Reflecting architecture and domain in code

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

When creating an application, the easy part is to build something that works. To build something that has performance despite handling a massive load of data, that is a bit more difficult. But the greatest challenge is to build an application that is actually maintainable for many years (10, 20, 100 years).

Most companies where I worked have a history of rebuilding their applications every 3 to 5 years, some even 2 years. This has extremely high costs, it has a major impact on how successful the application is, and therefore how successful the company is, besides being extremely frustrating for developers to work with a messy code base, and making them want to leave the company. A serious company, with a long-term vision, cannot afford any of it, not the financial loss, not the time loss, not the reputation loss, not the client loss, not the talent loss.

Reflecting the architecture and domain in the codebase is fundamental to the maintainability of an application, and therefore crucial in preventing all those nasty problems.

Explicit Architecture is how I rationalise a set of principles and practices advocated by developers far more experienced than me and how I organise a code base to make it reflect and communicate the architecture and domain of the project.

In my previous post, I talked about how I put all those ideas together and presented some infographics and UMLish diagrams to try to create some kind of a concept map of how I think of it.

However, how do we actually put it to practice in our codebase?!

In this post, I will talk about how I reflect the architecture and the domain of a project in the code and will propose a generic structure that I think that can help us plan for maintainability.

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More than concentric layers

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

In my previous post in this series, I published an infographic that reflects the mental map I use to figure out the relationships between the code units types.

However, there was something that I always felt it was not very well reflected there, but I just didn’t know how to do it any better: the shared kernel.

Furthermore, I figured out a few more things, and I’m gonna write about it all in this post!

Continue reading “More than concentric layers”

Service Oriented Architecture (SOA)

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

The SOA Style has been around since the late 1980s and has its origins in ideas introduced by CORBA, DCOM, DCE and others. Much has been said about SOA, and there are a few different implementation patterns but, in essence, SOA focuses on only a few concepts and doesn’t give any prescription on how to implement them:

  • Composability of user-facing applications;
  • Reusable Business Services;
  • Technology stack independent;
  • Autonomy (independent evolution, scalability & deployability).

SOA is a set of architectural principles independent of any technology or product, just like polymorphism and encapsulation are.

In this post I am going to address the following patterns related to SOA:

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From CQS to CQRS

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

When we have an application that is data-centric, ie. implements only basic CRUD operations and leaves the business process (ie. what data to change and in what order) to the user, we have the advantage that the users can change the business process without the need to change the application. In the other hand, this implies that all users need to know all details of all business processes that can be performed using the application, which is a big problem when we have non-trivial processes and a lot of people that need to know them.

In a data-centric application, the application has no knowledge of the business processes, so the domain is unable to have any verbs, and is unable to do anything else aside from changing raw data. It becomes a glorified abstraction of the data model. The processes exist only in the heads of the application users, or even in post-its pinned to the computer screen.

A non-trivial, and really useful, application aims to remove the “process” burden from the user’s shoulders by capturing their intentions, making it an application capable of processing behaviours as opposed to simply storing data.

CQRS is the result of an evolution of several technical concepts that work together to help provide the application with an accurate reflection of the domain, while overcoming common technical limitations. Continue reading “From CQS to CQRS”

Event-Driven Architecture

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

Using events to design applications is a practice that seems to be around since the late 1980s. We can use events anywhere in the frontend or backend. When a button is pressed, when some data changes or some backend action is performed.

But what is it exactly? When should we use it and how? What are the downsides?

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Clean Architecture: Standing on the shoulders of giants

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

Robert C. Martin (AKA Uncle Bob) published his ideas about Clean Architecture back in 2012, in a post on his blog, and lectured about it at a few conferences.

The Clean Architecture leverages well-known and not so well-known concepts, rules, and patterns, explaining how to fit them together, to propose a standardised way of building applications.

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Onion Architecture

This post is part of The Software Architecture Chronicles, a series of posts about Software Architecture. In them, I write about what I’ve learned on Software Architecture, how I think of it, and how I use that knowledge. The contents of this post might make more sense if you read the previous posts in this series.

The Onion Architecture was coined by Jeffrey Palermo in 2008. As I see it, it builds on the Ports & Adapters Architecture by adhering to the idea of placing the domain in the centre of the application, externalising the delivery mechanisms (UI) and infrastructure used by the system (ORM, Search engines, 3rd party APIs, …). But it goes further and adds internal layers to it.

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