Sorting
Question 1 
Merge sort uses
Divide and conquer strategy  
Backtracking approach  
Heuristic search  
Greedy approach 
Question 2 
Consider the following sequence of numbers
92, 37, 52, 12, 11, 25
Use bubble sort to arrange the sequence in ascending order. Give the sequence at the end of each of the first five passes.
Theory Explanation. 
Question 3 
A two dimensional array A[1...n][1...n] of integers is partially sorted if
∀i, j ∈ [1...n−1], A[i][j] < A[i][j+1] and A[i][j] < A[i+1][j]
Fill in the blanks:
(a) The smallest item in the array is at A[i][j] where i=............and j=..............
(b) The smallest item is deleted. Complete the following O(n) procedure to insert item x (which is guaranteed to be smaller than any item in the last row or column) still keeping A partially sorted.
procedure insert (x: integer); var i,j: integer; begin (1) i:=1; j:=1, A[i][j]:=x; (2) while (x > ...... or x > ......) do (3) if A[i+1][j] < A[i][j] ......... then begin (4) A[i][j]:=A[i+1][j]; i:=i+1; (5) end (6) else begin (7) ............ (8) end (9) A[i][j]:= ............. end
Theory Explanation. 
Question 4 
A sorting technique is called stable if
it takes O (nlog n) time  
it maintains the relative order of occurrence of nondistinct elements  
it uses divide and conquer paradigm  
it takes O(n) space 
Question 5 
If one uses straight twoway merge sort algorithm to sort the following elements in ascending order:
20, 47, 15, 8, 9, 4, 40, 30, 12, 17
then the order of these elements after second pass of the algorithm is:
8, 9, 15, 20, 47, 4, 12, 17, 30, 40  
8, 15, 20, 47, 4, 9, 30, 40, 12, 17  
15, 20, 47, 4, 8, 9, 12, 30, 40, 17  
4, 8, 9, 15, 20, 47, 12, 17, 30, 40 
Question 6 
Let s be a sorted array of n integers. Let t(n) denote the time taken for the most efficient algorithm to determined if there are two elements with sum less than 1000 in s. Which of the following statements is true?
t(n) is O(1)  
n ≤ t(n) ≤ n log_{2} n  
n log_{2} n ≤ t(n) < (n/2)  
t(n) = (n/2) 
Question 7 
Randomized quicksort is an extension of quicksort where the pivot is chosen randomly. What is the worst case complexity of sorting n numbers using randomized quicksort?
O(n)  
O(n log n)  
O(n^{2})  
O(n!) 
Question 8 
In a permutation a_{1}...a_{n} of n distinct integers, an inversion is a pair (a_{i}, a_{j}) such that i < j and a_{i} > a_{j}.
If all permutations are equally likely, what is the expected number of inversions in a randomly chosen permutation of 1...n ?
n(n1)/2  
n(n1)/4  
n(n+1)/4  
2n[log_{2}n] 
Question 9 
In a permutation a_{1}...a_{n} of n distinct integers, an inversion is a pair (a_{i}, a_{j}) such that i
What would be the worst case time complexity of the Insertion Sort algorithm, if the inputs are restricted to permutations of 1...n with at most n inversions?
Θ(n^{2})  
Θ(n log n)  
Θ(n^{1.5})  
Θ(n) 
Question 10 
Consider the recursive algorithm given below:
procedure bubblersort (n); var i,j: index; temp : item; begin for i:=1 to n1 do if A[i] > A [i+1] then begin temp : A[i]; A[i]:=A[i+1]; A[i+1]:=temp end; bubblesort (n1) end
Let a_{n} be the number of times the ‘if…then….’ Statement gets executed when the algorithm is run with value n. Set up the recurrence relation by defining a_{n} in terms of a_{n1}. Solve for a_{n}.
Theory Explanation. 
Question 11 
Following algorithm(s) can be used to sort n integers in the range [1...n^{3}] in O(n) time
Heapsort  
Quicksort  
Mergesort  
Radixsort 
As Radix sort is not comparison based sort (it is counting sort), so can be done in linear time.
