What is the main reason O(N!) complexity is considered impractical?
Data Structures and Algorithms The Complete Masterclass - Big O(n!) Complexity

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Information Technology (IT), Architecture
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University
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Hard
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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
It is commonly used in everyday applications.
It is easy to implement.
It involves a high number of nested loops.
It requires a lot of memory.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does O(N!) complexity affect the time taken by an algorithm?
Time increases significantly with each additional item.
Time decreases with fewer nested loops.
Time remains constant regardless of the number of items.
Time decreases as the number of items increases.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does O(N!) complexity imply for each element in an array?
Each element requires a single loop.
Each element is processed independently.
Each element adds a nested loop.
Each element reduces the overall complexity.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to be aware of O(N!) complexity?
It is the most efficient complexity for large datasets.
It is frequently used in coding interviews.
It represents the best-case scenario for algorithms.
It is the worst-case scenario and helps in understanding algorithm limits.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is true about encountering O(N!) complexity in real-world applications?
It is commonly encountered in everyday coding tasks.
It is almost impossible to encounter.
It is the most efficient complexity for sorting algorithms.
It is frequently used in machine learning models.
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