Here's a simple bash script I use to do things to files whenever they change. It takes a command as an argument and runs that command with the name of a changed file. Many times, it's all I need to do continuous testing.

#!/bin/bash
# Requires that the inotify-tools package be installed.
wait_cmd="inotifywait -m -r --format %w%f -e modify ."
filter=$1
shift
cmd="$@"
$wait_cmd | grep --line-buffered $filter | while read file; do 
  clear
  $cmd $file
  date
done

Bill Caputo, through repeated conversations we've had, has convinced me of something very surprising. It was something that changed the way I think about the world, and how I do my job.

There is no such thing as software productivity.

As Martin Fowler observed almost a decade ago, productivity in software cannot be usefully measured. The reason why is it just doesn't exist in The Realm of Relevant Things. Put another way, productivity has no applicability as a metric in software. "How much did we create today?" is not a relevant question to ask. Even if it could be measured, productivity in software does not approximate business value in any meaningful way.

This is because software development is not an activity that necessarily produces anything. Here's a thought experiment: Let's say that you have a couple of developers working on the same project, and by accident, both of them pick up the same task on the same day. The first one, Frank, hauls off and writes a 1000 line framework that solves the problem beautifully. The code is well written, well tested, and the deployment and operation of it is well documented. The second developer, Peter, heads off to to the park for the day, where he thinks about the problem while he feeds the pigeons. Around 4:45, Peter wanders back to the office, deletes 100 lines of code, deploys the change...and the problem is fixed.

Which of these two developers was more "productive" today? The answer is: It doesn't matter. What matters the that Peter solved the problem, while simultaneously reducing long term maintenance costs for the team. Frank also solved the problem, but he increased maintenance costs by producing code, and so (all other things being equal) his solution is inferior. To call Peter more "productive" is to torture the metaphor beyond any possible point of utility.

I would argue that what good software developers do is remove problems. The opposite, in fact, of production. The creation of technological artifacts such as code, documentation, data, etc...are all necessary evils to achieve the goal of removing problems. That's why, sometimes, the most effective solution to a problem is a 5 minute conversation.

To run across a lake, you only have to do one thing: Run fast. The same is true in software development.

Two years ago, I stood on my soapbox and yelled. I told the FP community that their languages were bad, and that they should feel bad. It was a post full of vitriol and frustration, but also a little bit of truth. I believed then (and still do) that functional languages are a poor solution if what you're looking for is a way to get B grade programmers to build scalable, concurrent systems. After trying to learn Erlang, Haskell, and then Scala, I couldn't see how using those languages was easier that just using separate processes, stitched together with message passing infrastructure, to build systems at scale. And with these thoughts running through my head, I vomited on the Internet. Then Hacker News picked it up.

A lot of people I've met don't use the private function definition in Clojure -- which is defn- if you've never seen it. They don't see the point, or they think that private functions in Clojure are dynfunctional (pun!). Based on my use of it so far this year, this confuses me, because I think private functions in Clojure are awesome. The reason I think they're awesome is because I write tests for my code, so that I can refactor. Having a clear deliniation between code the that's tested directly and indirectly means I can refactor much more quickly.

When you're looking for ways to refactor code, you can use your fingers, or you can use your eyes. Refactoring with your fingers is nice. When you have a continuous test runner, running a suite of tests on each change, you can refactor pretty quickly. But refactoring with your eyes is much, much faster. Being able to see possible refactorings and think through them in your head is a much faster way to reason about how to clean up code.

If most of your functions are private, you can refactor with your eyes before you refactor with your hands. Unless you've been doing something dumb like subverting access controls to invoke private functions, you know that all of your private functions can be changed, inlined, extracted, and generally recombobulated without fear of breaking a test or messing with another module. This frees up your mind to think about the code that's right in front of you, rather than worrying about the other code that might be calling it.

The public functions, on the other hand, are expensive to change. You will probably break some clients. You probably break tests. All of this will require a lot of work that, essentially, adds no value on it's own. That's not to say that you shouldn't refactor public functions, of course. It's just that the costs are potentially higher. And I find that too many public functions in a module create a slight reluctance to refactor. A pause in thinking, if you will, that I'd rather do without.

So I love private Clojure functions. They're just new a way to implement an old-fashioned idea: Encapsulation. Clearly dividing my clojure modules into public (more expensive to change) and private (less expensive to change) has worked out very well for me. If you haven't tried it, I suggest that you do.

Unless, of course, you're not writing tests...in which case I have nothing for you!

Things have come a long way since I wrote Continuous Testing in Ruby, Rails, and JavaScript. Lately, for JavaScript, I've been using John Bintz's jasmine-headless-webkit and his complementary guard plugin.

This tool has some really awesome features, not the least of which is that the environment your tests run in is really webkit. That means that you don't have to mock out major parts of the browser environment like window.location, localStorage and sessionStorage, and XMLHttpRequest if you don't want to.

Another great feature is the ability to generate an html file that will run all your tests in a real browser, whenever guard runs tests. Combined with the Live Page plugin for chrome, I get instant feedback about whether or not my Jasmine tests actually pass in the browser.

However, there is one downside compared the node.js technique I outlined in my book. jasmine-headless-webkit doesn't give you real stack traces in the guard output when tests fail. Usually this means you resort to looking at the test failure in the browser (using that generated html file). In practice, it's not a big deal, but it also means you need to make sure your tests pass in both environments, otherwise you might be stuck with a failing test that you can't diagnose.

I released version 0.4 of Jezebel last week. It now works with Node.js 0.6.2.

It's done! It's out. And I couldn't be happier.

As part of writing writing Continous Testing: with Ruby, Rails, and JavaScript, I had the opportunity to talk to a lot of people about what Rod and I were doing, and what they thought of it. Most of the people, once introduced to the idea, thought it was so obviously good that there just wasn't any reason not to follow this practice. By running your tests on every change, you create a tight feedback loop that makes it so much easier to find bugs and get a better understanding of what your code is doing. I'm really proud of what we've done with this book because I think the techniques we discuss in it will really open this practice up to a wide range of developers and projects.

Node.js is supposed to be all about an asynchronous style of programming. Rather than executing functions and getting results, we use a lot of first order functions and callbacks to do things asynchronously. Here's an example of this style from the djangode project. makeApp is a function that takes an array of arrays that are regex/function pairs. Some of those function invoke other functions (such as setTimeout) that take other functions.

I find this kind of code rather tricky to test, and to reason about. Functions nested four levels deep makes my spidey-sense tingle. A good technique for cleaning it up can be extracting those anonymous functions into named functions, but if there are variables that are shared across scopes, that can get a little messy too.

However, I really like Node.js and the approach they've taken, simply because the asynchronous style is a rather elegant (if not new) solution to the kind of performance problems you encounter when working with single threaded code. Blocking operations, IO is particular, can really kill your app, and using threads to avoid blocking can lead to code that is nigh-impossible to test or reason about...so the Node.js asynchronous style merely being a bit tricky is a huge upgrade.

However, I haven't found myself really digging using that style all the time. I generally prefer a functional style when working in JavaScipt. In my opinion, function composition is a huge advantage in JavaScript, but callbacks generally don't have return values, so they're harder to compose. In fact, it really only seems appropriate to use callbacks when I would otherwise be tempted to use a thread to avoid onerous blocking IO. Otherwise, I like to stick a more functional style and stay away from the asynchronous code.

I gotta say, this is pretty neat.

You know, just in case you forget what Huffman encoding is.