Slices in Go programming language gives us greater flexibility over working with arrays, but this flexibility comes with some trade-offs. Go optimizes towards the most frequent uses cases, and you are often working with them correctly. However, in certain cases, some of the implicit hidden behaviors of Go slices can create unclear issues which can be hard to diagnose at the first place. In this post, we will go over some of the implicit behaviors while recapping how slices work in Go in general.
I stumbled upon rocketlaunchr.cloud's great post on using generics in Go 2, and the post shows how you can implement ordered maps. The post is very informative, and shows you how powerful Generics will be for Go. However, I noticed a performance issues with the implementation of Delete operation on the ordered map, which can be a significant performance hit where there is a need to store large collections while making use of the Delete operation frequently. In this post, I want to implement that part with a Doubly Linked List data structure to reduce its time complexity from O(N) to O(1).
Heap is one of the powerful data structures, which optimizes the access to minimum or maximum value within a collection. In this post, we will go over the main characteristics of the data structure itself and understand how we can make use of it with Go (Golang) programming language with the usage heap package from the base library of Go.
A while ago, I have written up on Graphs and gave a few examples about their application for real world problems. In this post, I want to talk about one of the most common graph algorithms, Depth-first search (DFS).