This section contains more frequently asked Data Structure Basics Multiple Choice Questions Answers in the various University level and competitive examinations.

PRACTICE IT NOW TO SHARPEN YOUR CONCEPT AND KNOWLEDGE

view hide answers

1. For the bubble sort algorithm, what is the time complexity of the best/worst case? (assume that the computation stops as soon as no more swaps in one pass)

  • best case: O(n) worst case: O(n*n)
  • best case: O(n) worst case: O(n*log(n))
  • best case: O(n*log(n)) worst case: O(n*log(n))
  • best case: O(n*log(n)) worst case: O(n*n)

2. For the quick sort algorithm, what is the time complexity of the best/worst case?

  • best case: O(n) worst case: O(n*n)
  • best case: O(n) worst case: O(n*log(n))
  • best case: O(n*log(n)) worst case: O(n*log(n))
  • best case: O(n*log(n)) worst case: O(n*n)

3. In an arbitrary tree ( not a search tree) of order M. Its size is N, and its height is K. The computation time needed to find a data item on T is

  • O(K*K)
  • O(M*M)
  • O(N)
  • O(K)

4. Which of the following belongs to the algorithm paradigm?

  • Minimum & Maximum problem
  • Knapsack problem
  • Selection problem
  • Merge sort
  • Quick sort.

5. If f,t: N→ R+, then t (n)  Ω (f (n)), iff f(n)  O (t (n)) is known as

  • Limit rule
  • Rule of inference
  • Duality rule
  • Rule of consequences

6. The time taken by NP-class sorting algorithm is

  • O(1)
  • O(log n)
  • O(n2)
  • O(n)

7. Find the odd one out from the following categories of algorithms.

  • TVSP
  • N-Queens
  • 15-Puzzle
  • Bin-Packing.

8. The time complexity of binary search in best, worst cases for an array of size N is

  • N, N2
  • 1, Log N
  • Log N, N2
  • 1, N log N

9. Which of following algorithm scans the list by swapping the entries whenever pair of adjacent keys are out of desired order?

  • Insertion sort
  • Quick sort
  • Shell sort
  • Bubble sort

10. The mathematical definition for Omega can be defined as, provided f,g:NR+ and c is a positive constant and n > n0,

  • f(n) ≥ c. g(n) n
  • f(n) = c. g(n) n
  • f(n) ≥ c + g(n) n
  • f(n) = c + g(n) n
Share with : Share on Linkedin Share on Twitter Share on WhatsApp Share on Facebook