Developing software is a process that involves a lot of repetitious work. Building the code, updating configuration files, creating database change scripts, unit testing, deploying and integration testing are all tasks that are repeated many times during development.

Whatever anyone tells you, none of these tasks are exciting, in fact most of them are tedious and prone to error. That’s why so many developers automate them; if they run correctly once, they’ll keep on doing that. Remember, computers are faster and more reliable than people. Automating these parts of the development process is a solved problem.

Why is it then, that the tests run by so many testers and QA departments are manual?

The overall performance of systems is often an afterthought. Developers spend months building a system, often muttering things like “we have plenty of CPU”, “we can add more servers” or “parallel processing is more trouble than it’s worth” or the even more popular “premature optimization is the root of all evil”. After all, Donald Knuth said that last quote, and he was quoting Sir Tony Hoare, so it must be right!

The quote is correct, it’s just taken out of context.

If you are responsible in any way for the system's production you need to stamp on this attitude quickly, before this complacency turns into the acceptance of mediocrity.

Assuming that you missed your chance to do this, at some stage the system is declared complete because it meets the customer’s functional requirements. It also runs slowly. Pathetically slowly. Maybe users think it has crashed (apparently your system has seven seconds to respond before this occurs) or they are faced with crashes, graphs and charts taking minutes to draw, progress bars, loading screens, “(Not responding)” warnings in window title bars or any of a number of other indications that at least some of your architects and developers are incompetent.

When you ask why the system is slow, you should expect to be told that it’s because “the algorithms are really complex”, “there’s a lot of data to process”, “those graphs/charts take a long time to render” and various other excuses. These statements are almost always, shall we say, inaccurate at best.

So now, in addition to your other problems, you need to make sure the system runs at a reasonable speed. How do you do this?

Prime numbers appear everywhere in science and nature. They're very handy when it comes to solving puzzles as well, so it having a generator would be useful.

Unfortunately .NET doesn't seem to have a usable prime number generator class, and neither does the C++ Standard Library. It seems that if you want one, you need to write one.

Ruby has some quite nice prime generation facilities built in, and as of version 1.9 they're quite fast (for a scriopted language!). It might be worth looking at how the Ruby designers implemented their classes later, and seeing if we can improve on them.

Let's start with the (very) basics. If we want to generate prime numbers, we need a way to check whether a number is prime or not.

We've already seen a simple method for checking whether a particular number is prime. At the moment it's not particularly efficient, but we can improve it later. Now let's look at a way to generate prime numbers.

We'll start with a very old, but reliable method, called the "Sieve of Eratosthenes", or "Eratosthenes Sieve".