The world of computer science is abuzz with new developments in sorting algorithms! According to a recent article, four popular sorting algorithms have been analyzed for their efficiency and complexity. The findings show that each algorithm has its strengths and weaknesses.

* Bubble sort: Best case O(n2), average and worst-case O(n2), space complexity O(1). Not the most efficient, but can be useful when the array is already sorted.
* Insertion sort: Best case O(n), average and worst-case O(n2), space complexity O(1). A simple yet effective algorithm for small datasets.
* Merge sort: Best, average, and worst-case O(nlogn), space complexity O(logn) due to recursion. A reliable choice for larger datasets.
* Quick sort: Best, average, and worst-case O(nlogn), space complexity O(1). A popular choice due to its high efficiency.

These findings highlight the importance of understanding the strengths and weaknesses of each algorithm, as well as considering factors like space complexity when selecting the best approach for a given task.

Source: https://dev.to/madgan95/sorting-algorithms-dsa-4-50j5