When we model

I’ve observed a few levels of modeling (i.e. thinking about a problem and describing it in concepts plus data structures) that software developers do in the wild:

  • structural modeling, describe structure of the problem domain and represent that directly in code, probably using the concepts that your ORM or data layer provide
  • operational modeling, evolving a structural model to include models of the operations and workflows that interact with the structural models
  • deep modeling, evolving an operational model to include language that describes how the model, problem domain, and solution domain interact and describe each other

A structural model is what happens in a “just ship it” culture. If you’re lucky, you might start thinking about an operational model as you convert that just-ship-it app into an ecosystem of services connected by APIs and messaging.

Any of these models could poof into existence at a higher level. That is, a team could pop out an operational or deep model of a system on their first try. This is even more likely if it’s their second or third take on a problem domain.

Some ideas for kinds of even-higher level modeling that high-functioning teams perform: error-case modeling, coordinated system modeling, social modeling, migration modeling.

And, let’s not even speak of metamodeling :P

Raising all boats

It’s easy to complain about PHP. For instance, why didn’t they choose ☃ as their namespace resolution operator?! As a developer with lofty opinions, I’m not a big fan of PHP. To me, it’s an argument against allowing accretion to determine the design of a system. I don’t think it’s controversial to call the PHP language, core library, and ecosystem “inconsistent” and “a matter of curious histories”. A language feature here, a library function there, year over year, and you’ve got a “quaint” design. Yes, those are scare-quotes.

Whenever I feel a big rant about PHP shortcomings approaching, I try remember a few important facets of its success:

  • PHP made programming web applications accessible to lot of people for whom writing CGIs with Perl, Python or Java servlets was overwhelming. Myself included!
  • You still can’t beat the simplicity of PHP’s deployment model: acquire commodity web hosting, upload source files, and done.
  • Due to its accessibility and ease of deployment, a whole new kind of person started building stuff with code. Jason Kottke called part of this Liberal Arts 2.0. Less mathy programming, more craftsy.

Fast forward to today. PHP is still doing fine, though lots of people switched to Ruby or Python many moons ago, depending on personality type. And lots of those have since moved on to other things. The technology hype curve is an overlapping, ongoing thing.


Of those that switched, many ended up with JavaScript, in the guise of browser-side frameworks or server-side Node (and its ilk). I think there’s a huge opportunity here. JS is not without flaws, like PHP. But its sort of backed into really broad reach. Embedded, games, applications, mobile, probably more that I don’t even know about. That could make it compelling for an even less math-y demographic of people building stuff with computers.

And yet, there is no single JS community. There’s browser people, there’s server people. The future may hold mobile, gaming, and device people. That creates dissonance and some uphill battles.

But maybe that’s the really cool part. The JavaScript communities will have to slog uphill a bit to make accessible the previously intimidating domains of mobile apps, games, and embedded software. And that could raise the boat for people who aren’t building web apps but could be building software.

Functions about nothing

The tricky thing about decomposing code into abstractions is you end up with “functions about nothing”. You’ve probably seen on of these: a method or function with really vague names glommed into a utility or enumerations junk drawer. It’s probably innocuous, but as you’re reading code, it takes you out of your flow and forces you to think in the abstract instead of the concrete.

It’s easy to guess how these things happen. Successive refactoring iterations end up pulling business logic into a pile of predicates and side-effects and separate pile of abstractions. We feel pretty good ourselves at the end of the refactoring and write a fancy blog post about it!

The rub is when we come back to read the code later. Its easy to find the abstraction first and get side-tracked by figuring out why it exists, the context in which it was created, and when we might use it again. This is better than predicates and side-effects interwoven. But it’s still a problem.

I don’t have a salve for this. I just wanted to put the phrase “functions about nothing” on the internet. [SLAP BASS OUTRO RIFF PLAYS HERE]

It’s not your fault if your tools confuse you

I. Pet Peeve #43: Complaining About Frameworks

The whole point of a framework is that you trade one or more axes of freedom in how you structure your program so that you can move faster writing the meaningful (unique) part of that program. To wit, the first definition I learned of a framework goes something like:

A framework is a library that takes over the main() function of your program and provides a higher-level entry point for calling your code.

