Code Simplicity

The Singular Secret of the Rockstar Programmer

Before all the laws of software, before the purpose of software, before the science of software design itself, there is a singular fact that determines the success or failure of a software developer. This fact makes the difference between the senior engineer who can seem to pick up new languages in a day and the junior developer who struggles for ten years just to get a paycheck, programming other people’s designs and never improving enough to get a promotion. It differentiates the poor programmers from the good ones, the good programmers from the great ones, and the great ones from the “rockstar” programmers who have founded whole multi-billion dollar empires on their skill.

It’s not anything complicated, and it’s not something that’s hard to know. It’s not something that you can only do if you’re born with a special talent or a “magical ability to program well.” There is nothing about the nature of the individual that determines whether or not they will become an excellent programmer or a poor one.

There is only one, singular fact:

The better you understand what you are doing, the better you will do it.

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The Engineer Attitude

The attitude that every engineer should have, in every field of engineering, is:

I can solve this problem the right way.

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How We Figured Out What Sucked

So, after my last post, a few people asked, “Okay, but how do you figure out what sucks?”

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The Secret of Success: Suck Less

When I started working on Bugzilla in 2004, it was a difficult time for the whole project. There were tremendous problems with the code, we hadn’t gotten a major release out in two years, and a lot of the main developers had left to go do paid work.

But eventually, thanks to a bunch of new members in the Bugzilla community, we released Bugzilla 2.18. Hooray! Bells rang, birds sang, and there was much rejoicing.

However, in the space between Bugzilla 2.16 (which was before my time) and Bugzilla 2.18 (which was the first release that I helped get out), something very strange happened–we developed serious competition. All of the sudden there were a bunch of new bug-tracking systems, some of them open-source and some of them not, that people were actually using.

At first it wasn’t too worrisome. Bugzilla was pretty dominant in its field, and it’s hard to lose that kind of position. But as time went on, there was more and more competition, and some people were predicting doom and gloom for Bugzilla. We were a tiny group of completely unpaid volunteers, and some of these competing products were being made by companies whose marketing and development resources absolutely dwarfed us.

And yet, with every release, our download numbers kept going up. And always significantly–30-50% more than the previous release, every time.

And then we hit Bugzilla 3.0, and our download numbers nearly doubled. And they’ve kept going up with every release from there. Nowadays we get over 10 times the number of downloads per release that we did in 2004.

So how did we pull this off? Well, as far as I can tell:

All you have to do to succeed in software is to consistently suck less with every release.

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“Consistency” Does Not Mean “Uniformity”

In a user interface, similar things should look the same. But different things should look different.

Why do over 75% of Facebook’s users think that the new Facebook UI is bad? Because it makes different things look similar to each other. Nobody can tell if they’re updating their status or writing on somebody else’s wall, because even though the text is slightly different in the box depending on what you’re doing, the box itself looks the same. The new Chat UI (introduced a few days ago) makes idle users look basically identical to active users, except for a tiny icon difference. (It’s also important that different things are different enough, not just a little different, because people often won’t notice little differences.)

This is an easy pitfall for developers to fall into because developers love consistency. Everything should be based on a single framework, in the backend of an application. But that doesn’t mean that everything has to be displayed the same in the UI.

This fact–that different things should look different–is actually true with code, too, but people rarely think about it, because developers are actually pretty good about it. For example, accessing a value of an object should look different than calling a method on it, and in most programs, it does. For example, in Bugzilla’s code, accessing a value on an object looks like $object->value whereas calling a method on the object looks like $object->method(). It’s not all that different, but the () at the end is enough difference for the average programmer to notice “Oh, that’s a method call that does something–it’s not just accessing a value in the object.”

All in all, consistency is really important in both the backend and the frontend of an application. But that doesn’t mean that every single thing should look exactly the same–if we took that to extremes, we’d just have a solid white page, and that doesn’t seem all that usable (frontend) or readable (backend), does it?


Features, Simplicity, and the Purpose of Software

One of the best ways to keep an app simple is, of course, to limit how many features you implement. Twitter, for example, has very few features, but is enormously successful. The limited number of features of Twitter make it really easy to keep the application simple, which lets the developers focus a lot on the quality of the system, the polish of each individual feature, etc.

Twitter’s just one of the many proofs that you don’t have to have lots of features to be successful. In fact, many successful apps have fewer features than their less-successful competitors.

Still, you’ve got to have some features. 🙂 After all, it’d be pretty silly to be programming, otherwise. But how do you decide which features you should have? Is it just up to the Chief Architect’s intuition, or how many users demand that you give them “feature X”? Does whoever shouts the loudest in the development meeting get their feature implemented first?

Well, no, there is a way to decide whether or not you should implement a feature, and it comes out of one of our most basic principles: the purpose of software. This principle (that the purpose of software is “to help people”) isn’t just some fancy-sounding gibberish I made up to make myself happy–I wrote it because it’s something that can actually be really useful to think about in everyday programming, and this question of “Should we implement this feature?” gives us a great opportunity to show how it can be applied. Continue reading


(I)SAR Clarified

In my previous post, I said that there are three major parts to any computer program: Structure, Action, and Results. Also, a program has Input, which could be considered a fourth part of the program, although usually it’s not the programmer who’s creating the input, but the user. So we can either abbreviate this as SAR or ISAR, depending on whether or not we want to include “Input.”

