Algorithms Design And Analysis MCQS with Answers
Algorithms Design And Analysis MCQS with Answers is mainly intended fro GATE aspirants.These questions can also came in Btech Computer science university exams and various interview for computer science students
(31) T (n) = 1 for n=1
= 2 * T (n - 1) for n >1 then T (n) =
(32) T (n) = 4T (n/2) + n2√n then T (n) =
(A) ϴ (n3 √n) (B) ϴ (n2) (C) ϴ (n2√n) (D) ϴ (n√n)
(33) T (n) = 2T (n/2) + (n/ log n) then T (n) =
(A) ϴ (n log n) (B) ϴ (n log n log n)
(C) ϴ (n2 log n log n) (D) ϴ (n2 log n)
(34) T (n) = T (n/2) + T (n/4) + T (n/8) + n then T (n) =
(A) ϴ (n4) (B) ϴ (n3) (C) ϴ (n2) (D) ϴ (n)
(35) Set defines as
(A) Distinct objects (B) Similar elements (C) collection of elements (D) objects
(36) A machine took 200 sec to sort 200 names, using bubble sort. In 800 sec, it can approximately sort
(A) 400 names (B) 800 names (C) 750 names (D) 1800 names
(37) Linked lists are not suitable for
(A) Insertion sort (B) Binary search (C) Radix sort (D) Polynomial manipulation
(38) Which of the following is useful in implementing quick sort?
(A) Stack (B) List (B) Set (D) Queue
(39) A machine needs a minimum of 100 sec to sort 1000 names by quick sort. The minimum time needed to sort 1000 names by quick sort. The minimum time needed to sort 100 names will be approximately?
(A) 50.2 sec (B) 6.7 sec (C) 72.7 sec (D) 11.2 sec
(40) Given 2 sorted lists of size ‘m’ and ‘n’ respectively. Number of comparisons needed in the worst case by the merge sort algorithm will be
(A) mn (B) max(m,n) (C) min(m,n) (D) m+n-1
(41) The depth of a complete binary tree with ‘n’ nodes is
(A) log (n+1)-1 (B) log n (C) log (n-1)+ 1 (D) log n +1
(42) Average successful search time taken by binary search on a sorted array of items is
(A) 2.6 (B) 2.7 (C) 2.8 (D) 2.9
(43) Average successful search time for sequential search on ‘n’ items is
(A) n/2 (B) (n-1)/2 (C) (n+1)/2 (D) n2
(44) The maximum number of comparisons needed to sort 7 items using radix sort is (assume each item is a 4 digit decimal number)
(A) 280 (B) 40 (C) 47 (D) 38
(45) In Randomized Quick sort, the expected running time of any input is
(A) O(n) (B) O(n2) (C) O(n log n ) (D) O(n3)
= 2 * T (n - 1) for n >1 then T (n) =
(A) 2 n (B) 2 n-1 (C) 2 n-2 (D) 2 n-3
(32) T (n) = 4T (n/2) + n2√n then T (n) =
(A) ϴ (n3 √n) (B) ϴ (n2) (C) ϴ (n2√n) (D) ϴ (n√n)
(33) T (n) = 2T (n/2) + (n/ log n) then T (n) =
(A) ϴ (n log n) (B) ϴ (n log n log n)
(C) ϴ (n2 log n log n) (D) ϴ (n2 log n)
(34) T (n) = T (n/2) + T (n/4) + T (n/8) + n then T (n) =
(A) ϴ (n4) (B) ϴ (n3) (C) ϴ (n2) (D) ϴ (n)
(35) Set defines as
(A) Distinct objects (B) Similar elements (C) collection of elements (D) objects
(36) A machine took 200 sec to sort 200 names, using bubble sort. In 800 sec, it can approximately sort
(A) 400 names (B) 800 names (C) 750 names (D) 1800 names
(37) Linked lists are not suitable for
(A) Insertion sort (B) Binary search (C) Radix sort (D) Polynomial manipulation
(38) Which of the following is useful in implementing quick sort?
(A) Stack (B) List (B) Set (D) Queue
(39) A machine needs a minimum of 100 sec to sort 1000 names by quick sort. The minimum time needed to sort 1000 names by quick sort. The minimum time needed to sort 100 names will be approximately?
(A) 50.2 sec (B) 6.7 sec (C) 72.7 sec (D) 11.2 sec
(40) Given 2 sorted lists of size ‘m’ and ‘n’ respectively. Number of comparisons needed in the worst case by the merge sort algorithm will be
(A) mn (B) max(m,n) (C) min(m,n) (D) m+n-1
(41) The depth of a complete binary tree with ‘n’ nodes is
(A) log (n+1)-1 (B) log n (C) log (n-1)+ 1 (D) log n +1
(42) Average successful search time taken by binary search on a sorted array of items is
(A) 2.6 (B) 2.7 (C) 2.8 (D) 2.9
(43) Average successful search time for sequential search on ‘n’ items is
(A) n/2 (B) (n-1)/2 (C) (n+1)/2 (D) n2
(44) The maximum number of comparisons needed to sort 7 items using radix sort is (assume each item is a 4 digit decimal number)
(A) 280 (B) 40 (C) 47 (D) 38
(45) In Randomized Quick sort, the expected running time of any input is
(A) O(n) (B) O(n2) (C) O(n log n ) (D) O(n3)
Algorithms Design And Analysis MCQS with Answers
| 31 | B |
| 32 | C |
| 33 | B |
| 34 | D |
| 35 | A |
| 36 | A |
| 37 | B |
| 38 | A |
| 39 | B |
| 40 | D |
| 41 | A |
| 42 | D |
| 43 | C |
| 44 | A |
| 45 | C |
