What is a major limitation of bubble sort?

Bubble sort is characterized by its simplicity in implementation, which makes it easy to understand. However, one of its major drawbacks is that it is inefficient for large datasets. The algorithm repeatedly steps through the list to be sorted, compares adjacent elements, and swaps them if they are in the wrong order. This process continues until the list is sorted.

The reason bubble sort is considered slow, particularly with larger datasets, is due to its time complexity, which is O(n^2) in the average and worst-case scenarios. This means that as the number of elements increases, the time it takes to sort the list grows quadratically. In practical terms, this inefficiency results in a longer sorting time as the size of the dataset increases. For large data collections, more efficient algorithms such as quicksort or mergesort, which have better average-case time complexities, are usually preferred.

Additionally, bubble sort does not require a sorted list to function, does not use excessive memory space since it is an in-place sorting algorithm, and while it can work with large datasets, it simply becomes impractical compared to more efficient sorting algorithms.