I’ve been teaching game programming at the University of Darmstadt for a couple years now: as they say, teaching something helps you clarifying it in your head. They also say that who can do something does it, who can’t teaches it Smile

Last week I called two “volunteers” as usual to write some code at the main computer in front of the rest of the class, gave them some freedom to choose a solution for a little problem we were having in our XNA game. The solution they came up with was good and, then, they generalized it, writing some more code, and then some more code, and then a little bit more code.

I asked why.

We might need it later

I replied.

So next weekend you want to go to Berlin, spring is finally coming, time to enjoy a bit of sun, it won’t last long here in Germany. You evaluate all the available options, you may take the train (even if they are so expensive here), or go by plane which is not much more expensive than the train and takes less time, or rent a car which would give more freedom but costs a bit more. You discuss it among yourselves for a while, weighing pros and cons against the cost of each option; the train will be around 200 euro per person, same as the a plane ticket, while renting a car would cost around 100 euro per day plus petrol. You finally choose and you buy a car for 5.000 euro. Why? You might need it later. Maybe you will like Berlin so much that you want to travel there every weekend, or you will need the car to go to Amsterdam instead, or even Or maybe you will not do anything like that, and you will spend ten times more now to go to Berlin than if you just hopped on a train…


here). In software we usually take the alternative route, we might need it later, we are willing to spend more now for something that more often than not we will not need later. We do it so often that we gave it a name: Over Engineering.

I believe that this peculiar behavior stems from the fact the cost associated to each line of code we write is not directly evident, it’s not money leaving our pockets. It’s also difficult to estimate precisely, which leads to the false perception that generalizing a solution will actually save time. It will not. Each line of code has a cost over time in terms of maintenance and added complexity, that is paid by the team day after day: if it doesn’t solve a problem that we have now, it’s a sunk cost. It requires a huge amount of experience to foresee that “we might need it later” is actually going to be true, and it also requires having gone through the same problem at least few times, which is not always the case in our Industry: we are on the bleeding edge of technology, uncharted territory, where things are complex by nature. Adding more complexity that is strictly needed is not going to help our cause.

Half jokingly with my students, I showed how they could solve the problem with half the number of lines of code, which will probably mean something like half the number of bugs at the end of the project if the idea is applied consistently.

You Aren’t Gonna Need It