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

- (A) O(n)
- (B) O(n
^{2}) - (C) O(nlog
_{2}n) - (D) O(log
_{2}n)

#### 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(n
^{2}) - (B) best case: O(n2), worst case: O(n log(n))
- (C) best case: O(n log(n) ) worst case: O(n
^{2}) - (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(2
^{n}) - (B) O(n
^{2}) - (C) O(n
^{3}) - (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) n
^{2} - (B) n
- (C) n
^{3} - (D) n
^{n}

## Answer:

Question | Q1 | Q2 | Q3 | Q4 | Q5 | Q6 | Q7 | Q8 | Q9 | Q10 |

Answer | A | B | C | C | C | B | C | B | D | B |