# The Anatomy of a User Model

Here I’ll be talking about some things to think about when starting a new project with users and user authentication. What are the fields necessary in a user table? What kind of relationships to other tables might there be? What may become useful in the future? Save some time by setting up a comprehensive user model from the start.

Starting with the obvious, a user must be identifiable, typically with something unique such as a username or email address. Whichever you choose, add validation to ensure uniqueness. Next, we need a password. It is best to hash the password using…

# Floyd’s Cycle Detecting Algorithm Explained

Today we’ll discuss Floyd’s algorithm to detect cycles in a linked list. This algorithm uses two pointers, one fast and one slow, in order to find where a linked list cycles. An example of this problem can be found here.

The idea of this algorithm is to progress through a linked list and keep track of 2 nodes. We start at the beginning (head) of the given linked list. We assign that node as the “slow” pointer. We assign the next node the “fast” pointer. Next, we start stepping through the list as long as the fast and slow pointer…

# Finding Primes with Ruby

A prime number is a number other than 1 that is only divisible by itself and 1. For example, the prime numbers between 1 and 10 are 2, 3, 5, and 7. So just knowing the definition of a prime number gives a huge hint on how to build an algorithm to find all of the prime numbers between 0 and n.

The easiest way to solve this problem is to use trial division. Go through each number n, and check the remainder of dividing n by every number before it besides 1. If you find a number that has…

# Bcrypt: An Overview

What is Bcrypt? Why is it a popular way to keep passwords secure? Today we will answer these questions and gain a deeper understanding of Bcrypt.

Bcrypt is a hashing algorithm based on the Blowfish Cypher. It takes in a plain text password as an input and returns a hash of that password (along with some other stuff we’ll get to later) as a string for the output. Is this encryption? No. Encryption is a two-way function, meaning something can be decrypted with the key. So if an attacker has the right key, they can use it to find out…

Breadth first search is a common technique to search a tree data structure. As in the name, this algorithm traverses the tree shallow before going deeper. A tree usually consists of nodes or vertices that hold a value as well as point to other values, which links these items together in a tree like structure.

Let’s look at some pseudocode for how to implement the algorithm, this uses key value pairs to keep track of visited nodes and a queue to keep track of the next nodes to visit:

# Depth First Search and Simple Recursion

Today we’ll be talking about a technique to search through a tree called Depth First Search. One common implementation of a tree is a binary tree. A binary tree is a data structure consisting of nodes. Each node contains a value and a pointer to the next two nodes in the tree, right and left. A binary tree can be visualized as below:

There are many ways to search this data structure, and one is Depth First Search (DFS). DFS starts at a node, and searches through the tree one node at a time until it finds a node that…

# Implementing Quick Select in Ruby

In this blog, we’ll walk through how to write the Quick Select algorithm in Ruby. This technique is used to find the kth smallest element in an unsorted array, with an average runtime complexity of O(n). Quick Select uses a similar approach to the popular Quick Sort algorithm. It is a divide and conquer approach where the array to search is cut into smaller and smaller pieces until the desired result is found.

At first glance, finding the kth smallest element of an array is simple. Just sort the array and pick the element at the index [k - 1]…

# Implementing Quicksort in JavaScript

In this blog, we implement a Quicksort in JavaScript. Quicksort is an algorithm used to sort arrays with a divide and conquer technique. First, we select a pivot element of the array, in this case the middle element. Next, we swap elements that are greater than or less than the pivot and produce 2 sub-arrays. When successful, the sub-array on the right only contains elements that are greater than the pivot, and the one on the left only contains elements that are less than the pivot. After this step, we know that the pivot element has found its’ final position…

# Recursion, Fibonacci, and Speed with Ruby

The Fibonacci sequence is a sequence of numbers where the next number in the sequence is the sum of the previous 2 numbers. It is typically illustrated like this:

In this blog, I’ll be dipping my toes into the basics of how recursion works. I’ll implement two different solutions in Ruby to find the element of the Fibonacci sequence specified. The first solution is more standard coding practice while the second uses a more elegant, recursive solution to do the job.

The first solution takes in a number n, and creates a Fibonacci sequence from the beginning all the way… 