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Sr No Question Option A whether correct ?
1
n a gor m s ma e up o mo u es an .
order of M1 is f(n) and M2 is g(n) then the order of the
algorithm is
max (f (n) ,g
(n))100
2
There are 4 different algorithms AI, A2, A3, A4 to solve
a given problem with the order Iog(n), log(log(n)),nIog(n) ,n / log(n) respectively. Which is the best
algorithm? A1
0
3The time required to search an element in a linked list
of length n is . O(log2 n)0
4
.
f(n) = n3, if 0n < 10,000
n2, otherwise f(n) is O(n3)0
5 What is the worst-case time for serial search finding a
single item in an array? Constant time
0
6 ere ex s s wo unc ons n an g n e cons anc>0 and there exists an integer constant n0>=1 If f(n) f(n)= O(g(n)) 100
7ere ex s s wo unc ons n an g n e cons an
c>0 and there exists an integer constant n0>=1 If f(n) f(n)= O(g(n)) 0
8
oose e correc comp ex y or o ow ng co e
while(n>0)
{
n=n/10
} O(1) 09 (n-1)*(n-5) is expressed in terms of big oh O(1) 0
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Option B whether correct ? Option C whether correct ?
min (f (n) ,g (n)
)0
f (n) + g (n)0
A2
100
A3
0
O(n)100
O(1)0
. g(n) is O(n20
same as
O(g(n))0
Logarithmic
time
0
Linear time
100
f(n)=(g(n)) 0 f (n) =(g(n)) 0
f(n)=(g(n)) 0 f (n) =(g(n)) 100
O(n) 0 O(logn) 100
O(n) 0 O(logn) 100
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Option D whether correct marks Unit
.f (n) x g (n )0
2 3
A4
0
O(n^2)0
Both(b) and 100
Quadratic time
0
f(n)= o(g(n)) 0
f(n)= o(g(n)) 0
O(n2) 0
O(n2) 100
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Sr No Question Option A whether correct ?
1
The concept of order (Big O) is important because
it can e use
to decide the
best algorithm
that solves a
0
2
the input size, is given byT( n) = T( n - 1) + 1/n if n > 1 logn
100
3n e wors case, e num er o compar sons nee e
to search a single linked list of length n for a given logn 0
4
ma ema ca -mo e w a co ec on o opera ons
defined on that model is called Data Structure 0
5 Data structure in which one predecessor may have one
or more successor. Linear
0
6
me ac or w e e erm n ng e e c ency o
algorithm is measured by Counting Micro 0
7
c o e o ow ng s no e par o
description? data 0
8
c a a s ruc ure s es su e o pr n e
documents in the printer . Stacks 0
9 What term is used to describe an O(n) algorithm. Constan 0
10
me requ re o c ec o e erm ne w e er a g ven
no is prime quadratic 0
11 The space factor is measured by----
coun ng e
maximum 100
12
e prac ce ---- s use o e ne g ower oun on
growth of function f(n) big oh 0
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Option B whether correct ? Option C whether correct ?
it etermines
the maximum
size of a
problem that
100
Both a & b
0
n0
n20
n/2 0 log(n/2)-1 0
Abstract Data T 100pr m ve
data type 0
primitive
0
Non-linear
100
oun ng no o
statements 0oun ng no
of key 100
operations 0 Both a & b 100
Queues 100o s ac
queue 0
linear 100 logarithmic 0
linear 100 logarithmic 0
coun ng e
minimum 0coun ng e
aveage 0
big omega 100 big theta 0
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Option D whether correct marks Unit
None of the abo
0
nn0
n 100
algorithm 0
None of the
above
0
Counting key alg 0
one o e
above 0 1
Arrays 0
quadratic 0
constant time 0 2coun ng e
maximum disk 0
none of these 0
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Sr No Question Option A whether correct ?
1Which of the following symbols is used to denote a pre-
processor statement?! 0
2
The concept of order (Big O) is important because
it can e use
to decide the
best algorithm
that solves a
0
3
e me comp ex y o an a gor m n , w ere n s
the input size, is given by logn 100
4e or er o an a gor m a n s w e er a g ven
Boolean function of 'n' variables, produces a 1 is constant 100
5
n e wors case, e num er o compar sons nee e
to search a single linked list of length n for a given logn 0
6
ma ema ca -mo e w a co ec on o opera ons
defined on that model is called Data Structure 0
7
e erm a a s ruc ure re ers o -----------an
interelationship beween them
rogramm ng
language 0
8 Array is an example ofa c a a
structure 0
9 Two main measures for the efficiency of algorithm are Time and space 100
10 The complexity of the average case of an algorithm is
uc more
complicated to 100
11
a a w c can e v e ur er n o mean ng u
pieces is Atomic data 100
12c o e o ow ng s no e par o
description? data 0
13 . is not the component of data structure. operations 0
14 What term is used to describe an O(n) algorithm. Constan 0
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Option B whether correct ? Option C whether correct ?
# 100 ~ 0
it etermines
the maximum
size of a
problem that
100
Both a & b
0
n 0 n2 0
linear 0 logarithmic 0
n/2 0 log(n/2)-1 0
Abstract Data T 100pr m ve
data type 0
o ng
Standards. 0rgan za on
of data 100
Dynamic Data S 0 Linear data st 0
Processor and 0 Data and Spa 0
Much more sim 0ome mes
more 0
Primitive data 0ompos e
data 0
operations 0 Both a & b 100
s orage
structures 0 algorithms 0
linear 100 logarithmic 0
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Option D whether correct marks Unit
;0
1 3
None of the abo
0
nn 0
exponential 0
n 100
algorithm 0
None of this 0
both a & c 100
omp ex y an
capacity 0
None or above 0
one o e
above 0
one o e
above 0 1none o e
above 100
quadratic 0
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