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APCS: Standard Algorithms Drill 2, Problem 1. How much slower is InefficientSum than EfficientSum in the best case for an array of n elements?
In this computer science drill question, figure out which implementation will copy one array over to another.
AP Computer Science: Standard Algorithms Drill 3, Problem 3. What should go in "expression 1" to satisfy the conditional statement?
AP Computer Science 2.3 Standard Algorithms 169 Views
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Description:
AP Computer Science 2.3 Standard Algorithms. What would be the best possible way to sort our sheep?
Transcript
- 00:00
Thank you here's your shmoop du jour loaded with sheet
- 00:06
because we will in have it any other way All
- 00:09
right what would be the best possible way to sort
- 00:10
our sheet They'll be sorted by increasing wool density and
- 00:15
hear your potential And island all right there are more
Full Transcript
- 00:22
than a handful of sorting algorithms and each has its
- 00:25
own strengths and weaknesses It's election sorts main strength is
- 00:29
its simplicity which comes at the price of being usually
- 00:32
the slowest Well it works like this starting at the
- 00:35
beginning of an array it passes over every single element
- 00:37
and finds the smallest value Then it swaps that value
- 00:41
with whatever's in the front of the line and reverses
- 00:44
the entire thing again this time starting from the next
- 00:48
index down What you'll get is a sordid array Eventually
- 00:53
our insertion sort is also pretty simple It starts at
- 00:56
the beginning comparing two elements and move the lesson left
- 00:59
then checks the one immediately left of those two to
- 01:02
see if that newly moved value is smaller still If
- 01:05
so it moves to the left again and so on
- 01:08
Using this mechanism it'll move smaller and smaller values further
- 01:11
and further left until we're left with assorted array merge
- 01:15
sort tackle sorting by breaking one big problem into several
- 01:19
smaller ones Conceptually it divides the unsorted listed this following
- 01:23
father list until each element is its own list a
- 01:25
list with one element Is considered properly sorted then those
- 01:30
properly sorted tiny lists are combined in tow lists of
- 01:33
two elements which are easy to sort and those lists
- 01:36
are combined and sorted into larger lists and so on
- 01:39
until eventually the entire array is once again a single
- 01:41
list and sorted this time well quick sort is another
- 01:45
way of dividing a large problem in the smaller ones
- 01:48
To start an element is selected to be the pivot
- 01:51
all the other elements air then judges being either less
- 01:54
than or greater than a pivot element This ship which
- 01:57
has a wool density of four has had the great
- 02:00
fortune being selected as the pivot well quick sort would
- 02:03
then sort every sheep less than four to the left
- 02:06
and greater than four to the right and those two
- 02:09
groups that have their own pivots and do the same
- 02:11
thing And again And when the whole thing is finally
- 02:13
reconstituted we've got a single big so which one wins
- 02:18
out Well despite being way more complicated algorithms merge sort
- 02:22
and quick sort definitely perform their tasks faster than the
- 02:26
other two with quick sort beating merge sort in most 00:02:29.275 --> [endTime] situations but just barely
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