Algorithms
Complexity Analysis and Asymptotic Notations
Marks 1Marks 2
Searching and Sorting
Marks 1Marks 2
Divide and Conquer Method
Marks 1Marks 2
Greedy Method
Marks 1Marks 2
P and NP Concepts
Marks 1Marks 2
Dynamic Programming
Marks 1Marks 2
1
GATE CSE 2004
MCQ (Single Correct Answer)
+2
-0.6
The time complexity of the following C function is (assume n > 0)
int recursive(int n){
 if(n == 1){
   return (1);
 }
 return (recursive(n - 1) + recursive(n - 1));
}
A
O(n)
B
O(n log n)
C
O(n2)
D
O(2n)
2
GATE CSE 2004
MCQ (Single Correct Answer)
+2
-0.6
Let A[1,...,n] be an array storing a bit (1 or 0) at each location, and f(m) is a function whose time complexity is O(m). Consider the following program fragment written in a C like language:
counter = 0;
for(i = 1; i <= n; i++){
 if(A[i]==1){
   counter++;
 }else{
   f(counter); counter = 0;
 }
}
The complexity of this program fragment is
A
$$\Omega ({n^2})$$
B
$$\Omega (n\,\log n)\,and\,O({n^2})$$
C
$$\theta (n)$$
D
$$O(n)$$
3
GATE CSE 2004
MCQ (Single Correct Answer)
+2
-0.6
What does the following algorithm approximate?
(Assume m > 1, $$ \in > 0$$)
x = m;
y = 1;
while(x - y > ε){
 x = (x + y) / 2;
 y = m/x;
}
print(x);
A
log m
B
m2
C
m1/2
D
m1/3
4
GATE CSE 2004
MCQ (Single Correct Answer)
+2
-0.6
The recurrence equation
T(1) = 1
T(n) = 2T(n - 1)+n, $$n \ge 2$$
Evaluates to
A
2n+1 - n - 2
B
2n - n
C
2n+1 - 2n - 2
D
2n + n
GATE CSE Subjects
Theory of Computation
Operating Systems
Algorithms
Digital Logic
Database Management System
Data Structures
Computer Networks
Software Engineering
Compiler Design
Web Technologies
General Aptitude
Discrete Mathematics
Programming Languages
Computer Organization