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Cover image for Code Smell 122 - Primitive Obsession
Maxi Contieri
Maxi Contieri

Posted on • Originally published at maximilianocontieri.com

Code Smell 122 - Primitive Obsession

Objects are there for the picking. Even the smallest ones.

TL;DR: Use small objects instead of primitive ones.

Problems

  • Code Duplication

  • Small Objects Missing

  • Fail Fast principle violation.

  • Bijection Fault

  • Subset violations: Emails are a subset of strings, Valid Ages are a subset of Real, Ports are a subset of Integers, etc.

  • We spread Logic and Behavior in many places.

  • Premature Optimization.

Solutions

  1. Create Small Objects

  2. Build missing abstractions using MAPPER

  3. Use Value-Objects.

Context

We are very lazy to create small objects.

We are also lazy to separate What and How

We like very much to understand the internals of how things work.

We need to start thinking in a whitebox way and looking at the protocol and behavior of small components.

Sample Code

Wrong

//Samples borrowed with permission from 
//https://towardsdev.com/why-a-host-is-not-a-string-and-a-port-is-not-an-integer-595c182d817c

var port = 8080;

var in = open("example.org", port);
var uri = urifromPort("example.org", port);
var address = addressFromPort("example.org", port);
var path = pathFromPort("example.org", port);
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Right

//Samples borrowed with permission from 
//https://towardsdev.com/why-a-host-is-not-a-string-and-a-port-is-not-an-integer-595c182d817c

const server = Port.parse(this, "www.kivakit.org:8080");
//Port is a smallobject with responsibilities and protocol

let in = port.open(this);
const uri = port.asUri(this);
const address = port.asInetSocketAddress();
const path = port.path(this, "/index.html");
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Detection

[X] Manual

We can automate checks on constructors for small objects missing opportunities.

Tags

  • Primitive Obsession

Conclusion

We need to transform our strings, numbers, and arrays into small objects

Relations

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Credits

Photo by K. Mitch Hodge on Unsplash


Iteration allows us to progressively approach some goal. We can discard the steps that take us further away and prefer the steps that move us nearer. This is in essence how evolution works. It is also at the heart of how modern machine learning (ML) works.

Dave Farley


This article is part of the CodeSmell Series.

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