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.
Recent posts
Working with Slices in Go (Golang) - Understanding How append, copy and Slice Expressions Work
Implementing OrderedMap in Go 2.0 by Using Generics with Delete Operation in O(1) Time Complexity
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).
Usage of the Heap Data Structure in Go (Golang), with Examples
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.
Recent speaking activities
Essentials for Building and Leading Highly Effective Development Teams
Let the Uncertainty be Your Friend: Finding Your Path in a Wiggly Road
Getting Into the Zero Downtime Deployment World
Hey, I'm Tugberk 👋
Coder 👨🏻💻, Speaker 🗣, Author 📚, ex-Microsoft MVP 🕸, Blogger 💻, Software Engineering at Deliveroo 🍜, F1 fan 🏎, Loves travelling 🛫
I live in London, UK 🏡