Now, some people misunderstood me and said, “Oh, SAR is just another name for MVC.” No, I used MVC as an example of SAR, but SAR is a much, much broader concept than MVC–they are not comparable theories. MVC is a pattern for designing software, whereas SAR (or ISAR) is a statement of the three (or four) components that are present in all software.

The fascinating thing about SAR is that it applies not only to a whole program, but also to any piece of that program. A whole program has a Structure, just as a function or single line of code has a Structure. Same for Action and Results.

Here’s a little more about each of the pieces, and some examples to help explain:


Here are some examples of things that would be considered “Structure” for the whole program: Continue reading


Structure, Action, and Results

There’s a very popular model for designing software that we’ve all heard of if we’re web developers, and probably most desktop developers have heard of too: our old friend MVC. This works well because it reflects the basic nature of a computer program: a series of actions taken on a structure of data to produce a result. Programs also take input, and so you could possibly argue that input was a fourth part of a program, but usually I just think of a computer program as the first three parts: Structure, Action, and Results.

In the MVC sense, the Model is the Structure, the Controller is what does the Actions, and the View is the Result. I think the analogy (and the words) Structure, Action, and Results are more widely and accurately applicable to the operation of every program in existence, though, moreso than MVC, though MVC is a perfectly good way of looking at it for GUI applications.

Really, Structure, Action, and Results probably describes almost any machine in existence. A machine has some parts that don’t move, a framework–that’s the structure. Some parts move and do something–that motion is the action. And of course the machine produces something (otherwise we wouldn’t care much about it) so that’s the result.

Computer programs are unusual machines in that they can modify their own structure. However, it’s important that some part of the program be stable, that they “not move” in a logical sense. The way that object classes relate to each other, the names of methods and variables–these are all parts of the structure that usually don’t change while you’re running. (Sometimes you make new classes, methods, or variables while you’re running, but they usually follow some pre-set plan, so there’s still a lot of “not moving” involved.)

When I’m writing software, I usually build the Structure first, then I work on the Actions, and then I work on the displaying of the Result. Some people work backwards from the Results, that’s fine too. Probably the only inadvisable thing to do is to start with the Actions, since it’s kind of confusing to be performing Actions without a Structure and with no defined Result.

There’s so much to this concept that I could probably write a whole book just on this one topic, but I think this is a decent introduction, and I’m sure that given this, you can think of lots of other useful applications of it.


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Simplicity and Security

A big part of writing secure software (probably the biggest part) is simplicity.

When we think about software security, the first question that we ask is, “How many different ways could this program possibly be attacked?” That is, how many “ways in” are there? It’s a bit like asking “How many doors and windows are there on this building?” If your building has 1 exterior door, it’s very easy to protect that door. If it has 1000, it will be impossible to keep the building secure, no matter how good the doors are or how many security guards you have.

So we need to limit the “ways in” to our software to some reasonable number, or it won’t ever be secure. That’s accomplished by making the overall system relatively simple, or breaking it down into very simple and totally separate component parts.

Then, once we’ve limited the ways in, we need to start thinking about “How many different possible attacks are there against each way in?” We limit that by making the ways in themselves very simple. Like a door with only one unique key, instead of a door that can take five different keys, all of which individually will open the door.

Once that’s done, we limit how much damage any attack could do if it got through. For example, in a building, we’d make any given door only allow access to one room.

All of this explains, for example, why Windows is fundamentally flawed and will never be secure, and why UNIX-based systems have a better reputation for security. Continue reading


What Is A Computer?

What is a computer? You’d think that would be a fairly simple question. After all, I’m using one to type this up, I ought to know what it is, right? I mean obviously, it’s a…computer! I mean, it’s got a keyboard, and a monitor, and there’s that box down there…

But what is it that makes all that stuff a computer? Why do we look at it and go, “Oh yeah, that’s a computer,” as opposed to, say, “Oh, that’s just a TV,” or “That’s where I keep the leprechauns at night.”?

Some people try to define the word “computer” just by saying “it’s got such and such parts and they all work this way,” but that’s like saying “airplanes have two wings and jet engines.” It’s true, but I could build an airplane that didn’t have two wings or jet engines. The way something works is not a definition for that thing.

Others try to define it mathematically, but that can also be somewhat limiting, because then only the devices that fit into your mathematical scheme are computers, and there are multiple mathematical models that would all be considered “computers.”

So I turned to the dictionary. That was fun for me–I’m a dictionary fanatic. I’ve got lots of great dictionaries, and there are even more online. The Compact Oxford English Dictionary had the best definition, as it turned out.. I was very happy with it at first, but when I started to think about it, it didn’t quite work. For example, it calls computers “an electronic device,” and we know that computers can be built without electronics.

So I worked to come up with a definition of my own. Strangely enough, the key question that it boiled down to was “Why is a player piano not a computer?” It “processes information” by playing notes from its roll. If you gave it an etching machine, it could “store information” back on to the roll. But despite all that, it’s clearly not a computer. What is a computer doing that is fundamentally different from a player piano, that a player piano could never do? Continue reading