Algorithms & Data Structures — Paul Lemelle

I recently heard a software development podcast where one of the hosts mentioned that they did not want to learn algorithms & data structures. And to be honest, I understand why an individual may believe that algorithms & data structures is a scary subject for the simple fact that most books that I have read on the subject starts off with the math of "Big-O Notation." I do not claim to be an expert in this field, but I wanted to challenge myself to expand my own knowledge in the area, and hopefully, inspire someone else as well. In short, I believe you should start with the problem you are trying to solve then figuring out how to apply computer science to solve it.

Arrays:

Arrays are probably one of the most common data structures of any programming language. In short, a data structure is a way for a computer to read & write data. A linear array (simplest form) is an unordered collection of values that are stored contiguously in memory.

Paul LemelleJanuary 3, 2018

Sets:

Sets are unordered collection of unique values that share many Big-O characteristics & overall functionality with array based data structures. However, there are some key differences that are worth exploring and to better help illustrate differences between the two data structures as it relates to Big-O notation.

Paul LemelleJanuary 2, 2018

Binary Search & Sorting

Binary Search requires a sorted collection, and thankfully most programming languages (including Swift) have a sort method built in, but there are times that you may want to choose a different sorting algorithm. Selection Sort & Quick Sort take two different approaches to the sort problem and how the performance can vary between the two.

Paul LemelleJanuary 1, 2018