Most programs would have a boring main() anyway, so this is a great tradeoff in most cases.

And yet:

  • Some programs aren’t boring.
  • Some programs demand more control.
  • Some developers crave choice and accept the burden of picking each library and choosing how to wire them together.
  • There’s a bit of a hero complex about rolling your own framework from libraries.

Where we end up is that I notice people complaining about frameworks. I think most of these are proxy complaints about someone else choosing a framework they have to live with. To their credit, some complainers are actively trying to make a better thing too. Kudos to them. To the idle complainers: cut it out.

2. I complain about a framework

RSpec and minitest are both frameworks in the sense that your entry point is a special class with special methods. RSpec is more frameworky in that you don’t actually write classes or methods. You use a language-y DSL to define test cases that share some aspect of scope. You can go pretty crazy in this manner. Or you can not go crazy, RSpec accomodates either style.

Lately I’ve been wrestling with test cases written using at least three kinds of RSpec scope and it’s driving me a little crazy. They look something like this:

describe "POST /something" do
  before do
    @thingy = somethings(:alices)
    post :something, thingy: thingy
  end
  
  it { expects(assigns[:something].attributes).to eq(@thingy) }
  it { is_expected.to render(:created) }
  it { is_expected.to respond_with(:json) }
end

If scoping is about answering the question “what methods are available to me on this line of code”, this code seems to have four kinds of scope:

  1. Inside the describe block, we can call RSpec methods
  2. Inside the before block we can call RSpec expectations and rspec-rails controller methods (but that is implicit!)
  3. Inside the it blocks we can call RSpec expectations
  4. When we call is_expected, we can reference…I’m not sure at all

It is at this point I try and take my own medicine and make a constructive observation rather than yelling “this sucks and someone should feel bad about it!” into the wind (i.e. Twitter).

3. What’s an RSpec for?

I didn’t like RSpec at first (circa 2008), then I really liked it (circa 2010), and now I’m sort of ambivalent. The question of what RSpec exists to solve has evolved too. At first it was “hey, BDD!” and then it was a less underscore-y way to build tests and now I think it’s a tool for writing tests in a style that some prefer and some don’t. In short, the Ruby community is figuring this out and kind of storming through the awkward parts.

That awkward part is how I think my example test came to be so unclear. Without doing a deep archaeological dig on the code, I’m guessing this code had three phases:

  1. Originally written according to the RSpec vogue at the time, which was to use it one-liners as forcing function on the constraint that tests should have only one assertion (Which in retrospect I think is a rule about the functionality of the method under test and not a guideline about how to write tests. This isn’t the first time developers have adhered to the letter of the rule and missed the spirit entirely).
  2. Use the amazingly great transpec tool to translate RSpec 2.x style to RSpec 3.x style without having to spend months carefully transitioning a large test suite from one API to another. Mostly this works out great, but you get some awkward translation, like the is_expected part.
  3. Use the newer RSpec 3.x style expect syntax for assertions, introducing two ways to say the same thing with the intended long-term benefit of using the clearer expect style everywhere.

I don’t blame RSpec for any of these phases. You can easily swap out the names of libraries and concepts for any other language or library and find a similar story buried in any chunk of code that’s been around for more than a year and worked on by more than one person. It’s a thing that happens to code. I’m not even sure people should feel bad about it. Mindful of cleaning it up over time, yes. Throw it all in the bin and start over, no.

My first temptation is to say that using it one-liners is a smell. They are nice to scan through but tricky to write and trickier still to change. But I can see where a series of well-intentioned code changes compresses many structurally similar test cases down to nearly-declarative (nearly!) one-liners without much duplicate typing. I can imagine a high-functioning team writing their own matchers, carefully using one-liners, and succeeding. So this one is a word of warning and not a smell.

