Algorithm Complexity
Presentation
•
Computers
•
University
•
Medium
Shahbaz Farooq
Used 8+ times
FREE Resource
21 Slides • 21 Questions
1
By Shahbaz Farooq
Big O Notation
2
Multiple Choice
3
Multiple Select
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Multiple Choice
5
Multiple Choice
6
What do you think ?
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Multiple Choice
If for an algorithm time complexity is given by O(1) then complexityof it is:
constant
polynomial
exponential
none of the mentioned
21
Multiple Choice
O(n)
O(m)
O(n+m)
O(n*m)
22
Multiple Choice
If for an algorithm time complexity is given by O(n) then complexityof it is:
A. constant
B. linear
C. exponential
D. none of the mentioned
23
Multiple Choice
What is the time complexity of this algorithm?
O(n)
O(2n)
O(log n)
O(n2)
O(1)
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Multiple Choice
What is the time complexity of this algorithm?
O(n)
O(2n)
O(log n)
O(n2)
O(1)
25
Multiple Choice
Why is this not a sequence?
Start car
Put in key
Turn key
Drive away
There are spelling mistakes
The instructions are in the correct order
The instructions are in the wrong order
It is a sequence
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Multiple Choice
Time Complexity of this program:
def f():
a = 0
for i = 1 to n:
a += i;
b = 0
for i = 1 to m:
b += i;
O(n)
O(m)
O(n+m)
O(n*m)
30
Multiple Choice
If for an algorithm time complexity is given by O(1) then complexityof it is:
constant
polynomial
exponential
none of the mentioned
31
Multiple Choice
If for an algorithm time complexity is given by O(n) then complexityof it is:
A. constant
B. linear
C. exponential
D. none of the mentioned
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Multiple Choice
Indicate constant time complexity in terms of Big-O notation
O(n)
O(1)
O(log n)
O (n^2)
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Multiple Choice
Indicate exponential time complexity in terms of big-O notation
O (n)
O (n^2)
O (2^n)
O (log n)
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Multiple Choice
Find the slowest time complexity
O (n)
O (n^2)
O (n!)
O (2^n)
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Multiple Choice
Which notation is consistent for every execution?
O (n)
O (n^2)
O (1)
O (2^n)
36
Multiple Choice
The O (n!) is so inefficient, there is no practical use for it
True
False
37
Fill in the Blanks
Big-O is used to identify the most
Type answer...
38
Multiple Choice
O (n log n) is the worst case scenario for
Merge Sort
Bubble Sort
Binary Search
Linear Search
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Multiple Choice
O n2 is the worst case scenario for
Merge Sort
Bubble Sort
Binary Search
Linear Search
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By Shahbaz Farooq
Big O Notation
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