Algorithm: MCQ Set – 01

Q1: What is the time complexity of insertion sort in best case?

  • (A) O(n)
  • (B) O(n2)
  • (C) O(nlog2n)
  • (D) O(log2n)

Q2: The time factor when determining the efficiency of algorithm is measured by

  • (A) Counting microseconds
  • (B) Counting the number of key operations
  • (C) Counting the number of statements
  • (D) Counting the kilobytes of algorithm

Q3: Which of the following algorithm design technique is used in the quick sort algorithm?

  • (A) Dynamic programming
  • (B) Backtracking
  • (C) Divide and conquer
  • (D) Greedy method

Q4: For the Quick sort algorithm, what is the time complexity of the best/worst case?

  • (A) best case: O(log(n)) worst case: O(n2)
  • (B) best case: O(n2), worst case: O(n log(n))
  • (C) best case: O(n log(n) ) worst case: O(n2)
  • (D) best case: O(n2), worst case: O(n2log(n) )

Q5: Binary Search Method has Worst Case Time Complexity of

  • (A) 2n
  • (B) nlog(n)
  • (C) log(n)
  • (D) n*n

Q6: The average case complexity of Insertion Sort is

  • (A) O(2n)
  • (B) O(n2)
  • (C) O(n3)
  • (D) O(2n)

Q7: An hash table with chaining as a collision resolution technique degenerates to a

  • (A) Stack
  • (B) Queue
  • (C) Linked List
  • (D) Tree

Q8: Assume the input array is nearly sorted. Then performance of Quick sort is

  • (A) Better than Average case
  • (B) Worst than Average case
  • (C) Same as in Average case
  • (D) None of these

Q9: A technique for direct search is

  • (A) Binary Search
  • (B) Linear Search
  • (C) Tree Search
  • (D) Hashing

Q10: The running time T(n) is given as

T(n) = c + T(n-1) , if  n >1

        = d , if  n<=1

The order of the algorithm is

  • (A) n2
  • (B) n
  • (C) n3
  • (D) nn



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