There are two main ways to traverse a tree data structure, breadth first search (BFS) and depth first search (DFS). As the name suggests BFS travels the trees width first, visiting each node layer by layer until the end is finally reached. For example, in the tree below BFS will travel the following path: [A, B, C, D, E, F, G, H, I, J, K, L]
When it comes to understanding data, sorting is perhaps one of the most useful tools we have to help make sense of a data set. Many different algorithms have been developed over the years to improve the speed in which data can be sorted and the ones I will be comparing here are bubble sort, insertion sort, selection sort, mergesort, and quicksort. Hopefully after reading this you will be able to understand how each of these methods work and when (if ever) should they be used in sorting. We will begin with bubble sort.
Graphs are one of the most used and useful data structures used in computer science when it comes to modeling real life. Essentially, graphs are a set of nodes (vetricies) which are connected to each other with edges. These connections are great at representing real life relationships such as creating a map of roads between two cities, or giving a list of autocomplete suggestions when typing out a word. Trees and linked lists are both types of graphs and there are a few characteristics we can look for to help describe the graph.
As I continue to study data structures I finally arrived at trees. The first tree I was introduced to was the Binary Search Tree. Binary Search Trees are ordered trees that as the name suggests, are ideal for searching, with a Big O (log n) which is much more efficient than the linear time of arrays. The basics of Binary Search Trees are pretty simple, each node may have two branches, the left is reserved for items of lesser value and the right branch is for larger values. For example if the parent node is 5 then 3 would go to the left and 8 would go to the right. If duplicates are allowed they are typically sorted to the right. While I won’t be going over removing items in this post the idea is pretty simple, if the node has no children it is just erased, otherwise is removed by the leftmost node in the right branch below it - which should be the next largest value in the tree. Anywho let us begin building the tree.
Welcome everybody, this is meant to be a quick beginners guide to React Native and will briefly cover what it is, how to install, and how to get coding. I am still new to React Native myself and hope writing this blog will also be a good resource for myself going forward as well.