Even if you know the most optimal solution in terms of computational complexity, it might not be the best thing to put into your code base. There are a lot of o

Even if you know the most optimal solution in terms of computational complexity, it might not be the best thing to put into your code base. There are a lot of other things to balance including (but not limited to) readability, maintainability, probability of correctness, and of course developer time. Considering these multiple dimensions is essential to good engineering. I'm not saying you shouldn't know the best algorithms for a problem, as this article clearly demonstrates the effectiveness of a more efficient solution. In fact, having better understanding of algorithms and computational complexity makes it safer for you to accurately assess the trade-offs you'll be making by picking slower but simpler code or faster code with more complexity. There is more to consider than just big-O when writing software. Note: What I'm saying most strongly applies to software with functionality that doesn't exist yet. If there's a reliable library with what you're seeking (such as a way to generate primes), it's usually best to use it.