The Whats and Hows of Algorithm Sorting 

We all know about the significance of algorithms in the coding world. Algorithm is a precise step-by-step plan for a computational procedure that possibly begins with an input value and yields an output value in a finite number of steps. However, what most of us don’t know is that algorithms need to be sorted during binary search with the help of arrays. These are a series of memory locations or boxes where a single item of a data is stored.   

There are primarily three sorting types: Insertion sort, merge sort and selection sort. Coders are often unsure which one to use and when. Well, it all depends upon the situation. Let us now understand each sorting types in details. 

Selection sort 
It is the most fundamental kind of sorting, where, at the start of an array, the algorithm in function continuously locates the smallest value from an unsorted subarray (a part of an array) and transfers it to a sorted subarray. For instance, take the array 5, 3, 4, 1, 2 wherein the beginning, ‘5’ seems like the smallest value, but as we gradually cover the entire array, we realize ‘1’ is the smallest value and arrange the algorithm accordingly, starting with 1 and ending with 5. This repeating process needs to be done unless the whole array is completed. Although it may not be efficient, selection sort is used when things need to done quickly.  

Insertion sort 
In insertion sort, the algorithm itself locates subsequent values from the arrays and starts sorting them out on its own without any interference. Therefore, insertion sort is used to reorder an unsorted array from lowest to highest number. For instance, if you are dealing cards, to keep track of them, you can organize the dealt ones starting with the smallest value and moving on to the largest one. This is how insertion sort works too. When you begin with array A, it is of the smallest or largest value considering there’s no reference card. But supposing array B has a higher value, then array A is the first one, followed by array B and this goes on until the algorithm is able to cover the entire array. This sorting comes in handy, when time isn’t of the essence but right way of organizing is.  

Merge sort 
Merge sort is the most used sorting in algorithms which follows the divide and conquer rule. Here, the algorithm in question keeps dividing the arrays into halves, until the subarrays are left behind with only one element. At this point, the algorithm helps merging back the halves together, but this time in a specific order (decreasing to increasing value or vice versa). And in all this, the recursion programming technique is used, that helps the algorithm to figure things out on its own without any external directives. Merge sort is mostly used when a problem is solved by dividing it into subproblems until it is entirely solved. For instance, during a party, friends want to order a pizza. But everyone gets pizza, only when the others agree, until someone in the group realizes that pizza is something that everyone would want, says “yes,” which is when everyone can’t help but agree. This method is also especially helpful when the sorting needs to stable or a large data set needs to be sorted. It is perhaps the most efficient, but is hard to implement and consumes a lot of space. It is mostly used for solving linked lists.