What Is Good Code?

This is the second part of a 3 or 4 part series where I’m formulating my thoughts about an ongoing initiative at MedeAnalytics. I started yesterday with a related post called On Giving Technical Guidance to Others that’s a synopsis of an impromptu lecture I game our architecture team about all the things I wish I’d known before becoming any kind of technical leader. I’ll follow this post up hopefully as soon as tomorrow with my reasoning about why prescriptive architectures are harmful and my own spin on the SOLID Principles.

I’m part of an architectural team that’s been charged with modernizing and improving our very large, existing systems. We have an initiative just getting off the ground to break off part of one of our monoliths into a separate system to begin a strangler application strategy to modernize the system over time. This gives us a chance to work out how we want our systems to be structured and built going forward in a smaller subset of work instead of trying to boil the ocean to update the entire monolith codebase at one time.

As part of that effort, I’m trying to put some stakes in the ground to:

• Ban all usage of formal, prescriptive architectural styles like the Onion Architecture or Clean Architecture because I find that they do more harm than good. Rather, I’m pushing hard for vertical slice or feature folder code organization while still satisfying the need for separation of concerns and decent structuring of the code
• Generally choose lower code ceremony approaches whenever possible because that promotes easier evolution of the code, and in the end, the only truly guaranteed path to good code is adaptation and evolution in the face of feedback about the code.
• Be very cautious about how we abstract database access to avoid causing unnecessary complexity or poor performance, which means I probably want to ban any usage of naive IRepository<T> type abstractions
• Put the SOLID Principles into a little bit of perspective as we do this work and make sure our developers and architects have a wider range of mental tools in their design toolbox than just an easy to remember but hard to interpret or apply acronym developed by C++ developers before many of our developers were even born

The rest of this post is just trying to support those opinions.

First, What is Good?

More on this in a later post as I give my take on SOLID, but Dan North made an attempt at describing “good code” that’s worth your read.

Let’s talk a little bit about the qualities you want in your code. Quite a few folks are going to say that the most important quality is that the code satisfies the business needs and delivers value to the business! If you’ll please get that bit of self righteousness out of your system, let’s move on to the kind of technical quality that’s necessary to continue to efficiently deliver business value over time.

• You can understand what the code is doing, navigate within the codebase, and generally find code where you would expect it to be based on the evident and documented rules of the system architecture.
• The code exhibits separation of concerns, meaning that you’re generally able to reason about and change one responsibility of the code at a time (data access, business logic, validation logic, data presentation, etc.). Cohesion and coupling are the alpha and omega of software design. I’m a very strong believer in evolutionary approaches to designing software as the only truly reliable method to arrive at good code, but that’s largely dependent upon the qualities of cohesion and coupling within your code.
• Rapid feedback is vital to effective coding, so testability of the code is a major factor for me. This can mean that code is structured in a way that it’s easy to unit test in isolation (i.e., you can effectively test business rules without having to run the full stack application or in one hurtful extreme, be forced to use a tool like Selenium). This version of testability is very largely a restatement of cohesion and coupling. Alternatively, if the code depends on some kind of infrastructure that’s easy to deal with in integration testing (like Marten!) and the integration tests run “fast enough,” I say you can relax separation of concerns and jumble things together as long as the code is still easy to reason about.
• I don’t know a pithy way to describe this, but the code needs to carefully expose the places where system state is changed or “mutated” to make the code’s behavior predictable and prevent bugs. Whether that’s adopting command query segregation, using elements of functional programming, or the uni-directional data flow in place of two way data binding in user interface development, system state changes are an awfully easy way to introduce bugs in code and should be dealt with consciously and with some care.

I think most of us would say that code should be “simple,” and I’d add that I personally want code to be written in a low ceremony way that reduces noise in the code. The problem with that whole statement is that it’s very subjective:

The killer problem sometimes being that one dev's well engineered code is another dev's over-complicated code. And one dev's "clean" approach is another dev's "too much magic" https://t.co/f4dsIybX3t

— jeremydmiller (@jeremydmiller) August 3, 2022

Which is just to say that saying the words “just write simple code!” isn’t necessarily all that helpful or descriptive. What’s helpful is to have some mental tools to help developers judge whether or not their code is “good” and move in the direction of more successful code. Bet yet, do that without introducing unnecessary complexity or code ceremony through well-intentioned prescriptive architectures like “Onion” or “Clean” that purposely try to force developers to write code “the right way.”

And next time on Jeremy tries to explain his twitter ranting…

This has inevitably taken longer than I wished to write, so I’m breaking things up. I will follow up tomorrow and Thursday with my analysis of SOLID, an explanation of why I think the Onion/Clean Architecture style of code organization is best avoided, and eventually some thoughts on database abstractions.