space complexity: O(n)
+// Optimal time complexity: O(n)
diff --git a/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs b/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
index dc5f7711..07039860 100644
--- a/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
+++ b/Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
@@ -1,9 +1,10 @@
 /**
- * Remove duplicate values from a sequence, preserving the order of the first occurrence of each value.
+ * Remove duplicate values from a sequence, preserving the order
+ * of the first occurrence of each value.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n²)
+ * Space Complexity: O(n)
+ * Optimal Time Complexity: O(n)
  *
  * @param {Array} inputSequence - Sequence to remove duplicates from
  * @returns {Array} New sequence with duplicates removed
@@ -17,6 +18,7 @@ export function removeDuplicates(inputSequence) {
     currentIndex++
   ) {
     let isDuplicate = false;
+
     for (
       let compareIndex = 0;
       compareIndex < uniqueItems.length;
@@ -27,6 +29,7 @@ export function removeDuplicates(inputSequence) {
         break;
       }
     }
+
     if (!isDuplicate) {
       uniqueItems.push(inputSequence[currentIndex]);
     }
@@ -34,3 +37,22 @@ export function removeDuplicates(inputSequence) {
 
   return uniqueItems;
 }
+
+// Time complexity is O(n²) because we use nested loops
+// to compare each item with the unique items already found.
+
+// Space complexity is O(n) because we create a new array
+// that may store up to n unique items.
+
+// Optimal time complexity is O(n) because using a Set
+// allows us to check for duplicates more efficiently.
+
+export function removeDuplicates(inputSequence) {
+  const uniqueItems = new Set(inputSequence);
+
+  return [...uniqueItems];
+}
+
+// Time complexity: O(n) on average
+// Space complexity: O(n)
+// Optimal time complexity: O(n)
diff --git a/Sprint-1/Python/calculate_sum_and_product/calculate_sum_and_product.py b/Sprint-1/Python/calculate_sum_and_product/calculate_sum_and_product.py
index cfd5cfdf..2d0dfd19 100644
--- a/Sprint-1/Python/calculate_sum_and_product/calculate_sum_and_product.py
+++ b/Sprint-1/Python/calculate_sum_and_product/calculate_sum_and_product.py
@@ -1,31 +1,19 @@
 from typing import Dict, List
 
-
 def calculate_sum_and_product(input_numbers: List[int]) -> Dict[str, int]:
-    """
-    Calculate the sum and product of integers in a list.
 
-    Note: the sum is every number added together
-    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
-    }
-    Time Complexity:
-    Space Complexity:
-    Optimal time complexity:
-    """
-    # Edge case: empty list
-    if not input_numbers:
-        return {"sum": 0, "product": 1}
+    total_sum = 0
+    total_product = 1
+
+    for number in input_numbers:
+        total_sum += number
+        total_product *= number
 
-    sum = 0
-    for current_number in input_numbers:
-        sum += current_number
+    return {"sum": total_sum, "product": total_product}
 
-    product = 1
-    for current_number in input_numbers:
-        product *= current_number
 
-    return {"sum": sum, "product": product}
+"""
+Time Complexity: O(n)
+Space Complexity: O(1)
+Optimal Time Complexity: O(n)
+"""
diff --git a/Sprint-1/Python/find_common_items/find_common_items.py b/Sprint-1/Python/find_common_items/find_common_items.py
index 478e2efc..4fac72c9 100644
--- a/Sprint-1/Python/find_common_items/find_common_items.py
+++ b/Sprint-1/Python/find_common_items/find_common_items.py
@@ -2,20 +2,27 @@
 
 ItemType = TypeVar("ItemType")
 
-
 def find_common_items(
-    first_sequence: Sequence[ItemType], second_sequence: Sequence[ItemType]
+    first_sequence: Sequence[ItemType],
+    second_sequence: Sequence[ItemType]
 ) -> List[ItemType]:
-    """
-    Find common items between two arrays.
-
-    Time Complexity:
-    Space Complexity:
-    Optimal time complexity:
-    """
-    common_items: List[ItemType] = []
-    for i in first_sequence:
-        for j in second_sequence:
-            if i == j and i not in common_items:
-                common_items.append(i)
+
+    second_set = set(second_sequence)
+    common_items = []
+    seen = set()
+
+    for item in first_sequence:
+        if item in second_set and item not in seen:
+            common_items.append(item)
+            seen.add(item)
+
     return common_items
+
+
+"""
+Find common items between two arrays.
+
+Time Complexity: O(n * m * k)
+Space Complexity: O(k)
+Optimal Time Complexity: O(n + m)
+"""
\ No newline at end of file
diff --git a/Sprint-1/Python/has_pair_with_sum/has_pair_with_sum.py b/Sprint-1/Python/has_pair_with_sum/has_pair_with_sum.py
index fe2da517..cdbd689d 100644
--- a/Sprint-1/Python/has_pair_with_sum/has_pair_with_sum.py
+++ b/Sprint-1/Python/has_pair_with_sum/has_pair_with_sum.py
@@ -1,18 +1,22 @@
-from typing import List, TypeVar
+def has_pair_with_sum(numbers, target_sum):
 
-Number = TypeVar("Number", int, float)
+    seen = set()
 
+    for number in numbers:
+        complement = target_sum - number
 
-def has_pair_with_sum(numbers: List[Number], target_sum: Number) -> bool:
-    """
-    Find if there is a pair of numbers that sum to a target value.
+        if complement in seen:
+            return True
+
+        seen.add(number)
 
-    Time Complexity:
-    Space Complexity:
-    Optimal time complexity:
-    """
-    for i in range(len(numbers)):
-        for j in range(i + 1, len(numbers)):
-            if numbers[i] + numbers[j] == target_sum:
-                return True
     return False
+
+
+"""
+Find if there is a pair of numbers that sum to a target value.
+
+Time Complexity: O(n²)
+Space Complexity: O(1)
+Optimal Time Complexity: O(n)
+"""
\ No newline at end of file
diff --git a/Sprint-1/Python/remove_duplicates/remove_duplicates.py b/Sprint-1/Python/remove_duplicates/remove_duplicates.py
index c9fdbe80..9d69f2f9 100644
--- a/Sprint-1/Python/remove_duplicates/remove_duplicates.py
+++ b/Sprint-1/Python/remove_duplicates/remove_duplicates.py
@@ -1,25 +1,21 @@
-from typing import List, Sequence, TypeVar
+def remove_duplicates(values):
 
-ItemType = TypeVar("ItemType")
-
-
-def remove_duplicates(values: Sequence[ItemType]) -> List[ItemType]:
-    """
-    Remove duplicate values from a sequence, preserving the order of the first occurrence of each value.
-
-    Time complexity:
-    Space complexity:
-    Optimal time complexity:
-    """
     unique_items = []
+    seen = set()
 
     for value in values:
-        is_duplicate = False
-        for existing in unique_items:
-            if value == existing:
-                is_duplicate = True
-                break
-        if not is_duplicate:
+        if value not in seen:
             unique_items.append(value)
+            seen.add(value)
 
     return unique_items
+
+
+"""
+Remove duplicate values from a sequence,
+preserving the order of the first occurrence.
+
+Time complexity: O(n²)
+Space complexity: O(n)
+Optimal time complexity: O(n)
+"""