Why do we need sorting

Create a free Team What is Teams? Learn more. Why do we need so many sorting algorithms? Asked 3 years, 10 months ago. Active 3 years, 10 months ago. Viewed 2k times. Improve this question.

Add a comment. Add a comment. Active Oldest Votes. Here is a non-exhaustive list of things that can be learned by studying sorting algorithms: divide and conquer; heaps; binary search trees, including different types of self-balancing binary search trees; the importance of choosing an appropriate data-structure; difference between in-place and not-in-place; difference between stable and non-stable sort; recursive approach and iterative approach; how to calculate the time complexity, and how to compare the efficiency of two algorithms;.

Improve this answer. Stef Stef 5, 1 1 gold badge 11 11 silver badges 21 21 bronze badges. Merge sort appears to have been invented by John von Neumann to validate his stored-program computer model the von Neumann architecture. Insertion sort seems to have been around forever. Quicksort was invented in It plays excellently with processor caches, hence its continued popularity. Sorting networks were studied extensively many years back.

Timsort was invented for Python and was designed to sort practical, real-world sequences faster than other sorts by taking advantage of common distributions and patterns. Introsort was invented as a practical way to harness the speed of quicksort without its worst-case behavior. Shellsort was invented over fifty years ago and was practical on the computers of its age. Probing its theoretical limits was a difficult mathematical problem for folks who studied it back then.

But if the list is unsorted to a large extend then this algorithm holds good for small datasets or lists. This algorithm is fastest on an extremely small or nearly sorted set of data. This algorithm is stable and it has fast running case when the list is nearly sorted. The usage of memory is a constraint as it has space complexity of O 1.

It is widely used for external sorting, where random access can be very, very expensive compared to sequential access. It is used where it is known that the data is similar data. Merge sort is fast in the case of a linked list.

It is used in the case of a linked list as in linked list for accessing any data at some index we need to traverse from the head to that index and merge sort accesses data sequentially and the need of random access is low. The main advantage of the merge sort is its stability, the elements compared equally retain their original order. The slight disadvantage of quick sort is that its worst-case performance is similar to average performances of the bubble, insertion or selections sorts.

In general, the quick sort produces the most effective and widely used method of sorting a list of any item size. This algorithm has several advantages. It is simple to write, easy to understand and it only takes a few lines of code. The data is sorted in place so there is little memory overhead and, once sorted, the data is in memory, ready for processing.

The major disadvantage is the amount of time it takes to sort. The sorting process begins with the removal of incorrect items such as crisp packets and plastics bags. A vibrating machines separates the cardboard and paper — different types of paper are sorted by hand and then baled. The remaining recyclables continue on another conveyor where steel cans are removed using magnets. Skip to content Popular.