Month: June 2019

Introduction Big O is all about saving time and saving space, two resources that computer algorithms consume to do repetitive jobs (like sorting strings, calculating sums, or finding primes in haystacks). Big O analysis is required when data points grow very numerous. If you need to sort thousands, millions, billions, or trillions of data points […]