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One of the most important aspects of programming is algorithms. An algorithm in a nutshell is a set of instructions for solving a problem in a particular way, with the goal being to find an efficient solution to said problem. There can be several different algorithms for doing the same thing, and it all depends on what kind of efficiency you’re looking for. Today we’re going to be talking about some of the most popular classes and number one choices for many programmers, such as quicksort and binary search.

Today we’ll be focusing on the quicksort algorithm, which is a sorting algorithm that sorts an array of data, such as a list of numbers. In today’s article we’ll be looking at what this sorting algorithm does, and why we would choose to use it.

The quicksort algorithm breaks down into three steps: partition the array into two sub-arrays; swap the elements of one sub-array with those in another; and recursively sort each sub-array. This algorithm can be done in any O(n²) time for any given size of array, but the deeper than this will become to more efficient solutions.

As you can see, this algorithm is quite pregnant with steps. Therefore, it’s taken so long for quicksort to be made efficient enough to be used regularly. However, it’s still widely used today because of its simplicity and effectiveness, which are largely due to its implementation.

Before we can get started, we first need to talk about the data structure that quicksort will be sorting.

The quicksort algorithm is simple. If you’re familiar with any other sorting algorithms, then you’ll be familiar with the idea of “sorting an array.” This means that we’re going to take an array, and sort all the elements inside of it. The difference between this and other sorting algorithms is how it’s done.

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