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How to Find the Stinky Parts of Your Code (Part I)by@mcsee
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How to Find the Stinky Parts of Your Code (Part I)

by Maximiliano ContieriOctober 27th, 2020
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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.

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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.

Photo by Stacey Vandergriff on Unsplash

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:

Code Smell 02 — Constants and Magic Numbers

A method makes calculations with lots of numbers without describing their semantics.

Photo by Kristopher Roller on Unsplash

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.

Photo by Hari Panicker on Unsplash

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.

Photo by Nathaniel Shuman on Unsplash

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.

    Photo by Volodymyr Hryshchenko on Unsplash

    Problems

    • Maintainability
    • Obsolete
    • Documentation

    Solutions

    • 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.

    Examples:

    • Libraries
    • Class Comments
    • Method Comments

    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.