In October 2020 I asked Tomáš Votruba, the mastermind behind Rector, if we could have a little chat about this tool. I wanted to learn more about it and had spent a couple of days experimenting with it. Tomáš answered all my questions, which was tremendously valuable to me personally. When this happens I normally feel the need to share: there should be some kind of artefact that can be published, so others can also learn about Rector and how to extend it based on your own refactoring needs.

I recently heard this interesting question: if your project uses a static analysis tool like PHPStan or Psalm (as it should), should the tests by analysed too?

The first thing to consider: what are potential reasons for not analysing your test code?

Why not?

1. Tests are messy in terms of types

Tests may use mocks, which can be confusing for the static analyser:

$object = $this->createMock(MockedInterface::class);

The actual type of $object is an intersection type, i.e. $object is both a MockObject and a MockedInterface, but the analyser only recognizes MockObject. You may not like all those warnings about “unknown method” calls on MockObject $object so you exclude test code from the analysis.

This article is an excerpt from my book Advanced Web Application Architecture. It contains a couple of sections from the conclusion of Part I: Decoupling from infrastructure.

This chapter covers:

• A deeper discussion on the distinction between core and infrastructure code
• A summary of the strategy for pushing infrastructure to the sides
• A recommendation for using a domain- and test-first approach to software development
• A closer look at the concept of “pure” object-oriented programming

Core code and infrastructure code

In Chapter 1 we’ve looked at definitions for the terms core code and infrastructure code. What I personally find useful about these definitions is that you can look at a piece of code and find out if the definitions apply to it. You can then decide if it’s either core or infrastructure code. But there are other ways of applying these terms to software. One way is to consider the bigger picture of the application and its interactions with actors. You’ll find the term actor in books about user stories and use cases by authors like Ivar Jacobson and Alistair Cockburn, who make a distinction between:

A lot can happen in 9 years. Back then I was still advocating that you should unit-test your controllers and that setter injection is very helpful when replacing controller dependencies with test doubles. I’ve changed my mind: constructor injection is the right way for any service object, including controllers. And controllers shouldn’t be unit tested, because:

• Those unit tests tend to be a one-to-one copy of the controller code itself. There is no healthy distance between the test and the implementation.
• Controllers need some form of integrated testing, because by zooming in on the class-level, you don’t know if the controller will behave well when the application is actually used. Is the routing configuration correct? Can the framework resolve all of the controller’s arguments? Will dependencies be injected properly? And so on.

The alternative I mentioned in 2012 is to write functional tests for your controller. But this is not preferable in the end. These tests are slow and fragile, because you end up invoking much more code than just the domain logic.

Where should it go?

If you’re one of those people who make a separation between an application and a domain layer in their code base (like I do), then a question you’ll often have is: does this service go in the application or in the domain layer? It sometimes makes you wonder if the distinction between these layers is superficial after all. I’m not going to write again about what the layers mean, but here is how I decide if a service goes into Application or Domain:

This is an excerpt from my book PHP for the Web. It’s a book for people who want to learn to build web applications with PHP. It doesn’t focus on PHP programming, but shows how PHP can be used to serve dynamic web pages. HTTP requests and responses, forms, cookies, and sessions. Use it all to build a CRUD interface and an authentication system for your very first web application.

Chapter 11: Error handling

As a rather unusual pastime for the Saturday night I attended the third Domain-Driven Design Africa online meetup. Thomas Pierrain a.k.a. use case driven spoke about his adaptation of Hexagonal architecture. “It’s not by the book,” as he said, but it solves a lot of the issues he encountered over the years. I’ll try to summarize his approach here, but I recommend watching the full talk as well.

Hexagonal architecture

Hexagonal architecture makes a distinction between the use cases of an application, and how they are connected to their surrounding infrastructure. Domain logic is represented by pure code (in the FP sense of the word), surrounded by a set of adapters that expose the use cases of the application to actual users and connect the application to databases, messages queues, and so on.

You’ve picked a good refactoring goal. You are prepared to stop the project at anytime. Now how to determine the steps that lead to the goal?

Bottom-up development

There is an interesting similarity between refactoring projects, and regular projects, where the goal is to add some new feature to the application. When working on a feature, I’m always happy to jump right in and think about what value objects, entities, controllers, etc. I need to build. Once I’ve written all that code and I’m ready to connect the dots, I often realize that I have created building blocks that I don’t even need, or that don’t offer a convenient API. This is the downside of what’s commonly called “bottom-up development”. Starting to build the low-level stuff, you can’t be certain if you’re contributing to the higher-level goal you have in mind.

Refactoring is often mentioned in the context of working with legacy code. Maybe you like to define legacy code as code without tests, or code you don’t understand, or even as code you didn’t write. Very often, legacy code is code you just don’t like, whether you wrote it, or someone else did. Since the code was written the team has introduced new and better ways of doing things. Unfortunately, half of the code base still uses the old and deprecated way…

Refactoring projects

A common case of refactoring-gone-wrong is when refactoring becomes a large project in a branch that can never be merged because the refactoring project is never completed. The refactoring project is considered a separate project, and soon starts to feel like “The Big Rewrite That Always Fails” from programming literature.

The work happens in a branch because people actually fear the change. They want to see it before they believe it, and review every single part of it before it can be merged. This process may take months. Meanwhile, other developers keep making changes to the main branch, so merging the refactoring branch is going to be a very tedious, if not dangerous thing to do. A task that, on its own, can cause the failure of the refactoring project itself.