Sorting Algorithms

       Now it is time to sort the sorting algorithms by which one has the best runtime in their worst case! But, which sorting algorithm will we use to sort the sorting algorithms?

       Alright, all joking aside, algorithm efficiency is an essential part of the basics of computer science. Algorithm is simply a fancy word for a series of steps to solving what seems to be a complex problem. Looking at complex problems, we know there are numerous ways to approach it.
       Let's take a look at the current gaming craze '2048'. You have a 4x4 grid, and you start off with 2 tiles of either two '2's or one '2' and one '4'.You can move them in 4 directions (up, down, left, right).  Moving two of the same number tiles onto one another adds them up. As the game progresses, more tiles of value '2' and '4' appear randomly. We have to add all those tiles up until we reach a tile that has a value of '2048'. One strategy is to randomly move the pieces around and hope they eventually add up to the 2048 tile. Of course, we know this quickly leads one to get stuck an lose the game. So that is not a good strategy to follow. A better one is thinking about how to isolate the tiles with similar values so they can be added together easily. You can pick one of the corners to push all the tiles towards, and you will see that it adds up to higher powers of 2 much faster than randomly moving the pieces around in the center.
      This is the gist of algorithm efficiency. We just have to figure out what kind of algorithm uses simple moves but solves a complex problem much faster. In class we were given some examples of sorting algorithms. There are ones that check through the entire list and swap items that are out of order, like selection or insertion sort.  Other sorting algorithms which continually split the list into smaller halves until a certain point and then they sort the smaller lists like merge sort and quick sort. The latter are much more efficient because even though both break down the problem into simpler steps, the former sorting algorithms always go through much of the list with each step, and the latter only goes through sections with each step, which is much faster.

       The important part is to remember that not all simple steps are equal, some are much better for certain situations.  Algorithms are then, in essence life lessons. We should all strive to do things the easier way instead of the hard way! What could possibly go wrong?