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35 changes: 33 additions & 2 deletions big_o_exercise/readme.md
Original file line number Diff line number Diff line change
Expand Up @@ -4,16 +4,26 @@

Simplify the following big O expressions as much as possible:

1. `O(n + 10)`
1. `O(n + 10)`
// O(n)
2. `O(100 * n)`
3. `O(25)`
// O(n)
3. `O(1)`
// O(n)
4. `O(n^2 + n^3)`
// O(n^3)
5. `O(n + n + n + n)`
// O(n)
6. `O(1000 * log(n) + n)`
// log(n)
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double check this one - what grows faster, log(n) or n?

7. `O(1000 * n * log(n) + n)`
// nlog(n)
8. `O(2^n + n^2)`
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2^n grows faster than n^2, but we didn't talk about this in class so I wouldn't sweat it.

// O(n^2)
9. `O(5 + 3 + 1)`
// O(1)
10. `O(n + n^(1/2) + n^2 + n * log(n)^10)`
// O(n^2)

### Part 2

Expand All @@ -29,6 +39,12 @@ function logUpTo(n) {
}
}


time: O(n)
space: O(1)



// 2.

function logAtMost10(n) {
Expand All @@ -37,6 +53,10 @@ function logAtMost10(n) {
}
}

time: O(1)
space: O(1)


// 3.

function logAtLeast10(n) {
Expand All @@ -45,6 +65,9 @@ function logAtLeast10(n) {
}
}

time: O(n)
space: O(1)

// 4.

function onlyElementsAtEvenIndex(array) {
Expand All @@ -57,6 +80,10 @@ function onlyElementsAtEvenIndex(array) {
return newArray;
}

time: O(n)
space: O(n)


// 5.

function subtotals(array) {
Expand All @@ -70,4 +97,8 @@ function subtotals(array) {
}
return subtotalArray;
}

time: O(n^2)
space: O(n)

```
13 changes: 0 additions & 13 deletions readme.md

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