# 07 - Insertion Sort

1. Insertion sort is a simple sorting algorithm that works the way most people sort playing cards in their hands

TRUE

FALSE

2. The basic idea behind insertion sort is to divide our list into two portions:

the larger portion and the smaller portion

a sorted portion and an unsorted portion

x' and 'y' where x is always just 1 card or element

None of the above

3. At each step of the algorithm an element is moved from the ..

None of the above

unsorted portion into the unsorted portion

unsorted portion into the sorted portion until the whole list is sorted

sorted portion into the unsorted portion until the list is unsorted

4. Typically, the sorted numbers go to the _____of the unsorted numbers.

behind

infront

right

left

5. In the following list what is '23'?
23,42,4,16,8,15

The end point of our unsorted portion

The start and end of our unsorted portion

None of the above

The start and end of our sorted portion

6. 42 is the first element in the unsorted portion and we proceed in the algorithm to …..
23,42,4,16,8,15

compare the 42 to the 23 (23 being the only element in our sorted element)

None of the above

compare the 42 to the 4

compare the 42 to the 15

7. If 42 is larger than 23, we can…..
23,42,4,16,8,15

remove 42 and take it to the end of the list as it is largest (e.g. 23,4,16,8,15,42)

None of the above

include 42 before the 23 (e.g. 42,23 / etc)

append 42 to the end of the 'sorted' list. (e.g. 23, 42 / 4,16,8,15

8. At this point in the insertion sort we have two elements in our unsorted list. The four is next - what happens now?
SORTED      |    UNSORTED
--------------------------------------
23   42              4    16   8    15

#What comes next?

We have to move the 42 and the 23 right one place. and put the '4' into the first place in the sorted portion

We insert the '4' after the 42 and before the 16.

We do not need to move the elements in the sorted list to the right before inserting the new element.

We simply insert the '4' before the 42, but after the 23

9. In the following code for an insertion sort, what are the values of the variable 'index' generated by the for loop?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

1 to 8

0 to 9

0 to 8

None of the above

10. In line 4, what is the first 'value' that is being assigned to the variable 'currentvalue'?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

14

1

0

46

11. On line 5, what is the variable 'position'?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

All of the above statements are correct

The position variable, if printed, would the same as 'index'

position is being assigned the value of the 'index number'

position, when printed, would produce 1 to 8

12. On line 7 the while loop needs to find out what the values of 'nlist[position-1)' and 'currentvalue' are. What are they (in the first iteration of the for loop)?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

nlist[position-1] is equal to -1 which does not exist and currentvalue is equal to 1.

nlist[position-1] is equal 1 and currentvalue is equal to 0

nlist[position-1] is equal to nlist[0] which is 14 and currentvalue is equal to the element in index 1 which is 46.

nlist[position-1] is equal to nlist[1] which is 46 and currentvalue is equal to the element in index 1 which is also 46.

13. In the first iteration on line 7, is the while loop condition (while position>0 and nlist[position-1]>currentvalue:) TRUE or FALSE?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

None of the above

The position is greater than 0, but 14 is NOT greater than 46, so the loop does not run and line 11 is executed instead

The position is not greater than 0 so the loop does not run

The position is greater than 0 and 46 is greater than 14, so the loop runs (14 is printed)

14. What is line 9 doing?
def insertionSort(nlist):
for index in range(1,len(nlist)):

currentvalue = nlist[index]
position = index

while position>0 and nlist[position-1]>currentvalue:
nlist[position]=nlist[position-1]
position = position-1

nlist[position]=currentvalue

nlist = [14,46,43,27,57,41,45,21,70]
insertionSort(nlist)
print(nlist)

None of the above

It is decrementing the value of 'position' so that the list is searched from end to beginning

It is adding 1 to each number, e.g. making 14, 15 and 46 is turned into 47

It is incrementing the value of 'position' so that it goes through the list

15. Taking a look at the insertion sort algorithm again, can you fill in the blanks
Sorting is typically done in-place, by iterating up the array,
growing the sorted list behind it. At each array-position,
it checks the value there against the ____________ in the sorted
list (which happens to be next to it, in the previous array-position
checked). If _______, it leaves the element in place and moves to
the next. If smaller, it finds the correct position within the sorted list,
shifts all the larger values up to make a space, and inserts into that
correct position.

largest value / smaller

largest value / larger

smallest value / largest

smallest value / smaller

16. In an insertion sort, the ______________input is an array that is already sorted. In this case insertion sort has a linear running time (i.e., O(n))

worst case

first case

inverse case

best case

17. Analyse the following example on insertion sort and fill in the blanks
The following table shows the steps for sorting the sequence
{3, 7, 4, 9, 5, 2, 6, 1}.

3  7  4  9  5  2  6  1
3* 7  4  9  5  2  6  1
3  7* 4  9  5  2  6  1
3  4* 7  9  5  2  6  1
3  4  7  9* 5  2  6  1
3  4  5* 7  9  2  6  1
2* 3  4  5  7  9  6  1
2  3  4  5  6* 7  9  1
1* 2  3  4  5  6  7  9

In the above example the key that was moved (or left in place
because it was the biggest yet considered) in the previous step
is _______________________________________________

always the last element

always the '3' which is theinsertion sot key

marked with an asterisk.

always the first element

18. The insertion sort is suitable for large data sets as its average and worst case complexity are of ?(n2), where n is the number of items.

TRUE

FALSE

19. This is an alternative algorithm which also performs the insertion sort. Can you fill in the blanks?
Step 1 ? If it is the first element, it is already sorted. return 1;
Step 2 ? Pick next element
Step 3 ? ___________________________________________???
Step 4 ? Shift all the elements in the sorted sub-list that is greater than the
value to be sorted
Step 5 ? Insert the value
Step 6 ? Repeat until list is sorted

Compare with all elements in the sorted sub-list

None of the above

Compare with all the elements in the unsorted sub-list

Shift all the element left before going to the next step

20. The advantages of an insertion sort include the following:

simple implementation

All of the above are valid advantages

efficiency for relatively small data sets (small lists)

It is in-place and stable (does not change the relative order of elements)