Data Structures Algorithms Mock Test

This section presents you various set of Mock Tests related to Data Structures Algorithms. You can download these sample mock tests at your local machine and solve offline at your convenience. Every mock test is supplied with a mock test key to let you verify the final score and grade yourself.

Data Structures Algorithms Mock Test IV

Explanation

Recursion uses stack but the main reason is, every recursive call needs to be stored separately in the memory.

Explanation

Heap maintains itself to meet all the requirements of complete binary tree.

Explanation

In a min heap, parent nodes store lesser values than child nodes. The minimum value of the entire heap is stored at root.

Explanation

Regardless of being min heap or max heap, root is always replaced by last element of the last level.

Explanation

All possible spanning trees of graph G, have same number of edges and vertices.

Q 6 - From a complete graph, by removing maximum _______________ edges, we can construct a spanning tree.

A - `e-n+1`

B - `n-e+1`

C - `n+e-1`

D - `e-n-1`

Explanation

We can remove maximum `e-n+1` edges to get a spanning tree from complete graph. Any more deletion of edges will lead the graph to be disconnected.

Q 7 - If we choose Prim's Algorithm for uniquely weighted spanning tree instead of Kruskal's Algorithm, then

A - we'll get a different spanning tree.

B - we'll get the same spanning tree.

C - spanning will have less edges.

D - spanning will not cover all vertices.

Explanation

Regardless of which algorithm is used, in a graph with unique weight, resulting spanning tree will be same.

Q 8 - Re-balancing of AVL tree costs

A - Ο(1)

B - Ο(log n)

C - Ο(n)

D - Ο(n2)

Explanation

AVL rotations have complexity of Ο(log n)

Explanation

The balance factor (BalanceFactor = height(left-sutree) − height(right-sutree)) is used to check if the tree is balanced or unbalanced.

Explanation

BST does not care about complete binary tree properties.

Q 11 - The following sorting algorithms maintain two sub-lists, one sorted and one to be sorted −

A - Selection Sort

B - Insertion Sort

C - Merge Sort

D - both A &am; B

Explanation

Both selection sort and insertion sort maintains two sublists and then checks unsorted list for next sorted element.

Q 12 - If locality is a concern, you can use _______ to traverse the graph.

B - Depth First Search

C - Either BFS or DFS

D - None of the above!

Explanation

DFS is a better choice when locality-wise items are concerned.

Q 13 - Access time of a binary search tree may go worse in terms of time complexity upto

A - Ο(n2)

B - Ο(n log n)

C - Ο(n)

D - Ο(1)

Explanation

At maximum, BST may need to search all n values in the tree in order to access an element, hence, Ο(n).

Explanation

Shell sort uses insertion sort when interval value is 1.

Q 15 - A pivot element to partition unsorted list is used in

A - Merge Sort

B - Quick Sort

C - Insertion Sort

D - Selection Sort

Explanation

The quick sort partitions an array using pivot element and then calls itself recursively twice to sort the resulting two subarray.

Explanation

A stable sorting algorithm like bubble sort, does not change the sequence of appearance of similar element in the sorted list.

Explanation

A sorting algorithm is said to be adaptive, if it takes advantage of already 'sorted' elements in the list that is to be sorted.

Explanation

For this algorithm to work properly the data collection should be in sorted form and equally distributed.

Q 19 - If the data collection is in sorted form and equally distributed then the run time complexity of interpolation search is −

A - Ο(n)

B - Ο(1)

C - Ο(log n)

D - Ο(log (log n))

Explanation

Runtime complexity of interpolation search algorithm is Ο(log (log n)) as compared to Ο(log n) of BST in favourable situations.

Q 20 - Which of the following algorithm does not divide the list −

A - linear search

B - binary search

C - merge sort

D - quick sort

Explanation

Linear search, seaches the desired element in the target list in a sequential manner, without breaking it in any way.

Q 21 - The worst case complexity of binary search matches with −

A - interpolation search

B - linear search

C - merge sort

D - none of the above

Explanation

In the worst case a binary search needs to access all elements of the target list, same as linear search.

Explanation

Efficiency of algorithm is measured by assuming that all other factors e.g. processor speed, are constant and have no effect on implementation.

Explanation

In this analysis, actual statistics like running time and space required, are collected.

Explanation

Project scheduling is an exmaple of dynamic programming.

Q 25 - In conversion from prefix to postfix using stack data-structure, if operators and operands are pushed and popped exactly once, then the run-time complexity is −

A - Ο(1)

B - Ο(n)

C - Ο(log n)

D - Ο(n2)

Explanation

Infix to postfix conversion using stack will have run time complexity of Ο(n).

1 B
2 A
3 C
4 D
5 A
6 A
7 B
8 B
9 D
10 A
11 D
12 B
13 C
14 A
15 B
16 C
17 B
18 A
19 D
20 A
21 B
22 B
23 B
24 B
25 B