Question 12 
The minimum number of comparisons required to sort 5 elements is _____
7 
= ⌈log(n!)⌉
= ⌈log(5!)⌉
= ⌈log(120)⌉
= 7
Question 13 
Let a and b be two sorted arrays containing n integers each, in nondecreasing order. Let c be a sorted array containing 2n integers obtained by merging the two arrays a and b. Assuming the arrays are indexed starting from 0, consider the following four statements
1. a[i] ≥ b [i] => c[2i] ≥ a [i] 2. a[i] ≥ b [i] => c[2i] ≥ b [i] 3. a[i] ≥ b [i] => c[2i] ≤ a [i] 4. a[i] ≥ b [i] => c[2i] ≤ b [i]Which of the following is TRUE?
only I and II  
only I and IV  
only II and III  
only III and IV 
Since both 'a' and 'b' are sorted in the beginning, there are 'i' elements than or equal to a[i] and similarly 'i' elements smaller than or equal to b[i]. So, a[i] ≥ b[i] means there are 2i elements smaller than or equal to a[i] and hence in the merged array, a[i] will come after these 2i elements. So, c[2i] ≤ a[i].
Similarly, a[i] ≥ b[i] says for b that, there are not more than 2i elements smaller than b[i] in the sorted array. So, b[i] ≤ c[2i].
So, option (C) is correct.
Question 14 
If we use Radix Sort to sort n integers in the range [n^{k/2}, n^{k}], for some k>0 which is independent of n, the time taken would be?
Θ(n)  
Θ(kn)  
Θ(nlogn)  
Θ(n^{2}) 
where n = keys, w = word size
w = log_{2} (n^{k}) = k × log_{2} (n)
Complexity Θ(wn) = Θ(k × log_{2}(n) × n) = Θ(n log n) = Θ(n log n)
Question 15 
Let P be a quicksort program to sort numbers in ascending order. Let t_{1} and t_{2} be the time taken by the program for the inputs [1 2 3 4] and [5 4 3 2 1] respectively. Which of the following holds?
t_{1} = t_{2}  
t_{1} > t_{2}  
t_{1} < t_{2}  
t_{1} = t_{2} + 5 log 5 
Question 16 
Quicksort is ________ efficient than heapsort in the worst case.
LESS. 
Question 17 
You have an array of n elements. Suppose you implement quicksort by always choosing the central element of the array as the pivot. Then the tightest upper bound for the worst case performance is
O(n^{2})  
O(n log n)  
Θ(n logn)  
O(n^{3}) 
Question 18 
I. Quicksort runs in Θ(n^{2}) time
II. Bubblesort runs in Θ(n^{2}) time
III. Mergesort runs in Θ(n) time
IV. Insertion sort runs in Θ(n) time
I and II only  
I and III only  
II and IV only  
I and IV only 
→ The recurrence relation for Quicksort, if elements are already sorted,
T(n) = T(n1)+O(n) with the help of substitution method it will take O(n^{2}).
→ The recurrence relation for Merge sort, is elements are already sorted,
T(n) = 2T(n/2) + O(n) with the help of substitution method it will take O(nlogn).
We can also use master's theorem [a=2, b=2, k=1, p=0] for above recurrence.
Question 19 
The worst case running times of Insertion sort, Merge sort and Quick sort, respectively, are:
Θ(nlogn), Θ(nlogn), and Θ(n^{2})  
Θ(n^{2} ), Θ(n^{2} ), and Θ(nlogn)  
Θ(n^{2}), Θ(nlogn), and Θ(nlogn)  
Θ(n^{2}), Θ(nlogn), and Θ(n^{2}) 
Question 20 
An array of 25 distinct elements is to be sorted using quicksort. Assume that the pivot element is chosen uniformly at random. The probability that the pivot element gets placed in the worst possible location in the first round of partitioning (rounded off to 2 decimal places) is _____.
0.08  
0.01  
1  
8 
Step2: Pivot element = uniformly random.
Step3: Worst case position in the pivot element is either first (or) last.
Step4: So total 2 possibilities among 25 distinct elements
= 2/25
= 0.08
Question 21 
There are n unsorted arrays: A_{1}, A_{2}, ..., A_{n}. Assume that n is odd. Each of A_{1}, A_{2}, ..., A_{n} contains n distinct elements. There are no common elements between any two arrays. The worstcase time complexity of computing the median of the medians of A_{1}, A_{2}, ..., A_{n} is
O(n)  
O(n log n)  
Ω(n^{2} log n)  
O(n^{2}) 
But it is similar to quicksort but in quicksort, partitioning will take extra time.
