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 2003
MCQ (Single Correct Answer)
+1
-0.3
The usual $$\Theta ({n^2})$$ implementation of Insertion Sort to sort an array uses linear search to identify the position where an element is to be inserted into the already sorted part of the array. If, instead, we use binary search to identify the position, the worst case running time will
A
remain $$\Theta ({n^2})$$
B
become $$\Theta (n{(\log \,n)^2})$$
C
become $$\Theta (n\log \,n)$$
D
become $$\Theta (n)$$
2
GATE CSE 2002
MCQ (Single Correct Answer)
+1
-0.3
The solution to the recurrence equation
T(2k) = 3 T(2k-1) + 1, T (1) = 1, is:
A
2k
B
(3k+1 - 1)/2
C
3 log 2K
D
2 log 3K
3
GATE CSE 2001
MCQ (Single Correct Answer)
+1
-0.3
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?
A
O(n)
B
O(n Log n)
C
O(n2)
D
O(n!)
4
GATE CSE 2000
MCQ (Single Correct Answer)
+1
-0.3
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?
A
t (n) is O(1)
B
n < t (n) < $$n\log _2^n$$
C
$$n\log _2^n$$ < t (n) < $$\left( {\matrix{ n \cr 2 \cr } } \right)$$
D
t(n) = $$\left( {\matrix{ n \cr 2 \cr } } \right)$$
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