Tricky sorting Algorithm

In this blog we have compared many sorting algorithms with new proposed Sorting Algorithm. Previously, all the Sorting Algorithm is capable of sorting positive integers. In this algorithm, we have come up with an idea of sorting positive repeating/non-repeating Integers having complexity, this algorithm is capable of searching element with O(1) complexity once sorting is complete. This algorithm can also be used to find the maximum repeating elements with complexity n. This algorithm was analyzed, implemented and tested and the results are promising for a random data.
Sorting Algorithm puts elements of a list in a particular order and makes it possible to search a particular data element in a collection quickly. Today real world has been getting enormous amount of data in form of data ware-houses, data marts etc and is used in many fields, where sorting is needed to organize it in a suitable format and to search for a particular element as and when required for a particular task. Thus, Sorting plays a major role in commercial data processing and in modern scientific computing.
For ex : Search Engine such as GOOGLE which searches word by word for the particular topic and then gives the desired output on screen as and when required. Many algorithms have been proposed by many known researchers’ until now, some of them are, BUBBLE SORT ALGORITHM, MERGE SORT ALGORITHM, HEAP SORT ALGORITHM, QUICK SORT ALGORITHM, INSERTION SORT ALGORITHM, SELECTION SORT ALGORITHM etc. A Sorting Algorithm is judged on the basis of its Computational Complexity, i.e, time needed by sorting algorithm to accomplish the task and Memory Usage, i.e, amount of memory needed to perform the operation.
In this blog, we devised a new sorting algorithm based on the number of elements given as an input by the user and arrange the given data in certain order. The Computational Complexity of the algorithm is O(n2) and the Space complexity of the algorithm is O(n2).