Big O Notation Revision

What does the Big O notation O(1) signify about an algorithm's performance?

• The algorithm's performance improves as the data set increases.

• The algorithm's performance declines as the data set increases.

• The algorithm executes in the same time regardless of the size of the data set.

• The algorithm's performance is proportional to the square of the size of the data set.

Which Big O notation describes an algorithm that halves the data set in each pass?

• O(n)

• O(log n)

• O(n²)

• O(2ⁿ)

What type of algorithmic complexity is described by O(N^2)?

• Constant

• Logarithmic

• Linear

• Polynomial

Which example use is associated with the Big O notation O(N)?

• Binary search

• Hashing algorithm

• Linear search

• Quick sort

What is the Big O notation for an algorithm that becomes less efficient with each addition to the data set, doubling its processing time?

• O(1)

• O(n)

• O(log n)

• O(2ⁿ)

What is the average time complexity of a binary search on an array?

• O(1)

• O(log n)

• O(n)

• O(n²)

What is the worst-case space complexity of Merge Sort?

• O(1)

• O(log n)

• O(n)

• O(n log n)

Which searching algorithm has a best case time complexity of O(1)?

• Linear search

• Binary search tree

• Hashing

• Breadth/Depth first of graph

What is the best case time complexity for Quick Sort?

• O(n)

• O(n²)

• O(log n)

• O(n log n)

Which algorithm has a worst-case time complexity of O(n log n)?

• Merge Sort

• Quick Sort

• Insertion Sort

• Bubble Sort