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Practical Big O Notation for JavaScript Developers
A practical approach to understanding this tool
Big O notation is one of those things we usually learn about when we go through some kind of formal education (i.e college), otherwise the practical aspects of our day-to-day tend to overrun it and leave it as a completely secondary term that we can live without — and many of you do!
With that being said, I still believe there are benefits to understanding this notation at a high level. Quickly understanding the performance implications of an algorithm is not only useful but very practical.
So let’s take a quick look at what Big O notation is and what exactly should you be looking out for.
What is Big O notation?
The Big O notation is nothing more than a mathematical way of describing the complexity and performance of an algorithm.
I refuse to go in-depth into how to calculate the exact expression because honestly, you will likely never need it. Instead, you’ll only be needed the abbreviated version of it, something that will give you an idea of how fast the complexity of an algorithm will grow once the amount of values it needs to work with grows.
