1. Overview

Code smells are indicators of potential issues in our code. Kotlin, like any other programming language, has some known code smells that we want to learn to recognize and avoid. In this article, we’ll explore some common Kotlin code smells, how to identify them, and how to address them.

2. What Are Code Smells

Code smells are design issues or patterns that suggest problems in our code. They don’t necessarily translate to bugs, but they highlight areas where our code could be improved in terms of readability, maintainability, and performance.

Code smells can manifest as patterns that violate best practices, reduce code clarity, or hinder extensibility and maintainability.

3. Identifying Code Smells

Code reviews, static analysis tools, and a good understanding of Kotlin best practices can help us spot code smells.

Two common ways to identify code smells are static analysis tools and code reviews.

Static code analysis tools like Detekt and ktlint are designed to identify code smells. These tools can automatically analyze our codebase and provide reports on potential issues. They can catch many common code smells including unused variables, long functions, and nested loops.

Regular code reviews with various teams can help us identify code smells. Developers with different perspectives can spot issues that might be missed by automated tools. It’s crucial to make code reviews part of our development process and focus on identifying and addressing code smells.

4. Common Kotlin Code Smells

Now, we’ll explore some common code smells with examples in Kotlin.

4.1. Long Functions

If a function is too long, it becomes challenging to understand, test, and maintain. While there’s no hard-and-fast rule for the number of lines a function should contain, a good practice is to aim for functions that are small, focused, and do one thing well.

Essentially, to address long functions, we can break them down into smaller, more focused functions. Each function should have a single responsibility. Remember to use meaningful functions and variable names to document the purpose of each piece of code.

Let’s look at an example of a long function:

fun generateReport(data: List<Data>) {
    // Data Manipulation
    val processedData = processData(data)

    // Complex Calculations
    val intermediateResult = complexCalculation(processedData)

    // More Data Manipulation
    val finalData = furtherProcessData(intermediateResult)

    // Additional Complex Calculations
    val finalResult = moreComplexCalculations(finalData)

    // Report Generation
    val report = generateReportFromResult(finalResult)

    // Email the Report
    val emailBody = createEmailBody(report)
    val recipients = getEmailRecipients()
    sendEmail(emailBody, recipients)
}

Let’s see one way to break it up:

fun generateReport(data: List<Data>): String {
    val processedData = processData(data)
    val finalResult = calculateFinalResult(processedData)
    return generateReportFromResult(finalResult)
}

private fun processData(data: List<Data>): ProcessedData {
    // Data manipulation and processing logic
    // ...
    return processedData
}

private fun calculateFinalResult(processedData: ProcessedData): FinalResult {
    // Complex calculations specific to the report
    // ...
    return finalResult
}

private fun generateReportFromResult(finalResult: FinalResult): String {
    // Report generation logic
    // ...
    return report
}

In this refactored code, the generateReport function is now much shorter and focuses on orchestrating high-level tasks such as processing data, calculating the final result, and generating the report. Data manipulation, complex calculations, and report generation have been broken out into separate, well-named functions each responsible for a single task. Our code is now more modular, easier to read, and adheres to the Single Responsibility Principle, making it simpler to maintain and test.

4.2. Nested Functions

Nested functions often result in excessive complexity in our code. When functions are deeply nested, it becomes difficult to follow the program’s logic. This can be addressed by breaking down the logic into smaller, reusable functions and classes.

Here’s an example of some nested functions:

fun processOrder(order: Order) {
    fun validateOrder(order: Order) {
        // Validation logic
    }

    fun calculateTotal(order: Order) {
        // Total calculation logic
    }

    validateOrder(order)
    calculateTotal(order)
}

In this code, the functions validateOrder() and calculateTotal() are nested inside the processOrder() function. While nesting functions can be useful in some cases, excessive nesting can make the code less readable.

We can easily clean up those nested functions:

fun processOrder(order: Order) {
    validateOrder(order)
    calculateTotal(order)
}

fun validateOrder(order: Order) {
    // Validation logic
}

fun calculateTotal(order: Order) {
    // Total calculation logic
}

In this code, the validateOrder() and calculateTotal() functions are defined outside the processOrder() function. This improves code readability and allows for better organization of functions.

4.3. Complex Conditional Statements

Kotlin’s concise syntax can lead to the temptation of writing complex conditional statements in a single line. While this might seem elegant, it can reduce code readability. Use descriptive variable names and consider splitting complex conditionals into multiple lines.

Let’s look at an overly complex conditional statement:

if ((isAdult(user) && hasValidPayment(user)) || (isStudent(user) && hasValidStudentID(user))) {
    // Process the order
} else {
    // Handle eligibility issues
}

This conditional is complex because it combines multiple conditions with different logical operators. It checks if the user is either an adult with a valid payment or a student with a valid student ID. This can be difficult to understand and maintain.

Instead, we could write it as:

val isEligible = isAdult(user) && hasValidPayment(user)
val isStudentEligible = isStudent(user) && hasValidStudentID(user)
if (isEligible || isStudentEligible) {
    // Process the order
} else {
    // Handle eligibility issues
}

In the refactored version, we simplify the complex conditional by breaking it down into two separate conditions, one for adult eligibility and one for student eligibility. This makes the code easier to read and understand.

