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.
The specific data values being sorted.
Time complexity, which measures the number of operations as data size grows.
Programming language used to implement the algorithm.
Is Bubble Sort a stable sorting algorithm?
Only in its optimized version
Yes
Stability is irrelevant for Bubble Sort
No
Which algorithm repeatedly finds the minimum element from the unsorted part and puts it at the beginning?
Merge Sort
Bubble Sort
Selection Sort
Quick Sort
Insertion Sort can be considered an incremental algorithm. What does this mean?
It requires the entire dataset to be present in memory
It divides the problem into smaller subproblems
It can handle data arriving in a continuous stream
It performs better on smaller datasets
Why is Insertion Sort not preferred for large datasets?
It is difficult to implement
It is not a stable sorting algorithm
Its time complexity is quadratic in the worst case
It has a high space complexity
Bubble sort performs better than selection sort in which scenario?
Bubble sort never outperforms Selection sort
When the input array is already sorted.
When the input array is reversely sorted.
When the input array is randomly ordered.
Why are sorting algorithms considered fundamental in computer science?
They are the basis for more complex algorithms and data structures.
They are primarily used for displaying data to the user.
They are only used in specific niche applications.
They are rarely used in modern software development.
Which sorting algorithm is generally considered more efficient for small datasets?
It depends on the data distribution
They have the same efficiency
Which of the following sorting algorithms is NOT comparison-based?
Insertion Sort
Radix Sort
Which statement BEST describes the significance of understanding sorting algorithms?
All sorting algorithms perform equally well, so understanding them is unnecessary.
It enables developers to choose the most suitable algorithm for a given task based on efficiency and data characteristics.
It's only essential for software engineers specializing in algorithm development.
It's primarily a theoretical concept with little practical relevance.