→ Find the median will be (i+j)/2
1. If n is odd, the value is Ceil((i+j)/2)
2. If n is even, the value is floor((i+j)/2)
> Here, total number of arrays are
⇒ O(n)*O(n)
⇒ O(n^{2})
Note:
They are clearly saying that all are distinct elements.
There is no common elements between any two arrays.
Question 22 
Consider the Quicksort algorithm. Suppose there is a procedure for finding a pivot element which splits the list into two sublists each of which contains at least onefifth of the elements. Let T(n) be the number of comparisons required to sort n elements. Then
T(n) ≤ 2T(n/5) + n
 
T(n) ≤ T(n/5) + T(4n/5) + n  
T(n) ≤ 2T(4n/5) + n  
T(n) ≤ 2T(n/2) + n

So, T(n/5) comparisons are needed for the first subset and T(4n/5) comparisons needed for second subset.
Now, suppose that one subset contains more than n/5 elements then another subset will contain less than 4n/5 elements. Due to which time complexity will be less than
T(n/5) + T(4n/5) + n
Because recursion tree will be more balanced.
Question 23 
Which one of the following in place sorting algorithms needs the minimum number of swaps?
Quick sort  
Insertion sort  
Selection sort  
Heap sort 
Question 24 
What is the number of swaps required to sort n elements using selection sort, in the worst case?
θ(n)  
θ(n log n)  
θ(n^{2})  
θ(n^{2} logn) 
Question 25 
In quick sort, for sorting n elements, the (n/4)^{th} smallest element is selected as pivot using an O(n) time algorithm. What is the worst case time complexity of the quick sort?
θ(n)  
θ(n log n)  
θ(n^{2})  
θ(n^{2} log n) 
n→n/(4/3)→n/(4/3)^{2}→n/(4/3)^{3}n/(4/3)^{k}=1
n/(4/3)^{k} = 1
⇒n=(4/3)^{k} ⇒ k = log_{4/3}n [k=no. of levels]
In each level workdone = Cn
So, total workdone = Cn⋅log_{4/3}n = (nlog_{4/3}n)
Question 26 
Which one of the following is the tightest upper bound that represents the number of swaps required to sort n numbers using selection sort?
O(log n)  
O(n)  
O(n log n)  
O(n^{2}) 
Selection sort time complexity O(n^{2}) in terms of number of comparisons. Each of these scans requires one swap for n1 elements (the final element is already in place).
Question 27 
The number of elements that can be sorted in Θ(log n) time using heap sort is
Θ(1)  
Θ(√logn)  
Θ (logn/loglogn)  
Θ(log n) 
So, Θ((logn/ log log n)log(logn/log log n))
= Θ(logn/log logn (log logn  log log logn))
= Θ((log n/log logn) × log log n)
= Θ(log n)
Hence, option (C) is correct answer.
Question 28 
function mystery (A[0..99]) {
int i,j,m;
for (i = 0; i < 100; i++) {
m = i;
for (j = i; j < 100, j++) {
if (A[j] > A[m]) {
m = j;
}
}
reverse(A,i,m);
}
return;
}
When the procedure terminates, the array A has been:
Sorted in descending order  
Sorted in ascending order  
Reversed  
Left unaltered 
Question 29 
Heap Sort  
Quick Sort  
Insertion Sort  
None of the above 
Example of external sorting is merge sort.
Question 30 
Question 31 
Dynamic programming  
Back tracking  
Divide and conquer  
Greedy method 
Question 32 
Quick Sort  
Heap Sort  
Merge sort  
All the above 
Question 33 
Bubble Sort  
Quick Sort  
Merge Sort  
Heap Sort 
Question 34 
Quick sort is run on two inputs shown below to sort in ascending order:
I : 1,2,3,…n II : n, n1,…, 2, 1
Let k1 and k2 be the number of comparisons made for the inputs I and II respectively. Then
k1 < k2  
k1 = k2  
k1 > k2  
None 
Question 35 
Ω(n)  
Ω(n/k)  
Ω(nlogk )  
Ω(n/klogn/k) 
(k!)^{n/k} ≤ 2^{h}
Taking the logarithm of both sides, we get:
h ≥ lg(k!)^{n/k}
= (n/k)lg(k!)
≥ (n/k)(k/2)lg(k/2)
= (1/2)*(nlogk)(1/2)*n
= Ω(nlogk)
Question 36 
Insertion sort  
Quick sort  
Merge sort  
Selection sort 