Compulsive automation

Programmers tend to have a disease: we compulsively automate. That is, no matter the task, we are always on the lookout for ways to automate it regardless of how much (or little) we gain by doing so. The problem is that we too often end up with very small, or even negative gains.

Automation can be viewed as a kind of optimization, and everyone knows that optimizing too early can cause problems. Certainly a task shouldn’t be automated unless it will need to be carried out repeatedly and doing so will be costly. However, compulsive automation seems to come in a few other varieties as well.

The first is when so much time is spent on automation that it kills, or disproportionately hinders the overall project. In this case, there might be very good reasons for automating, but the resources to actually carry it out may not exist.

This can happen at the very beginning of a project. Prematurely setting up continuous integration, version control, and a reproducible development environment can, in some cases, prevent a project from getting off the ground. Automation at the “end” of a project can also lead to problems. I personally struggle with this more than any of the others. Deploying an application is a great example.

You’ve got your snazzy new app (or whatever) working and you’re ready to show it to the world. You could set up a snowflake server, but everyone knows that’s a bad idea. So you decide to automate. You then proceed to fiddle around with Chef or Ansible until you run out of steam and never actually deploy anything, or you deploy but never actually make any updates (which would have justified the automation effort).

In the long run, automating deployments is the right thing to do. But when you’re deploying a prototype or a side project the extra time required up-front can hurt your momentum. It doesn’t matter how much theoretical time you’ll save in the future if no one ever sees your work.

A second variety of unwise automation is when automation reduces the burden on the person doing the automating but transfers it to others, sometimes even magnifying it in the process. The implementation of information systems tends to be an ugly business. We often forget that many of the ugliest systems actually seem clean and elegant to their users. Sometimes the price of this elegance is manual effort behind the scenes. This effort can often be eliminated, but doing so usually requires either significant technical investment or the imposition of constraints on end-users. I noticed a great example of this phenomenon on Hacker News the other day (which actually inspired this blog post).

It was revealed that the volunteer who has been (manually) aggregating hiring-related posts for the past four years has decided to step down. Shortly thereafter, a specification for hiring posts was proposed. The spec itself isn’t bad, it tries to split the difference between human- and machine-readability and does a decent job of it. However, it would require anyone who wanted to post a job to read, understand, and follow the spec.

This wouldn’t be a big deal if the same people posted jobs over and over again, but the community discourages posts from recruiters and HR employees. This means that most people who post will only post occasionally, increasing the odds of having to re-learn the spec every single time.

It seems reasonable, given that someone was willing to do the job manually for four years, to assume that the amount of effort involved in aggregating jobs posts is manageable. So a spec would save a relatively small amount of time behind the scenes, but at a large (total) cost on the part of the posters.

To be fair, a spec for hiring posts might make them easier to search, but a couple bullet points with suggestions for how to write an effective job post would solve this problem just as well.

The final problematic form of automation is when the automation itself becomes a larger project than the original task. I think this usually happens because we delude ourselves into believing that the automation project will be “easy”. Even when the automation is fairly straightforward, feature creep can turn a 10 line shell script into a 10,000 line application before anyone even realizes what is happening.

However, this kind of automation isn’t always a bad idea. If the automation tool can be released for use by others, the total time saved across all users may be greater than the time it took to build the solution. We see this dynamic a lot with open source software. Of course the time must still be justified internally, perhaps trading time for goodwill from the community.

So what is to be done? Certainly we shouldn’t stop automating, the benefits are just too great. What we should do is always consider the context in which an automation project exists. We should think explicitly about the benefits of automating and when they will be realized, whether automating will actually put an additional burden on users, and whether the realistic cost of automating is actually worthwhile.

Image credit: XKCD: Automation

Maintenance

I started on a new project last week. I started the way I usually do, with a sketch of how it should work, inputs, outputs, and a general idea of the data flow. Then I did a rough prototype. Progress was pretty fast, partly because the concept is simple, and partly because I wrote something similar for a past employer. After hacking on it over the weekend, I spent yesterday doing “cleanup” to get it ready for actual use. Yesterday afternoon I realized that, despite getting quite a bit done, I felt I had hardly made a dent in my “todo” list for the project.

This made me ponder. I feel as though the speed at which I can complete a given project has fallen since I was a kid. I remember being 13 or so and starting something after dinner, staying up all night, and having a working application in the morning. Has something changed since then? Or is it just my perception or poor memory?

On the one hand, the “quality” of the code I write today is much higher. For instance, when I was a kid I saw no problem with using a text field as the canonical storage for a piece of data. I also remember a lot of deeply nested branching statements and extremely long functions. Code quality certainly explains some of the “slowdown” I perceive.

But there is more to it. I didn’t write crappy code as a kid because I had no choice. In some cases I actually knew better, and I certainly had no shortage of books from which I could have learned the rest. As I thought about my younger self during my walk to the metro station last night I realized that the greatest difference between my younger self and my present self is that my younger self didn’t expect to have to maintain any of the code he wrote. Once it was finished, it was finished, I moved on to the next project (in a way, this reflected the prevailing software release cycle of the time, I’m not sure if that influenced me in any way).

Today, I expect to have to maintain the code I write. Every time I write a line I unconsciously consider whether I’ve just written a check I’ll be asked to cash later. This means I rewrite more lines than I used to, or take longer to write them the first time (more thinking, less coding). It also means that I test and document more.

Oh well, back to (slowly) writing code.