Which of these characteristics is typically used to analyze and compare the efficiency of sorting algorithms?
Code readability, which refers to how easy the code is to understand.
Programming language used to implement the algorithm.
The specific data values being sorted.
Time complexity, which measures the number of operations as data size grows.
Why is Insertion Sort not preferred for large datasets?
Its time complexity is quadratic in the worst case
It is not a stable sorting algorithm
It has a high space complexity
It is difficult to implement
What is the space complexity of Bubble Sort in its standard form?
O(log n)
O(1)
O(n)
O(n^2)
Which statement BEST describes the significance of understanding sorting algorithms?
It's primarily a theoretical concept with little practical relevance.
It's only essential for software engineers specializing in algorithm development.
It enables developers to choose the most suitable algorithm for a given task based on efficiency and data characteristics.
All sorting algorithms perform equally well, so understanding them is unnecessary.
Which algorithm repeatedly finds the minimum element from the unsorted part and puts it at the beginning?
Selection Sort
Bubble Sort
Quick Sort
Merge Sort
What is the worst-case space complexity of Insertion Sort?
O(n log n)
Is Bubble Sort a stable sorting algorithm?
Yes
Only in its optimized version
Stability is irrelevant for Bubble Sort
No
What is the worst-case time complexity of Selection Sort?
Sorting algorithms can be broadly classified into two categories. What are they?
Stable and Unstable
In-place and Out-of-place
Comparison-based and Non-comparison-based
Recursive and Iterative
Bubble sort performs better than selection sort in which scenario?
When the input array is randomly ordered.
When the input array is already sorted.
When the input array is reversely sorted.
Bubble sort never outperforms Selection sort