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Original file line number Diff line number Diff line change
@@ -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) {
Expand Down
15 changes: 9 additions & 6 deletions Sprint-1/JavaScript/findCommonItems/findCommonItems.js
Original file line number Diff line number Diff line change
@@ -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)];
}
36 changes: 33 additions & 3 deletions Sprint-1/JavaScript/hasPairWithSum/hasPairWithSum.js
Original file line number Diff line number Diff line change
@@ -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
Expand All @@ -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)
30 changes: 26 additions & 4 deletions Sprint-1/JavaScript/removeDuplicates/removeDuplicates.mjs
Original file line number Diff line number Diff line change
@@ -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
Expand All @@ -17,6 +18,7 @@ export function removeDuplicates(inputSequence) {
currentIndex++
) {
let isDuplicate = false;

for (
let compareIndex = 0;
compareIndex < uniqueItems.length;
Expand All @@ -27,10 +29,30 @@ export function removeDuplicates(inputSequence) {
break;
}
}

if (!isDuplicate) {
uniqueItems.push(inputSequence[currentIndex]);
}
}

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)
Original file line number Diff line number Diff line change
@@ -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)
"""
35 changes: 21 additions & 14 deletions Sprint-1/Python/find_common_items/find_common_items.py
Original file line number Diff line number Diff line change
Expand Up @@ -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)
"""
30 changes: 17 additions & 13 deletions Sprint-1/Python/has_pair_with_sum/has_pair_with_sum.py
Original file line number Diff line number Diff line change
@@ -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


"""
Comment thread
cjyuan marked this conversation as resolved.
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)
"""
32 changes: 14 additions & 18 deletions Sprint-1/Python/remove_duplicates/remove_duplicates.py
Original file line number Diff line number Diff line change
@@ -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)
"""
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