The real smell, I think, is that its really easy to have very different scopes adjacent to each other in an RSpec test file. Further, not all scope-introducing constructs look the same! describe/context introduce one kind of scope, it introdues another kind of scope, let/subject/before introduce three similar but different kinds of scope, and expects/is_expected look the same but have different scopes as well.

Even smellier is that I’m making this list from an empirical understanding and not by examining the implementation or experimenting with reduced test cases.

What are you gonna do about it?

I’m probably going to leave that code alone. Wait for a muse to strike at the same time I need to make wholesale changes.

People who use RSpec should feel fine about themselves. People who contributed to RSpec should feel great about themselves. People who struggle with figuring out scope in RSpec should take solace that the best of us find this stuff confusing and frustrating at times. Developers not in one of these camps should take my advice, globals are bad but a bunch of weird scoping is not great either. Everyone else can smile and nod.

Organize your Gemfile by function and coupling

Most Gemfiles I see are either unordered (just throw new gems in, wherever!) or alphabetically ordered. A while back, I reordered the Sifter Gemfile, ordering by difficulty of removing the dependency and grouping by functional area. Thus organized, it came out a bit like this:

  • Framework: Rails, Rack, the mysql2 driver, JSON, Rake. We will basically use these forever.
  • Gems for our vendors: Postmark, Braintree, Skylight, Bugsnag. We’ll use these as long as we’re using their respective service.
  • Partner integratons: GitHub, OmniAuth, etc. Most of these aren’t maintained by the partner, and we’d have to drop the integration to drop the gem.
  • Extensions: jquery-rails, delayed-job, will_paginate, etc. We could stop using these if we cared a lot, but we’re pretty committed to them.
  • File uploading: carrierwave, fog, wand, rmagick. We’d have to overhaul our file attachment support if we wanted to remove these.
  • Sphinx support: thinking-sphinx and ts-delayed-delta. We’d have to overhaul our search to remove these.
  • Admin: bootstrap, etc. Things we could easily remove next time we overhaul our admin, which isn’t really a big deal if we decide to.
  • Gems for building assets: jquery-ui-rails, therubyracer, execjs, coffee-rails, sass, compass, etc. We’d have to remove uses of the underlying tool (CoffeeScript, SCSS, etc.) if we wanted to drop one of these.
  • Development gems: pry, ffaker, byebug, better_errors, spring, rack-mini-profiler. We can switch these out if we want.
  • Testing gems: rspec-rails, capybara, etc. Again, if we change tools we can change these.
  • Deployment: capistrano. This could go in the framework section, seems unlikely we’d overhaul our deploy scripts away from Capistrano.

This organization makes it easy to know where to add a new dependency. More importantly, we can better understand how much we depend on a gem and the level of effort to remove it if we need to.

Programming advice for a younger me

How to get better at programming without even programming:

  1. Accept, in your heart and mind, that the languages, libraries, and tools that you use to write programs may not be good for other people, other teams, or other problems.
  2. Search for deeper understanding of approaches to programming that seem strange or incorrect to you. Don’t look for wrongness in what someone else is doing or what you’re thinking.
  3. You will come across scenarios that challenge principles 1) and 2). When you do, say what you can to help but err on the side of not making things worse; let go of what you can’t control.

Bonus: be a kind person.

Leadership, pick a size

Like fast food or coffee at Starbucks, maybe team leadership comes in three sizes.

Extra large leadership. “This is what you’re doing. Make it happen, let me know when it’s done.” The old school, top-down approach. This is what I thought all management was like many moons ago. In my experience this is only useful when people need to think only about what they’re doing, not why they’re doing it or how they do it. Leadership sets the work, lays out the exact process for doing that work, and closely monitors the work as its done. See also: Taylorism.

Large leadership. “Here are some things that need doing. Do one of them, keep me posted.” This is where I think cohesive teams of knowledge workers should aim to be. Leadership lays out the tasks to be done, makes the work to do clear, and gets out of the way. Luckily this is a lot more frequent lately, but probably not so much in part-time labor. Leadership still monitors the flow of work, but not overtly as in Taylorism.

