# Data Structure and Alogrithm MCQs

- How can we describe an array in the best possible way?
- The worst-case occur in linear search algorithm when ..
- The complexity of the sorting algorithm measures the.. as a function of the number n of items to be sorter.
- The Time complexity of bubble sort algorithm is ..
- Partition and exchange sort is …
- To represent hierarchical relationship between elements, Which data structure is suitable?
- The way in which the data item or items are logically related defines..
- Which of the following can be used as a criterion for classification of data structures used in language processing?
- What is the process of finding the location of a given data element in the data structure called?
- What plays an important role in programming?
- Which of the following is a stable sorting algorithm?
- How do you initialize an array in C?
- Which of the following recursive formula can be used to find the factorial of a number?
- Is following sequence is a fibonacci sequence:0, 1, 1, 2, 3, 5, 8, 13, 21,.
- Before sorting & After sorting location of element is same. This concept is called as
- Perform based criteria of algorithm, which has to do with computing algorithm called as _________.
- Worst case measured by
- Which of the following is non-liner data structure ?
- Which of the following is not the required condition for binary search algorithm?
- Binary Search can be categorized into which of the following?
- What is the time complexity of binary search with iteration?
- The element that is going to be searched in a list is called
- In binary search, we compare the value with the elements in the. position of the array.*
- Which is the fastest searching algorithm?
- The following sequence is a fibonacci sequence: 0, 1, 1, 2, 3, 5, 8, 13, 21,. Which technique can be used to get the nth fibonacci term?
- What is an internal sorting algorithm?
- Which of the following real time examples is based on insertion sort?
- How many passes does an insertion sort algorithm consist of?
- Which of the following sorting algorithms is the fastest for sorting small arrays
- Which of the following sorting algorith ms is the fastest?
- Which of the following is true about merge sort?
- What is the average case time complexity of merge sort? *
- In a stack, if a user tries to remove an element from empty stack it is called
- The given array is arr = {1,2,4,3). Bubble sort is used to sort the array elements.How many iterations will be done to sort the array with improvised version?*
- In computer science, algorithm refers to a special method usable by a computer for the solution to a problem.*

(a) The Array shows a hierarchical structure.

(b) Arrays are immutable.

(c) Container that stores the elements of similar types

(d) The Array is not a data structure

(c) Container that stores the elements of similar types

(a) Item is somewhere in the middle of the array

(b) Item is not in the array at all

(c) Item is the last element in the array

(d) Item is the last element in the array or item is not there

(d) Item is the last element in the array or item is not there

(a) Average time

(b) Running time

(c) Average-case complexity

(d) Case-complexity

(b) Running time

(a) O(n)

(b) o(logn)

(c) O(n2)

(d) O(n logn)

(c) O(n2)

(a) Quick sort

(b) heap heap sort

(c) bubble sort

(d) None

(a) Quick sort

(a) Tree

(b) Graph

(c) Stack

(d) Queue

(a) Tree

(a) storage structure

(b) data structure

(c) data relationship

(d) data operation

(b) data structure

(a) nature of a data structure

(b) purpose of a data structure

(c) lifetime of a data structure

(d) All of the above

(d) All of the above

(a) Deletion

(b) Insertion

(c) Traversing

(d) Searching

(d) Searching

(a) Data

(b) Computer

(c) Frameowrk

(d) None of the Above

(a) Data

(a) Merge Sort

(b) Quick Sort

(c) Heap Sort

(d) Selection Sort

(a) Merge Sort

(a) int int arr[3] = (1,2,3);

(b) int arr(3) = {1,2,3);

(c) int arr[3] = {1,2,3};

(d) int arr(3) = (1,2,3);

(c) int arr[3] = {1,2,3};

(a) fact(n) = n * fact(n)

(b) fact(n) = n * fact(n+1)

(c) fact(n) = n * fact(n-1)

(d) fact(n) = n * fact(1)

(c) fact(n) = n * fact(n-1)

(a) True

(b) False

(a) True

(a) Sort Stability

(b) Sort Selection

(c) Sorting

(d) None of the above

(a) Sort Stability

(a) Space Complexity

(b) Time Complexity

(c) Notations

(d) Subtitles/closed captic

(b) Time Complexity

(a) Big Oh Notation

(b) Omega Notation

(c) Theta Notation

(d) None

(a) Big Oh Notation

(a) Trees

(b) Stack

(c) List

(d) Queue

(a) Trees

(a) The list must be sorted

(b) There should be the direct access to the middle element in any sublist

(c) Divide conquare is used

(d) Search sequentially

(d) Search sequentially

(a) Brute Force technique

(b) Divide and conquer

(c) Greedy algorithm

(d) Dynamic programming

(b) Divide and conquer

(a) O(nlogn)

(b) O(logn)

(c) o(n)

(d) O(n2)

(b) O(logn)

(a) items

(b) key

(c) file

(d) table

(b) key

(a) Left

(b) middle

(c) Right

(d) None

(b) middle

(a) Linear Search

(b) Binary Search

(c) Interpolation

(d) None

(b) Binary Search

(a) Switch case

(b) Recursion

(c) Functions calling

(d) Divide & Conquare

(b) Recursion

(a) Algorithm that uses tape or disk during the sort

(b) Algorithm that uses main memory during the sort

(c) Algorithm that involves swapping

(d) Algorithm that are considered ‘in place’

(a) Algorithm that uses tape or disk during the sort

(a) Arranging a pack of playing cards

(b) Database scenarios and distributes scenarios

(c) Arranging books on a library shelf

(d) Oreal-time systems

(a) Arranging a pack of playing cards

(a) N

(b) N-1

(c) N+1

(d) N2

(b) N-1

(a) Quick sort

(b) Insertion sort

(c) Shell sort

(d) Heap sort

(b) Insertion sort

(a) Bubble Sort

(b) Quick Sort

(c) Merge Sort

(d) Selection Sort

(b) Quick Sort

(a) Merge Sort works better than quick sort if data is accessed from slow sequential memory.

(b) Merge Sort is stable sort by nature

(c) Merge sort outperforms heap sort in most of the practical situations.

(d) All of the ahove

(a) O(n log n)

(b) o(n2)

(c) o(n2 log n)

(d) O(n log n2)

(a) Underflow

(b) Empty collection

(c) Overflow

(d) Garbage Collection

(a) 4

(b) 2

(c) 1

(d) 0

(b) 2

(a) True

(d) False

(a) True

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