The Art of Understanding a Simple Sorting Algorithm
When it comes to sorting algorithms, there are many different approaches and techniques that can be used to achieve efficient and effective results. In this article, we will explore one such algorithm, known as quicksort, and examine how it works in detail.
Let's start with an example of the code itself, which is quite simple to understand:
```
while I is greater than zero
my six got copied here
my six replaced my five right then I equals to I minus one
so what happened to my eye my eye became zero now if this loop again restarts because this is a loop right this is the loop now here while I is greater than zero no I is equal to zero now so I will come out of this loop as soon as I come out of this loop it says AI plus one equals two key now what is AI plus 1
```
As we can see, this code appears to be a simple loop that increments the value of `I` by 1 until it reaches 0. However, upon closer examination, we realize that there is actually more going on beneath the surface.
The first part of the loop copies the current value of `my six` into itself, and then replaces it with the value of `my five`. This is a clever trick to avoid having to use an extra variable to store the current value of `my six`.
Next, the code calculates the new value of `I` by subtracting 1 from its current value. This results in `my eye` becoming zero. However, the loop does not simply stop here - it actually restarts because this is a loop.
The inner part of the loop checks whether `my I` is still greater than zero. If it is, then the loop continues indefinitely. But if `my I` is equal to zero, then the loop exits.
Now, let's examine what happens when `J` takes on different values. We will take the example of `J equals 2`, and walk through the steps of the algorithm:
```
at the end of J equals 2 at the end of my first outer iteration
my first so this became five
so what is my area of my array now
is five six three one eight seven two four
```
As we can see, the value of `my first` has increased to 5. This means that the current subarray being sorted is now `[5, 6, 3, 1, 8, 7, 2, 4]`.
Next, we examine what happens when `J` equals 3:
```
at the end of J equals to do this is the this is the array that you have now
take J equals to 3 because this loop is running right now try to write the same thing on your notebook so then you know how these so how this inner loop and outer loop are working in a nutshell what's happening is so so you want you want to do that walkthrough on your page on your notebook so that you understand this code better right
```
As we can see, the value of `J` has increased to 3. This means that the current subarray being sorted is now `[4, 5, 6, 3, 1, 8, 7, 2]`.
We can continue to examine different values of `J`, and walk through the steps of the algorithm. Each time we do so, we gain a deeper understanding of how the quicksort algorithm works.
Let's examine what happens when `J` equals 6:
```
when J equals to 6 I am trying to take the sixth element and trying to insert into this array which is already sorted right
when my J equals to 6 a 1 2 a 5 are already sorted so I'm taking the value of a 6 or AJ into key right and I will start from a J minus 1 from here from here rest of the elements this is exactly what the intuition says right
```
As we can see, when `J` equals 6, we are trying to insert the sixth element into the array. The array is already sorted, so we know that the new value will be inserted at the correct position.
We can continue to examine different values of `J`, and walk through the steps of the algorithm. Each time we do so, we gain a deeper understanding of how the quicksort algorithm works.
The key insight behind this algorithm is that when `J` equals `n-1`, where `n` is the length of the array, we know that all the elements in the subarray are already sorted. In this case, we simply take the value of `AJ` and insert it into the correct position in the array.
To achieve this, we start from `J-1` (which is 5 in our example) and iterate through each element in the subarray. We compare the current element with the value of `AJ`, and if it is smaller, we increment `my I` by 1. If it is larger, we simply move on to the next element.
By doing so, we effectively "partition" the array into two parts: elements that are less than or equal to `AJ`, and elements that are greater than `AJ`. This allows us to recursively apply the same algorithm to each part of the array, resulting in a fully sorted array.
In conclusion, the quicksort algorithm is a simple yet elegant solution to the problem of sorting arrays. By understanding how it works, we can gain a deeper appreciation for the underlying mechanics of this algorithm and develop our own solutions to similar problems.