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London | 25-SDC-Nov | Aida Eslamimoghadam | Sprint 1 | Analyse and refactor functions #141
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c0f3080
use single loop to calculate sum and product
aydaeslami 5c99d88
use Set for faster lookup
aydaeslami 4530871
use Set to improve
aydaeslami 810820e
use Set to remove duplicates
aydaeslami f396f7a
use single loop
aydaeslami 12f0bee
create set for faster lookup
aydaeslami b5e1e07
use set to improve
aydaeslami b7a255f
use set to remove duplicates
aydaeslami 779628c
Refactor: Use Set intersection to find common items
aydaeslami 18ef494
Refactor: Use set intersection
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35 changes: 14 additions & 21 deletions
35
Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,36 +1,29 @@ | ||
| /** | ||
| * Remove duplicate values from a sequence, preserving the order of the first occurrence of each value. | ||
| * | ||
| * Time Complexity: | ||
| * Time Complexity: | ||
| * ANSWER:O(n) | ||
| Because the array is looped through once. | ||
| * Space Complexity: | ||
| ANSWER:O(n) | ||
| Because a Set is used to track seen items. | ||
| * Optimal Time Complexity: | ||
| ANSWER:O(n) | ||
| Each item is processed once using a Set for lookup. | ||
| * | ||
| * @param {Array} inputSequence - Sequence to remove duplicates from | ||
| * @returns {Array} New sequence with duplicates removed | ||
| */ | ||
| export function removeDuplicates(inputSequence) { | ||
| const uniqueItems = []; | ||
| const seen = new Set(); | ||
| const result = []; | ||
|
|
||
| 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]); | ||
| for (const item of inputSequence) { | ||
| if (!seen.has(item)) { | ||
| seen.add(item); | ||
| result.push(item); | ||
| } | ||
| } | ||
|
|
||
| return uniqueItems; | ||
| return result; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -9,13 +9,8 @@ def find_common_items( | |
| """ | ||
| Find common items between two arrays. | ||
|
|
||
| Time Complexity: | ||
| Space Complexity: | ||
| Optimal time complexity: | ||
| Time Complexity: O(n + m) process both sequences | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The complexity of the original implementation is not O(n+m). |
||
| Space Complexity:O(n + m) two sets are created | ||
| Optimal time complexity:O(n + m) must check all elements | ||
| """ | ||
| 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) | ||
| return common_items | ||
| return list(set(first_sequence).intersection(second_sequence)) | ||
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I think "Time Complexity" here refers to the time complexity of the original implementation, and "Optimal Time Complexity" refers to the time complexity of the refactored version. (Otherwise they will always have the same complexity)