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

Answer:

Question	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10
Answer	A	B	C	C	C	B	C	B	D	B