CS502 1st Quiz Spring 2013 File 2

No Comments

For the heap sort we store the tree nodes in
 Select correct option:

 level-order traversal
 in-order traversal
 pre-order traversal
 post-order traversal





One of the clever aspects of heaps is that they can be stored in arrays without using any _______________.
 Select correct option:
 pointers
 constants
 variables
 functions



A (an) _________ is a left-complete binary tree that conforms to the heap order
 Select correct option:
 heap
 binary tree
 binary search tree
 array



Divide-and-conquer as breaking the problem into a small number of
 Select correct option:
 pivot
 Sieve
 smaller sub problems
 Selection


 Heaps can be stored in arrays without using any pointers; this is due to the ____________ nature of the binary tree,
 Select correct option:
 left-complete
 right-complete
 tree nodes
 tree leaves

 For the sieve technique we solve the problem,
 Select correct option:
 recursively
 mathematically
 precisely
 accurately

 A heap is a left-complete binary tree that conforms to the ___________
 Select correct option:
 increasing order only
 decreasing order only
 heap order
 (log n) order


 We do sorting to,
 Select correct option:
 keep elements in random positions
 keep the algorithm run in linear order
 keep the algorithm run in (log n) order
 keep elements in increasing or decreasing order


 How many elements do we eliminate in each time for the Analysis of Selection algorithm?
 Select correct option:
 n / 2 elements
 (n / 2) + n elements
 n / 4 elements
 2 n elements


 How much time merge sort takes for an array of numbers?
 Select correct option:
 T(n^2)
 T(n)
 T( log n)
 T(n log n)


 The reason for introducing Sieve Technique algorithm is that it illustrates a very important special case of,
 Select correct option:
 divide-and-conquer
 decrease and conquer
 greedy nature
 2-dimension Maxima



Question # 1 of 10 ( Start time: 08:17:23 AM ) Total M a r k s: 1
 The number of nodes in a complete binary tree of height h is
 Select correct option:
 2^(h+1) – 1
 2 * (h+1) – 1
 2 * (h+1)
 ((h+1) ^ 2) – 1

Question # 2 of 10 ( Start time: 08:18:46 AM ) Total M a r k s: 1
 A (an) _________ is a left-complete binary tree that conforms to the heap order
 Select correct option:
 heap
 binary tree
 binary search tree
 array

 Question # 3 of 10 ( Start time: 08:19:38 AM ) Total M a r k s: 1
 In Sieve Technique we do not know which item is of interest
 Select correct option:
 True
 False

 Question # 4 of 10 ( Start time: 08:20:33 AM ) Total M a r k s: 1
 Heaps can be stored in arrays without using any pointers; this is due to the
 ____________ nature of the binary tree,
 Select correct option:
 left-complete
 right-complete
 tree nodes
 tree leaves

 Question # 5 of 10 ( Start time: 08:21:59 AM ) Total M a r k s: 1
 In the analysis of Selection algorithm, we make a number of passes, in fact it could be as
 many as,
 Select correct option:
 T(n)
 T(n / 2)
 log n
 n / 2 + n / 4

 Question # 6 of 10 ( Start time: 08:23:01 AM ) Total M a r k s: 1
 For the sieve technique we solve the problem,
 Select correct option:
 recursively
 mathematically
 precisely
 accurately
 Theta asymptotic notation for T (n) :
 Select correct option:
 Set of functions described by: c1g(n)Set of functions described by c1g(n)>=f(n) for c1 s
 Theta for T(n)is actually upper and worst case comp
 Set of functions described by:
 c1g(n)


 Question # 8 of 10 ( Start time: 08:24:39 AM ) Total M a r k s: 1
 The sieve technique is a special case, where the number of sub problems is just
 Select correct option:
 5
 many
 1
 few

Question # 9 of 10 ( Start time: 08:25:54 AM ) Total M a r k s: 1
 Sieve Technique applies to problems where we are interested in finding a single item from a larger set of _____________
 Select correct option:
 n items
 phases
 pointers
 constant

 Question # 10 of 10 ( Start time: 08:26:44 AM ) Total M a r k s: 1
 The sieve technique works in ___________ as follows
 Select correct option:
 phases
 numbers
 integers
 routines



Memorization is?

To store previous results for future use

To avoid this unnecessary repetitions by writing down the results of recursive calls and looking them up again if we need them later

To make the process accurate

None of the above



Question # 2 of 10 Total M a r k s: 1

Which sorting algorithm is faster

O (n log n)

O n^2

O (n+k)

O n^3



Quick sort is

Stable & in place

Not stable but in place

Stable but not in place

Some time stable & some times in place



One example of in place but not stable algorithm is

Merger Sort

Quick Sort

Continuation Sort

Bubble Sort



In Quick Sort Constants hidden in T(n log n) are

Large

Medium

Small

Not Known



Continuation sort is suitable to sort the elements in range 1 to k

K is Large

K is not known

K may be small or large

K is small



In stable sorting algorithm.

If duplicate elements remain in the same relative position after sorting

One array is used

More than one arrays are required

Duplicating elements not handled



Which may be a stable sort?

Merger

Insertion

 Both above

None of the above



An in place sorting algorithm is one that uses ___ arrays for storage

Two dimensional arrays

More than one array

No Additional Array

None of the above



Continuing sort has time complexity of ?

