Complex testing – the saga

While I’m developing Chlorine, sometimes I need to test multiple specific implementations of lots of really complicated stuff like REPL state, connection, async stuff (as the project is ClojureScript on Node.JS, all I/O treatment is via callbacks) and the complicated nature of rendering multiple different object types on Atom editor. I had multiple regression errors, then I’ve created some “acceptance” tests (these open up a real Atom editor and evaluate commands on it). The problem with these tests should be obvious: they are slow, and I mean REALLY SLOW, and they need a real Atom editor, lots of setups, and because Atom is not really predictable on its actions (sometimes you connect REPL and it changes the focus on the editor) there are lots of unnecessary interactions on the editor just to have less false-negatives.

Now, as I told before, I’m developing Chlorine together with REPL-Tooling, a library that should contain all tooling for any editor capable of running Javascript to run a port or Chlorine. There’s still too much on Chlorine that relies on internal Atom APIs (for example, detection of the beginning and end of forms is one, detection of namespace’s forms is other) but time is passing and more and more is being moved to REPL-Tooling, and as soon as the detection of forms is on REPL-Tooling (and is stable) there should be possible to port most Clojure parts to REPL-Tooling, and then I can think on how to refactor the ClojureScript part, test it, and then Chlorine will be a very easy project to port. Also, as a proof-of-concept there’s Clematis for NeoVIM (it’s still on the very beginning and nothing much happened after I wrote about it here), and also an “electron fake editor” that I’m using as test.

Wait, What?
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To be wrong, even when you’re not

There’s a time when we must assume that we are wrong – even when we are doing the right thing. At my last job, I realized that it was happening with me.

After Nubank, I began to work on a company that, in a way, was a bet in my career – most of the systems in this new company were written in C# (a language that I had never written a single line), there was a huge codebase without a single line of test, the systems did not run on the developer’s machines, and one of the reasons that I was interested in working with then was to organize this codebase, in Clojure, with microservices. Also, to coach the development team, so we would migrate away from monolithic systems to a better architecture, with tests, microservices, and multiple programming languages.

In other words, to apply what I learned at Nubank in this company.

It was a long journey, first to be able to make the code, at least partially, compile on my Linux machine (the default configuration of our development machines was Windows with Visual Studio). And no, there wasn’t simply a matter of swimming against the flow that made me want to work on Linux: it was simply because the mandatory configuration of our Windows workstations was a very slow machine with a very slow antivirus and monitoring systems (to see if anyone was installing pirate software). Also, we had no access to USB, could not download external software, and our antivirus sometimes identified our git blobs as “suspicious software”, effectively corrupting our code every git commit. My machine booted in 10 minutes, and I had to wait another 20 for Visual Studio to be responding (and I’m not faking these numbers).

Then, the migration to Clojure. It wasn’t really that difficult to write the code. The problem was to publish it – the company did not want to use docker, nor containers, nor continuous integration/delivery. We migrated our code from TFS to Bitbucket to GitLab, then to a self hosted GitLab, then back to Bitbucket. Also, we had to fight – a lot – to be able to access our Q/A docker environment, as we had no access to production, staging, or homologation environments. We caught lots of bugs only in production, because we simply had no idea on how the calls for external APIs worked (there was not a single mocked/stubbed external system, and the very few external services that did offer sandboxed environments were so misconfigured that even API versions were different).

Then, after a long fight, more than a year later, we lost.
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Two new libraries in Clojure

Last week, I was looking to some old code I wrote in my last job and my spare time. Then, I’ve decided to publish two new libraries for Clojure and ClojureScript.

One is Paprika, available in Clojars at version 0.1.0-SNAPSHOT.

The other is Check, also available in Clojars (but at version 0.0.1-SNAPSHOT).

The reason for the early publishing is to push forward some simple libraries to fix a simple problem that I had while working with Clojure: the absence of abstractions.
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