It smells because there are likely many instances where it could be edited or improved.

Most of these smells are just hints of something that might be wrong. Therefore, they are not required to be fixed per se… (You should look into it, though.)

Previous Code Smells

You can find all the previous code smells (Part i - XXXVII) here.

Let's continue...

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Code Smell 186 - Hardcoded Business Conditions

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You are FTX and your code allows special cases

TL;DR: Don't add hard business rules to your code.

Problems

• Open / Closed Principle Violation
• Hardcoding
• Testability

Solutions

1. Reify the condition.
2. Create configuration options and set the exception on the configuration behavior.
3. Don't use Settings/Configs.

Context

According to , in a recent FTX scandal, there was a hardcoded condition to skip risk controls to its own portfolio. The code was explicit and developers were aware of that rule.

Sample Code

Wrong

if (currentExposure > 0.15 && customer != "Alameda") {
  // Be extra careful not to liquidate
  liquidatePosition();
}

Right

  customer.liquidatePositionIfNecessary(0.15);
  
  // This follows the Tell, Don't ask principle

Detection

• [x]Semi-Automatic

We can search for primary hardcoded conditions (related to primitive types). We might have more false positives than actual problems.

Tags

• Hardcoding

Conclusion

If you make code reviews, pay special attention to this kind of hard coding.

Relations

Code Smell 133 - Hardcoded IF Conditions

Code Smell 29 - Settings / Configs

More Info

Credits

Photo by on

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Computer science inverts the normal. In normal science, you're given a world, and your job is to find out the rules. In computer science, you give the computer the rules, and it creates the world.

Alan Kay

Software Engineering Great Quotes

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Code Smell 187 - If/Else Backwards

The first thing we read after the if the condition is the IF

TL;DR: You have the important else condition on the else.

Problems

• Readability

Solutions

1. Swap the conditions.

Context

It is not as straightforward as it appears to write IF clauses in an elegant manner. There are lots of variants and choices. We need to pay special attention to readability.

Sample Code

Wrong

fun addToCart(item: Any) {
    if (!cartExists()) {
        // Condition is negated
        this.createCart();
        this.cart.addItem(Item);
        // Repeated Code
    }
    else {
        // Normal case is on the else clause
        this.cart.addItem(Item);
    }
}

Right

fun addToCart(item: Any) {
    if (cartExists()) {
        this.cart.addItem(Item);
    }
    else {      
        this.createCart();
        this.cart.addItem(Item);
    }
}   

fun addToCartShorter(item: Any) {
    if (!cartExists()) {
        this.createCart();
    }
    this.cart.addItem(Item);    
}

Detection

• [x]Semi-Automatic

We can find negated expressions on IF conditions and check for this anti-pattern.

Tags

• IFs

Conclusion

We need to read code like prose. Humans read the standard case first and the exceptional one after it.

Relations

Code Smell 51 - Double Negatives

Code Smell 156 - Implicit Else

More Info

Credits

Photo by on

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Beauty is more important in computing than anywhere else in technology because software is so complicated. Beauty is the ultimate defense against complexity.

D. Gelernter

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Code Smell 188 - Redundant Parameter Names

Use contextual and local names

TL;DR: Don't repeat your parameters' names. Names should be contextual.

Problems

• Duplication
• Readability

Solutions

1. Remove the repeated part from the name

Context

When using names, we often miss that words are contextual and need to be read as a whole sentence.

Sample Code

Wrong

class Employee
  def initialize(@employee_first_name : String, @employee_last_name : String, @employee_birthdate : Time)
  end
end

Right

class Employee
  def initialize(@first_name : String, @last_name : String, @birthdate : Time)
  end
end

Detection

• [x]Semi-Automatic

We can check our parameter names and try to find duplication.

Tags

• Naming

Conclusion

Use short and contextual names for your parameters.

Relations

Code Smell 174 - Class Name in Attributes

Code Smell 87 - Inconsistent Parameters Sorting

Credits

Photo by on

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As a rule, software systems do not work well until they have been used, and have failed repeatedly, in real applications.

David Parnas

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Code Smell 189 - Not Sanitized Input

Bad actors are there. We need to be very careful with their input.

TL;DR: Sanitize everything that comes from outside your control.

Problems

• Security

Solutions

1. Use sanitization and input filtering techniques.

Context

Whenever you get input from an external resource, a security principle requests you to validate and check for potentially harmful inputs. is a notable example of a threat.

We can also add assertions and invariants to our inputs.

Even better, we can work with Domain Restricted Objects.

Sample Code

Wrong

user_input = "abc123!@#"
# This content might not be very safe if we expect just alphanumeric characters

Right

import re

def sanitize(string):
  # Remove any characters that are not letters or numbers
  sanitized_string = re.sub(r'[^a-zA-Z0-9]', '', string)
  
  return sanitized_string

user_input = "abc123!@#"
print(sanitize(user_input))  # Output: "abc123"

Detection

• [x]Semi-Automatic

We can statically check all the inputs and also we can also use penetration testing tools.

Tags

• Security

Conclusion

We need to be very cautious with the inputs beyond our control.

Relations

Code Smell 121 - String Validations

Code Smell 178 - Subsets Violation

Code Smell 15 - Missed Preconditions

More Info

Credits

Photo by on

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Companies should make their own enterprise systems as often as network security companies should manufacture their own aspirin.

Phil Simon

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Code Smell 190 - Unnecessary Properties

Stop thinking of data as attributes. They are only needed to back your behavior

TL;DR: Don't focus on accidental properties. You won't need many of them.

Problems

• Anemic Models
• Properties bloating
• YAGNI violation

Solutions

• Create attributes only to support your methods (behavior).

Context

Whenever they want to model a person or an employee, junior programmers or students add an attribute 'id' or 'name' without thinking if they are really going to need them.

We need to add attributes 'on-demand' when there's enough evidence. Objects are not 'data holders'.

Sample Code

Wrong

class PersonInQueue
  attr_accessor :name, :job

  def initialize(name, job)
    @name = name
    @job = job
  end
end

Right

class PersonInQueue

  def moveForwardOnePosition
    # implement protocol
  end
end

Detection

• [x]Semi-Automatic

We can detect unused attributes. But in many cases, we need an excellent designer to validate the actual need.

Tags

• Anemic

Conclusion

Start designing your objects from the protocol. Add attributes only when needed.

Relations

Code Smell 144 - Fungible Objects

Code Smell 01 - Anemic Models

Code Smell 40 - DTOs

Code Smell 109 - Automatic Properties

Credits

Photo by on

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Object thinking focuses our attention on the problem space rather than the solution space.

David West

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5 more code smells are coming soon…