TLDR — A Linear search cycles through an array from start to finish whilst a binary search breaks the array into halves and does a half-interval search. If the variable is not found it breaks the array into another half based upon with its position being too high or too low relative to the search topic, as seen below. In general a binary search is much faster for large arrays.

Have a look at this gif below:

Linear Search

A linear search makes more sense in specific circumstances:

• If your array is guaranteed to be small. There’s not much sense in having…

The TLDR — Big O Notation takes a look at how an algorithm scales.

As the size of the data set increases, how does the algorithm speed change?

The idea of Big O notation was best understood by me in story form, in 2009 a Cape Town homing pigeon called Winston, made history by beating an ISP by delivering 4GB of data 75km, in just 2 hours 6 minutes and 57 seconds, During the same time, the ADSL line had sent just 4% of the data.

Big O notation looks at the amount of time something takes verse the volume of data it has

Listed below are a different scenario

O(1)

So it takes the pigeon just as long to carry 8GB of data as it does 4GB this…

Traditional CPU’s process tasks in a synchronous order one operation after another, this was enhanced by multi-threaded CPU’s, most PC's today have multiple cored CPU’s. The exception to this is Quantum computing but this isn’t in the scope of this post and as of now is not working.

Multi-threaded CPUs enable the CPU to handle multiple problems at once increasing the performance of the PC.

Due to this ‘code’ is synchronous by nature as it is run by the CPU, in Javascript you give an instruction, that instruction goes to the ‘Call Stack’. …