Data Structures and Algorithms

Data Structures and Algorithms are considered one of the most important topics in computer science. This post and the ones linked below are aimed at helping people understand the significance of this topic and also to show how data structures and algorithms can be used in various applications.

Data Structures allow us to store information in a way that helps the programmer solve complex problems quickly while algorithms are basically the instructions for performing a task.

The reason why algorithms are considered important is because a good algorithm can perform the same task millions of times faster than a badly written algorithm. For example, let us say that you have a database with some items that we want to sort. If we compare the number of operations that it takes for selection sort and merge sort for increasing amount of items we get the following graph:

As we can see in the above graph, as the number of items that need to be sorted increases, the time it takes for the sort largely depends on the quality of the algorithm that we are using.

Here are the links to the posts that either implement various data structures and algorithms into some projects or analyze various algorithms to find which algorithm works best and in what situation:

If you wish to learn more about data structures and algorithms, I would strongly recommend the following two part free course on coursera:

Algorithms, Part I | Algorithms, Part II

If you have any questions or have a project recommendation, feel free to leave a comment below.

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Project 6 - State Space Search - 8-Puzzle

State space search is a process which is used to create simple artificial intelligence. It can be used when the problem can be represented as a set of simple states and the player / agent is the only one who can affect the environment. It allows us to generate a path from the initial state to the goal state (of which there can be many depending on the problem). 8-Puzzle / Sliding Puzzle , N-queens and Route Finding are some of the various problems which can be solved using state space search. Let us explore the process of solving the 8-Puzzle problem using various path finding algorithms and comparing how effective each of them is. To get started, we need to start by creating the 8-Puzzle game itself. First, we need a simple way to represent different states of the puzzle. A good way to do this is to store the state as a string. For example: Next up, we need a way to generate the actions that are possible from a particular state. We can think of it as moving the empty space itself

Project 1 - Browser linked list implementation

All of us use a browser to surf through the internet. In fact you are using one right now. Have you ever wondered how the forward and backward buttons of the browser work ? Or how the undo and redo functions of your text editor works ? The answer to this is a doubly linked list. A linked list consists of various individual nodes which store some data as well as a pointer to the next node. A doubly linked list has nodes which have pointers to the previous node as well. In a circular linked list, the last node points to the first node. Here is how the application is going to work: Whenever you go to a new website, a new node is added in front of the current node. And the forward and backward button traverse through the linked list. If you wish to tinker with the code, here is the Github Repository . You can easily expand this program to act like undo and redo buttons of a text editor. Linked list are used in various other practical applications such as photo viewers and music players. A

Project 3 - Analysis of sorting algorithms

Sorting algorithms are one of the most basic as well as one of the most used algorithms. They form the basis for many other data structures and algorithms and are also a great way to learn to analyse algorithms. In this post, I would like to perform my own analysis of these sorting algorithms to understand where and why various sorting algorithms should be used. My main focus is going to be practical analysis of these sorting algorithms and I am also going to be considering the simplicity of these algorithms. So first, let us think about what basis we are going to use for these sorting algorithms. To analyse any sorting algorithm, let us measure the time it takes to sort an array of integers. The array of integers that we are going to give to the sorting algorithms should be of the following types: Random arrays. Ex: [5, 2, 9, 7, 0, 4]. Sorted arrays. Ex: [3, 5, 7, 8, 11]. Sorted arrays in reverse order. Ex: [14, 11, 7, 3, 1]. Sorted arrays with a few random elements added to the end.

Satwik Kambham

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