Thoughts on Software
Big-O is a way of expressing time and space complexity of an algorithm. Complexity is the rate of growth given variable inputs. Complexity is implicitly expressed in worst-case unless otherwise stated.
For example:
function printArray(n) {
for(var i = 0; i < n.length; i++) {
console.log(n[i])
}
}
printArray in this instance is O(n) time complexity and O(1) space complexity.
node.js‘s popularity isn’t without it’s reasons. node.js is lightweight, it’s mature and it has enough packages in the npm repository to make you start wondering if you’ll ever learn enough tools to become a half decent developer.
If you know JavaScript, you just need to know a bit about the node.js event loop and the node.js standard library and maybe express and you’re pretty much a decent node.js developer.
But it’s definitely not without it’s drawbacks.
When laying out your solution, it’s important to have a clear separation between your application and your domain. In most areas that I see, the application is either a Web API or a web application.
What does this actually mean?
During the earlier years of programming, you may think that coding is the most significant part of writing software. Fast-forward to the future, you realise that code isn’t the main problem. It’s the things that happen before and in-between writing code – solving the problem at hand.