The code smells bad. Let’s see how to change the aromas. In this series, we will see several symptoms and situations that make us doubt the quality of our developments. We will present possible solutions. Most of these smells are just hints of something that might be wrong. They are not rigid rules.
Code Smell 01 — Anemic Models
Your objects are a bunch of public attributes without behavior.
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Protocol is empty (with setters/getters).
If we ask a domain expert to describe an entity he/she would hardly tell it is ‘a bunch of attributes’.
Problems
Solutions
- 1) Find Responsibilities.
- 2) Protect your attributes.
- 3) Hide implementations.
- 4) Delegate
Examples
- DTOs
Sample Code
Wrong
Right
Detection
Detection can be automated with sophisticated linters ignoring setters and getters and counting real behavior methods.
Also Known as
- Data Class
Tags
- Anemic
- OOP as Data
- Encapsulation
- Setters/Getters
- Mutability
More info:
- Wikipedia
- Refactoring Guru
- Nude Models — Part I : Setters
- Nude Models — Part II : Getters
- How to Decouple a Legacy System
Code Smell 02 — Constants and Magic Numbers
A method makes calculations with lots of numbers without describing their semantics.
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Problems
- Coupling
- Low testability
- Low readability
- Repeated Code
Solutions
- 1) Rename the constant with a semantic and name (meaningful and intention revealing).
- 2) Replace constants with parameters so you can mock them from outside.
- 3) The constant definition is often a different object than the constant (ab)user.
Examples
- Algorithms Hyper Parameters
Sample Code
Wrong
Right
Detection
Many linters can detect number literal in attributes and methods.
Tags
- Hard coded
- Constants
- Repeated Code
More info
Code Smell 03 — Functions Are Too Long
Humans get bored beyond line 10.
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Problems
- Low Cohesion
- High coupling
- Difficult to read
Solutions
- 1) Refactor
- 2) Create small objects dealing with some of the tasks. Unit test them.
- 3) Compose methods
Examples
- Libraries
Sample Code
Wrong
Right
Detection
All linters can measure and warn when methods are larger than a predefined threshold.
Also Known as
- Long Method
More info
Tags
- Complexity
Code Smell 04 — String Abusers
Too many parsing, exploding, regex, strcomp, strpos and string manipulation functions.
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Problems
- Complexity
- Readability
- Maintainability
- Lack of Abstractions
Solutions
- 1) Work with objects instead.
- 2) Replace strings with data structures dealing with object relations.
- 3) Go back to Perl :)
- 4) Find Bijection problems between real objects and the strings.
Examples
- Serializers
- Parsers
Sample Code
Wrong
Right
Detection
Automated detection is not easy. A warning can be issued if too many string functions are used.
Relations
- Primitive Obsession
Tags
- Mapping
Code Smell 05 — Comment Abusers
Code has lots of comments. Comments are coupled to implementation and hardly maintained.
- Maintainability
- Obsolete
- Documentation
- 1) Refactor methods.
- 2) Rename methods to more declarative ones.
- 3) Break methods.
- 4) If a comment describe what a method does, name the method with this description.
- 5) Just comment important designs decisions.
- Libraries
- Class Comments
- Method Comments
Photo by Volodymyr Hryshchenko on Unsplash
Problems
Solutions
Examples:
Sample Code:
Wrong
Right
Detection:
Linters can detect comments and check the ratio comments / lines of code against a predefined threshold.
More info
Tags
- Comments
- Declarative
To be continued...
How to Find the Stinky Parts of Your Code (Part II)
How to Find the Stinky Parts of Your Code (Part III)
How to Find the Stinky Parts of Your Code (Part IV)
How to Find the Stinky Parts of Your Code (Part V)
… and many more to come.
Smells are certain structures in the code that suggest (sometimes they scream for) the possibility of refactoring.
Martin Fowler
Part of the objective of this series of articles is to generate spaces for debate and discussion on software design.
We look forward to comments and suggestions on this article.
