Manchester | 26-SDC-Jun | Fithi Teklom | Sprint 1 | Analyse And Refactor Functions

Sprint-1/JavaScript/calculateSumAndProduct/calculateSumAndProduct.js

@@ -9,26 +9,30 @@
  *   "product": 30 // 2 * 3 * 5
  * }
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity:O(n) — two loops each visit every number.
+ * Space Complexity: O(1) — uses a fixed number of variables.
+ * Optimal Time Complexity: O(n) — every number must be checked.
  *
  * @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 product = 1;
   for (const num of numbers) {
+    sum += num;
     product *= num;
   }
-
   return {
     sum: sum,
     product: product,
   };
 }
+
+/** 
+ After Refactor 
+ * Time Complexity: O(n) — one loop calculates both results.
+ * Space Complexity: O(1) — uses a fixed number of variables.
+ * Optimal Time Complexity: O(n) — every number must be checked.
+ */

Sprint-1/JavaScript/findCommonItems/findCommonItems.js

@@ -1,14 +1,30 @@
 /**
  * Finds common items between two arrays.
  *
- * Time Complexity:
- * Space Complexity:
- * Optimal Time Complexity:
+ * Time Complexity: O(n * m), where as well as m  referes to a size — checks each item in the first array against items in the second array.
+ * Space Complexity: O(n) — creates a filtered array and a Set.
+ * Optimal Time Complexity: O(n + m) — each array can be checked in linear time using a Set.
  *
  * @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 const findCommonItems = (firstArray, secondArray) => {
+  const secondSet = new Set(secondArray);
+  const commonItems = new Set();
+
+  for (const item of firstArray) {
+    if (secondSet.has(item)) {
+      commonItems.add(item);
+    }
+  }
+
+  return [...commonItems];
+}
+
+/**
+ After Refactoring
+ * Time Complexity: O(n + m) — uses a Set to check for common items efficiently.
+ * Space Complexity: O(m + q) — stores items from the second array and the common items, where q is the number of unique matches.
+ * Optimal Time Complexity: O(n + m) — each array is processed in linear time.
+ */

Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js

@@ -1,21 +1,32 @@
 /**
  * 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) — nested loops check pairs of numbers.
+ * Space Complexity: O(1) — uses only a fixed number of variables.
+ * Optimal Time Complexity:O(n) — a Set can find a matching pair in one pass, 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 number of numbers) {
+    const needed = target - number;
+
+    if (seen.has(needed)) {
+      return true;
     }
+
+    seen.add(number);
   }
+
   return false;
 }
+
+/*
+After Refactoring
+ * Time Complexity: O(n) — checks each number once on average.
+ * Space Complexity: O(n) — stores numbers in a Set.
+ * Optimal Time Complexity: O(n) — one pass using a Set, on average.
+ */

Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs

@@ -1,36 +1,20 @@
 /**
  * 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),the nested loops may compare many items against one another.
+ * Space Complexity:O(n) — stores the unique items in a new array.
+ * Optimal Time Complexity: O(n) — a Set can check for duplicates in one pass, on average.
  *
  * @param {Array} inputSequence - Sequence to remove duplicates from
  * @returns {Array} New sequence with duplicates removed
  */
 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)];
 }
+
+/*
+After Refactoring
+ *Time Complexity: O(n) — uses a Set, on average.
+ * Space Complexity: O(n) — stores unique items in a new collection.
+ * Optimal Time Complexity: O(n) — each input item must be checked.
+*/