Big-O Notation

Front

Indicate constant time complexity in terms of Big-O notation

Back

O(1)

Front

Indicate exponential time complexity in terms of big-O notation

Back

O (2^n)

Front

Find the slowest time complexity: O (n), O (n^2), O (n!), O (2^n)

Back

O (n!)

Front

Which notation is consistent for every execution? Options: O (n), O (n^2), O (1), O (2^n)

Back

O (1)

Front

The O (n!) is so inefficient, there is no practical use for it

Back

False

Front

Which notation grows in proportion to the size of the input? Options: O (n), O (n^2), O (1), O (2^n)

Back

O (n)

Front

Which notation would you usually use for a nested loop?

Back

O (n^2)

Front

Indicate polynomial time complexity in terms of big-O notation

Back

O (n^2)

Front

Big-O is used to identify the most ____ algorithm for a specific purpose

Back

Efficient, Time efficient

Front

When calculating the Big-O for an algorithm, which of the following rules is not true?
Focus on the dominant term,
Disregard any constants,
Focus only on polynomials,
Count the number of assignments

Back

Focus only on polynomials