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Standard Algorithms Videos 19 videos

AP Computer Science 2.1 Standard Algorithms
432 Views

APCS: Standard Algorithms Drill 2, Problem 1. How much slower is InefficientSum than EfficientSum in the best case for an array of n elements?

AP Computer Science 2.5 Standard Algorithms
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In this computer science drill question, figure out which implementation will copy one array over to another.

AP Computer Science 3.3 Standard Algorithms
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AP Computer Science: Standard Algorithms Drill 3, Problem 3. What should go in "expression 1" to satisfy the conditional statement?

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AP Computer Science 4.1 Standard Algorithms 173 Views


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AP Computer Science 4.1 Standard Algorithms. How much slower is InefficiantSum than EfficientSum in the best case for an array of n elements?

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Transcript

00:00

Sorry Here's your shmoop news your it's a maze ing

00:07

and not at all corny Alright sorry Sometimes we just

00:10

do that Alright Moving on you know art ignore it

00:12

Don't throw up art How much slower is inefficient Some

00:16

than efficient Some in the best minimum case for an

00:19

array of n elements right here in the rays list

00:24

go all right here your potential answers How many times

00:30

slower like a rap song All right well to answer

00:35

this one we'll have to figure out how both methods

00:38

work to see exactly what would make one of them

00:40

less efficient than the other So for efficient Some were

00:44

creating a loop that begins with its iterated at one

00:46

and adds the contents of each following array element to

00:49

array in deck zero until we reach the end Yeah

00:53

in effect index zero becomes the running total as we

00:56

travel through the array makes sense and it's pretty efficient

00:59

just like the name says inefficient Some creates a separate

01:03

variable toe hold are running total then visits each element

01:06

of the array as we had done before but here's

01:09

the univision part while the value of the current array

01:12

element is greater than zero It subtract one from it

01:15

and adds one to the some variable Then it checks

01:18

it again and again and again And i will keep

01:20

doing this until the array element here is zero So

01:24

often injure in the array Had a value of say

01:26

fifty We'd have to complete this process fifty times If

01:29

a were a million six hundred four thousand two hundred

01:32

ninety three Well yeah inefficient is the right word for

01:35

it The difference is a bit like someone opening a

01:37

can of corn and eating each nibble it one by

01:39

one versus more standard practise of opening began and chugging

01:43

the entire thing right there in a sec That's The

01:46

new mcdonald's product It's really cool and pride Okay from

01:49

this we can tell that the larger the values aaron

01:52

the array the larger the kansas corn would be and

01:54

the longer inefficient some would take This question is asking

01:57

for the best case scenario And by far the best

02:00

case as far as inefficient Some is concerned would be

02:02

in a ray full of zeros It could be enormous

02:05

Hundreds of thousands of zeros and we'd zip right through

02:08

It practically the same speed as efficient some because we'd

02:10

be avoiding that tedious wild loop entirely The result in

02:14

that best all zero case is that bullet methods would

02:17

run at the same speed or at least at such

02:20

close speeds that it would be difficult to accurately measure 00:02:22.968 --> [endTime] the difference That'll make her answer

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