Medium leadership. “Do what you think is most important. Let me know how to remove obstacles.” I suspect most leaders really want to get here, but are constrained, imagined or in reality, by some organizational detail. It’s definitely where I want to be in leadership style. High trust in the team, high trust in the leadership. Lots of unicorn dust.

Oddly enough, I think some teams and projects require large leadership and some require medium leadership. Some people want a little structure to their work, some projects require well-defined milestones to rally around. Other people can effectively guide themselves to useful outcomes, other projects are less about the milestone and more about the journey.

Pick one novelty per project

My pal Brandon Hays and I are fond of noting that projects have a very limited tolerance for the risk of picking a novel technology or approach. Thus, they should intentionally choose one thing to break ground on: database, language, domain model, testing methodology, design paradigm, etc.

Turns out, that’s sort of a thing in social psychology too:

Idiosyncrasy credit is a concept in social psychology that describes an individual’s capacity to acceptably deviate from group expectations. Idiosyncrasy credits are increased (earned) each time an individual conforms to a group’s expectations, and decreased (spent) each time an individual deviates from a group’s expectations.

Turns out this is strongly related to leadership, group expectations, and conformism. That explains a lot of my experience. Those most interested in trying novel approaches are often those who let expectations and conformism take a backseat to trying something new or breaking the mold.

I don’t think this is necessarily good or bad; it’s fine and healthy for a project to choose to vary from the norm in some way. Even better, manage those variances so if things don’t go to plan, you can back them out and keep rolling. But, it doesn’t hurt to consider varying in ways that are likely to yield more “credits” amongst your team.

Teach people to magnify their mind, not write code

Coding is not the new literacy:

When we say that coding is the new literacy, we’re arguing that wielding a pencil and paper is the old one. Coding, like writing, is a mechanical act. All we’ve done is upgrade the storage medium. Writing if statements and for loops is straightforward to teach people, but it doesn’t make them any more capable. Just like writing, we have to know how to solidify our thoughts and get them out of our head. In the case of programming though, if we manage to do that in a certain way, a computer can do more than just store them. It can compute with them.

That is, it’s not enough to write a loop in Ruby, a class in Java, or use a channel in Go. You’ve got to learn way more “material” than that: how to run your code in an application server, how to store rows in a database, how to deploy all your code to another machine. And then: how to have good taste, how to correct oversight, how to avoid bugs! And then, worst of all: knowing all the little miniutae like platform bugs, slow code paths, unstable code, dependency hell.

We shouldn’t put that upon people just because that’s how most programmers interact with computers. We should keep looking to help folks leverage systems as part of their work, not learn how to build systems to leverage systems to do their work.

Hence, the ending:

Alan Kay did a talk at OOPSLA in 1997 titled “The computer revolution hasn’t happened yet,” in which he argued that we haven’t realized the potential that computers can provide for us. Eighteen years later, I still agree with him – it hasn’t happened yet. And teaching people how to loop over a list won’t make it happen either. To realize the potential of computers, we have to focus on the fundamental skills that allow us to harness external computation. We have to create a new generation of tools that allow us to express our models without switching professions and a new generation of modelers who wield them.

We’ve succeeded in magnifying our voices with computers. I like forward to standing back and looking with wonder at how much we’ve magnified our minds.

When software loses its hair

Software’s Receding Hairline:

This is interesting, because the mechanism of growing a comb-over applies to software development. A comb-over is the accumulation of years of deciding that today is not the day to change things. A comb-over is the result of years of procrastination, years of decisions that seem right when you’re in a hurry to get ready for work but in retrospect one of those days should have included a trip to the barber and a bold decision to accept your baldness or take some other action as you saw fit.

A comb-over is a local maximum for improving baldness. You can’t really escape baldness of your head. You can escape a local maximum in your software, if you’re thoughtful about managing tradeoffs between product progress and technical progress.

It would have been better if you hadn’t gone bald in the first place though. Same with software!

(Analogies are just great. Thanks for this one, Reginald.)