Shitlist Driven Development
Recently the team I work with completed a project to allow Shopify to run in multiple datacenters. This project was a refactoring project in disguise. When you undertake large refactoring of a code-base with 100s of developers and 100,000s of lines of code, you can’t align by sending an email. The merge-conflicts a single pull request would entail makes me shiver. When deprecating in a large code-base the only way to reliably avoid new deprecated behaviour is a failing test that tells you what to do. Otherwise the pace that new deprecated code is introduced can easily outpace the speed at which you can remove them, or be a massive source of frustration.
Typically deprecations come in the form of soft warnings: Logging to stderr
,
capital letters and exclamation marks in the documentation, or a legacy prefix
to the method or class name. At the end of the day, everyone needs to get work
done, and if they see a code-path already being used from 10 places in the
code-base despite these soft warnings—it doesn’t seem crazy to introduce
another. However, if another project is blocked on these deprecated code-paths,
piling on may have a large cost.
To solve this problem Florian Weingarten on our team introduced what he calls “shitlists”: a whitelist of deprecated behaviour. Existing deprecated behaviour is OK and whitelisted. New usage of the deprecated API is banned and fails a test with a well-defined error.
They come in many forms, but could look like this:
Shitlist = [
ClassA,
ClassB,
ClassC
]
def push_job_that_does_crazy_things(klass)
if Shitlist.include?(klass)
# Existing deprecated behaviour is called.
else
raise Shitlist::Error, <<-EOS
You're pushing a job that does crazy things. This API has been
deprecated in this code-base. <team> is actively trying to get
rid of this code-path, because
<reason>. We suggest you instead do <alternative>. If you have questions, please
ping <team>.
EOS
end
A shitlist could be something as simple as a git grep
for a certain code-path:
test "no new introductions of legacy code path" do
actual = `git grep some_legacy_method_with_a_unique_name`
assert_equal 321, actual
end
Other times you can reach into another API and get a count or shitlist:
RedisShitlist = [
Session,
FragmentCache,
AuthenticationTokens,
]
test "no new redis models introduced" do
assert_equal RedisShitlist, RedisModel.descendants
end
Other ways we’ve used shitlists in the past:
- Make sure that a certain datastore is only read from in a certain context (or not used at all). This would allow for using a read-only slave, or improving resiliency in a certain area.
- Ensure fallbacks for all uses of a secondary data-store. E.g. if you access sessions in Redis and Redis is down, you should be able to still render the page (i.e. have an empty session fallback).
- Shitlisting joins between tables that have no business being joined. This is helpful to keep data-models and scope clean, or separating a part of an application.
If you have a linter for a project, you may be able to encode rules. For example you might use Foodcritic for Chef, or Rubocop for Ruby.
Sometimes the shitlist is quite complicated, and much more domain-specific.
Building the shitlist gives the team responsible for it a number of advantages:
- Strong feedback loop. The goal is to reduce the
Shitlist
to an empty Array and always raise or remove the code entirely. Remove a class from the list, fix the code and the tests, celebrate and move on. - Stopped the bleeding. New deprecated behaviour is not introduced unless the team is contacted or some other action defined in the error is taken.
- Success metric. If you have shitlists for everything that needs to be done for your project, you have metrics that you can track. Every week you can look at how these lists are shrinking. Refactoring for months at a time can be exhausting, but if you see that you’re making progress with metrics moving, it’s much more rewarding.
- Enforces a guarantee. For example, you can have a shitlist that all jobs have a retry mechanism. In that case, you know that you can kill any worker gracefully at any time since the job will retry. Because of 1-3 you know how much work it will take to have this guarantee.
It is important that the shitlist errors are actionable. If you hit the shitlist of another team, you need to know what to do next. Ideally the error explains exactly what you need to do, and no humans need to talk, but reaching out to the owner of the shitlist should always be part of the shitlist.
If you own a shitlist, you must empathize with the problems of everyone who’s running into problems. If you simply deprecate new behaviour and don’t offer an alternative, you will be the source of frustration. If the value of emptying the shitlist far outweighs the value of adding to the shitlist, it may be OK to not offer a direct other solution but ask the person who ran into the error to revise their solution.
It is important that people run into shitlists as early in development as possible. If you run into a shitlist after spending hours implementing your solution, you will be less than popular. Some shitlists may require an entire re-architecting of some teams’ solutions.
Months, in our case more than a year, of refactoring can be overwhelming and unrewarding work. With the strong feedback loop that shitlists introduce you can see the light at the end of the tunnel. You know that nothing is added to the shitlist without you knowing about it.
Creating shitlists in some cases can be extremely difficult. Some take hours to create, others weeks, and in our case one took months to come up with. You’ll have to place the cost of developing the shitlist against the cost of not having it. In some cases logging when you hit a bad code-path may be enough (simple soft warning deprecation) if you assert the risk of new behaviour small and the complexity of introducing the shitlist big.
Delegating with shitlists is great. Due to the tight feedback loop, asking other teams or onboarding new team members becomes much easier. Remove something on the shitlist, fix the code and the tests, then move on. Sometimes during large refactorings you may need other teams with more domain expertise of a certain area of the code-base to help. The shitlist becomes a great rock to point people at.
If you are about to embark on a large refactor, I highly recommend adding shitlists to your toolbox. Your project will look much less daunting when it goes from an opaque objective to a list of shitlists.
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