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Can inversion of control go awry?

Is there any downside to using inversion of control? Absolutely

Can the testing code become a disaster? Totally

Can you create a big mess of tangled code with inversion of control? Daily

Is it harder to read code that has been “distilled” so that compile time and runtime dependencies are different? Yep

So what is the conclusion? We need to train our brains to think in new ways and build/find tools to help us write code that supports automated testing (and therefore works and can be maintained).

We need to get better at distilling out the un-testable parts. We need to learn how to test more un-testable code. We need to learn better patterns of clearly doing inversion of control. We need to train our brains to think in different ways. We need to keep groping towards a better way of building software.

Distill code to make it testable

I am adding a small module to a big application. If I add the module in the default way it won’t be easy to test. The default way is to simply slap the new code onto the existing app and stir it all together nicely. If I want to test the new code I must run the entire application. And that is hard to do in an automated way.

To make this example concrete, let’s say I need to add table support to a word processor. The default approach is to just start adding code to the word processor code until I have tables working. But when I am done, the “table module” is very tightly integrated with the word processor app.

Here is an alternative approach: There are two kinds of code that are mixed into the new module that must be distilled out. The first, is application specific code. Find all the parts that are specific to this use of the new module and pull them together at the top. This is the common approach of making a library. This involves a bit of abstraction, pulling out constants and other details that apply to the application. So I make a table library and then use that table library in the application.

This part is fairly well understood, if not followed. The second aspect is much less well understood. The second kind of code that must be distilled out is system access code. System access code is any code that goes outside of memory and touches real resources. For example, reading a file, talking on the network, accessing a database, reading the system clock. This is all system access code that is harder to test than normal code.

Just as I distilled the application code out to the top of the new module, I need to distill the system access code out to the bottom of the new module. So imagine different pieces of code working together: the application code is on top (the word processor), making calls down to the new module (the table module), which in turn is calling bits of system access code that are plugged in underneath it.

The final step is to use inversion of control, to allow the application code to pass the system access code into the module. From an object construction perspective this pulls the system access code up on top of the module and puts it under the control of the application. (This point is complicated unless you understand inversion of control. The module still makes calls down to the system access code, but the system access code is constructed by the application code. So there is a runtime dependency from the module to the system access code. But, the system access code implements interfaces defined in the module, so the compile time dependencies are such that the system access code depends on the module, not vice-versa).

With inversion of control in place, I can create fake system access code that is just normal code (i.e. only uses memory, does not access other system resources). This makes it easy to test. For example, suppose the table module in the word processor needs to read a config file to know how many columns to create by default. With the file access code distilled out of the module, I can write simple automated tests that give the module different strings as “config files”.

To do this really well I want to only distill out pure application code and pure system access code. I want the distilled parts to be as small as possible. Why? Because they are going to be harder to test. I am going to put the module under extensive automated testing. So the more code that is in the module, the more code that will be tested. Which means: the more code that will work.

This approach also simplifies the task of automated testing because everything that must be faked for the automated test is gathered together at the top of the library (remember the system access code is “on top” with the application code from a compile time perspective). This means I can have a nice neat bit of code that “fakes” the system access, and then everything below that is the “real” module running.

So, to make my modules testable I need to keep them free of application code and free of system access code. I use inversion of control to allow the application code to control what system access code to use.

10 ways to spot a good coder

Some coders are really good. How can you identify them?

• You gotta know how to read a stack trace. I know this is a pathetically low bar, but I have seen countless developers just stare in wonder at a stack trace. So even this low bar will eliminate a bunch of people.

• Know your tools Know your IDE. Know your editor. Know your operating system. Select the right “power” tools and make them serve you. (An interesting corollary is that if you code on Windows then you have to use Cygwin to be a good developer.)

• Know your language If you have things to say in code, then you need to know how to talk. Learn every part of your language syntax. Get a broad understanding of the libraries your language offers.

• You have to be able to download a 3rd party package, get the source code compiling, make some changes to the source and get the hacked library working. Maybe they even have to use a decompiler to get the source.

• Know how to use a debugger.

• Know how to use a profiler. At some point the code is too slow and you need to know why. A good developer can bust out a profiler and get an answer.

• Read a spec. Sure every developer will read the spec before coding. Good developers read the spec when they are done coding… then they code up all the stuff they missed.

• Read code. Writing code is more fun, but a good developer reads someone else’s code, understand it, and make sensible changes to it.

• Work from the command line. Yeah GUIs are great, but you are doing way too much manual work if you don’t drop down to the command line and script out what you need.

• Create the build script It’s easy to find a good developer on a project. Find the guy who made the build script. He is the one who actually knows how the stuff works.

So what is the common theme here? The bad developers are faced with something new and they stare in wonder at all the meaningless symbols in front of them. Whether it be a stack trace or someone else’s code, or the confusion of buttons in our tools, or the build script. The good coders are filled with the same wonder, for a moment, but they apply their brain to gain understanding. They dig in, read, understand, learn. Programming is a knowledge business if there ever was one.

Resolio is live

I have been working on Resolio, a web tool for making online resumes. It is now live. Check it out if you want to make a nice looking web resume without a lot of work.

Requirements, people, and monsters (part 4)

The final complex system is the application we build: the system. Over time the system becomes a monster. A monster that threatens the team by causing damage, demanding attention, creating more urgent work, growing out of control, refusing to cooperate, and generally causing pain for the development team. The source code grows into a monster. The running system grows into another kind of monster.

The task is to tame the beast. The monster is supposed to serve the team and the users, not the other way around. We need to get the beast in a cage, tame him, get a bit in his mouth, and steer him where we want. We must make the monster serve people.

Once again, the agile movement shows us many of the key techniques we need. Create automated unit tests around each piece of the system. Create automated end-to-end functional tests that confirm the whole thing works as expected. These tests create a cage that constrains the monster.

Build with an eye to creating visible workings. The system cannot be a black box, it has to show its users what it is doing. The system has to provide useful logging and monitoring. Now people can reason about its behavior rather than making up superstitions to explain the rampages of the beast.

With extensive tests in place the development team has a safety net that emboldens them to keep the design from deteriorating into a big ball of mud. When a coder is working on a piece of code and when they see how terrible the code is they can make it better and count on the tests to help them keep things working. The code base can be steered in the direction of good design. The monster has a bit in his mouth.

Software development projects are dominated by these three complex systems: the requirements, the team, and the application itself. Each one of these offers endless opportunities for learning. Any one of them can run out of control and cause misery. Welcome to the joyful world of software development.