O(n)

O(n+k)

O(nlogn)

O(k)



We do sorting to,

keep elements in random positions

keep the algorithm run in linear order

keep the algorithm run in (log n) order

keep elements in increasing or decreasing order





In Sieve Technique we donot know which item is of interest



True

False

A (an) _________ is a left-complete binary tree that conforms to the

heap order

heap

binary tree

binary search tree

array

27. The sieve technique works in ___________ as follows

phases

numbers

integers

routines



For the sieve technique we solve the problem,

recursively

mathematically

precisely

accurately

29. For the heap sort, access to nodes involves simple _______________

operations.

arithmetic

binary

algebraic

logarithmic







The analysis of Selection algorithm shows the total running time is

indeed ________in n,\

arithmetic

geometric

linear

orthogonal



For the heap sort, access to nodes involves simple _______________

operations.

Select correct option:

arithmetic

binary

algebraic

logarithmic



Sieve Technique applies to problems where we are interested in finding a

single item from a larger set of _____________

Select correct option:

n items

phases

pointers

constant



Question # 9 of 10 ( Start time: 07:45:36 AM ) Total Marks: 1

In Sieve Technique we do not know which item is of interest

Select correct option:

True

False



How much time merge sort takes for an array of numbers?

Select correct option:

T(n^2)

T(n)

T( log n)

T(n log n)



For the heap sort we store the tree nodes in

Select correct option:

level-order traversal

in-order traversal

pre-order traversal

post-order traversal





Sorting is one of the few problems where provable ________ bonds exits on

how fast we can sort,

Select correct option:

upper

lower

average

log n



single item from a larger set of _____________

Select correct option:

n items

phases

pointers

constant



A heap is a left-complete binary tree that conforms to the ___________

Select correct option:

increasing order only

decreasing order only

heap order

(log n) order



In the analysis of Selection algorithm, we make a number of passes, in fact it could be as many as,

Select correct option:

T(n)

T(n / 2)

log n

n / 2 + n / 4



The reason for introducing Sieve Technique algorithm is that it illustrates a

very important special case of,

Select correct option:

divide-and-conquer

decrease and conquer

greedy nature

2-dimension Maxima



The sieve technique works in ___________ as follows

Select correct option:

phases

numbers

integers

routines

For the Sieve Technique we take time

Select correct option:

T(nk)

T(n / 3)

n^2

n/3



In the analysis of Selection algorithm, we eliminate a constant fraction of the

array with each phase; we get the convergent _______________ series in the

analysis,

linear

arithmetic

geometric

exponent



Analysis of Selection algorithm ends up with,

Select correct option:

T(n)

T(1 / 1 + n)

T(n / 2)

T((n / 2) + n)



Quiz Start Time: 07:23 PM
 Time Left 90
 sec(s)
 Question # 1 of 10 ( Start time: 07:24:03 PM ) Total M a r k s: 1
 In in-place sorting algorithm is one that uses arrays for storage :
 Select correct option:
 An additional array
 No additional array
 Both of above may be true according to algorithm
 More than 3 arrays of one dimension.



 Time Left 89
 sec(s)
 Question # 2 of 10 ( Start time: 07:25:20 PM ) Total M a r k s: 1
 Which sorting algorithn is faster :
 Select correct option:
 O(n^2)
 O(nlogn)
 O(n+k)
 O(n^3)

In stable sorting algorithm:
 Select correct option:
 One array is used
 In which duplicating elements are not handled.
 More then one arrays are required.
 Duplicating elements remain in same relative posistion after sorting.


 Counting sort has time complexity:
 Select correct option:
 O(n)
 O(n+k)
 O(k)
 O(nlogn)




 Counting sort is suitable to sort the elements in range 1 to k:
 Select correct option:
 K is large
 K is small
 K may be large or small
 None




 Memorization is :
 Select correct option:
 To store previous results for further use.
 To avoid unnecessary repetitions by writing down the results of recursive calls and looking them again if needed later
 To make the process accurate.
 None of the above



The running time of quick sort depends heavily on the selection of
 Select correct option:
 No of inputs
 Arrangement of elements in array
 Size o elements
 Pivot elements

 Which may be stable sort:
 Select correct option:
 Bubble sort
 Insertion sort
 Both of above


 In Quick sort algorithm, constants hidden in T(n lg n) are
 Select correct option:
 Large
 Medium
 Not known
 small



Quick sort is
 Select correct option:
 Stable and In place
 Not stable but in place
 Stable and not in place
 Some time in place and send some time stable





For the Sieve Technique we take time

T(nk)

T(n / 3)

n^2

n/3



The sieve technique is a special case, where the number of sub problems is just

Select correct option:

5

Many

1

Few



The reason for introducing Sieve Technique algorithm is that it illustrates a very important special case of,

Select correct option:

divide-and-conquer

decrease and conquer

greedy nature

2-dimension Maxima











Quick sort is

Select correct option:

Stable and In place

Not stable but in place

Stable and not in place

Some time in place and send some time stable



Memoization is :

Select correct option:

To store previous results for further use.

To avoid unnecessary repetitions by writing down the results of

recursive calls and looking them again if needed later

To make the process accurate.

None of the above



One Example of in place but not stable sort is

Quick
Heap
Merge
Bubble



The running time of quick sort depends heavily on the selection of

No of inputs
Arrangement of elements in array
Size o elements
Pivot elements



Question # 9
In Quick sort algorithm,constants hidden in T(n lg n) are

Large
Medium
Not known
Small
Next PostNewer Post Previous PostOlder Post Home

0 comments

Post a Comment