4.4. Data Class Abuse

Kotlin provides data classes to simplify the creation of classes that primarily hold data. However, using data classes for all classes — even those with complex behavior — can lead to code smells. Data classes should be reserved for simple value-holding objects:

data class User(val name: String, val email: String)

4.5. Overuse of !! Operator

Kotlin promotes null safety, but it also allows the use of the !! operator to forcefully dereference nullable types. Overusing this operator can lead to unexpected null pointer exceptions. Instead, prefer safe calls and handling nullable types gracefully.

We should replace the excessive use of the !! operator with safer constructs like safe calls and the ?. operator.

5. Code Smell Hindering Code Quality

The next category of code smells we’ll explore are higher-level smells that can negatively impact the overall quality of the code.

5.1. Code Duplication

Code duplication is a common code smell in any programming language. Repeated code can lead to maintenance issues. Consider extracting common functionality into functions or classes to minimize duplication.

For example, let’s consider these functions that all relate to circles and spheres:

fun calculateCircleArea(radius: Double): Double {
    return 3.14159265359 * radius * radius
}

fun calculateCylinderVolume(radius: Double, height: Double): Double {
    return 3.14159265359 * radius * radius * height
}

fun calculateSphereVolume(radius: Double): Double {
    return (4 / 3) * 3.14159265359 * radius * radius * radius
}

We can extract and reuse common pieces to remove duplication::

val PI = 3.14159265359

fun calculateCircleArea(radius: Double): Double {
    return PI * radius * radius
}

fun calculateCylinderVolume(radius: Double, height: Double): Double {
    return calculateCircleArea(radius) * height
}

fun calculateSphereVolume(radius: Double): Double {
    return (4.0 / 3.0) * calculateCircleArea(radius) * radius
}

In our improved example, the value of PI is declared as a constant at the beginning of the code. Since we’re computing the area and volume of circular shapes, we are also able to reuse our calculateCircleArea() function as the basis for our three-dimensional shapes. This not only reduces code duplication but also enhances code maintainability, readability, and consistency.

5.2. Excessive Mutable State

Kotlin encourages immutability, but developers can still use mutable state excessively. Immutable data structures lead to more predictable code and fewer bugs. We should try to minimize mutable state where possible and use val over var when declaring variables.

Let’s see an example of excessive use of mutable state:

class ShoppingCart {
    private var items = mutableListOf<Item>()
    private var totalPrice = 0.0

    fun addItem(item: Item) {
        items.add(item)
        totalPrice += item.price
    }

    fun removeItem(item: Item) {
        items.remove(item)
        totalPrice -= item.price
    }

    fun checkout() {
        items.clear()
        totalPrice = 0.0
    }
}

Our ShoppingCart class uses mutable variables items and totalPrice to maintain the state of the shopping cart. This mutable state can lead to unexpected side effects and make it difficult to reason about the behavior of the class.

Let’s see how we can refactor this code to prefer immutable values:

data class ShoppingCart(val items: List<Item>) {
    fun addItem(item: Item): ShoppingCart {
        return copy(items = items + item)
    }

    fun removeItem(item: Item): ShoppingCart {
        return copy(items = items - item)
    }

    fun calculateTotalPrice(): Double {
        return items.sumByDouble { it.price }
    }
}

fun checkout(cart: ShoppingCart) {
    // Process the order and update the inventory
}

In our improved example, ShoppingCart is now a data class with immutable properties, and its methods return a new instance with an updated state instead of modifying the existing instance.

This approach makes it easier to reason about the behavior of the code and minimizes the potential for unexpected side effects. Additionally, the checkout() function is separate from the ShoppingCart class, which promotes separation of concerns and helps keep the codebase more maintainable.

5.3. Inappropriate Exception Handling

Improper exception handling can clutter our code and lead to unexpected runtime issues. We should handle exceptions at the right level of abstraction and avoid catching and ignoring exceptions without a good reason.

Here’s an example of inappropriate exception handling:

fun divide(a: Int, b: Int): Int {
    try {
        return a / b
    } catch (e: Exception) {
        // Ignore the exception and continue
        return 0
    }
}

Let’s rewrite this function using proper exception handling:

fun divide(a: Int, b: Int): Int {
    if (b == 0) {
        throw IllegalArgumentException("Division by zero is not allowed.")
    }
    return a / b
}

Proper exception handling is used to handle the specific case of division by zero. When such an error occurs, the code now throws an IllegalArgumentException with a descriptive error message.

5.4. Inefficient String Manipulation

Kotlin provides several ways to manipulate strings, but not all are efficient. String concatenation in loops can lead to performance problems. Instead, we should use StringBuilder for building large strings.

Let’s look at some basic inefficient string concatenation:

fun concatenateStrings(strings: List<String>): String {
    var result = ""
    for (str in strings) {
        result += str
    }
    return result
}

In the above code, we have a loop that concatenates strings using the plus (+) operator, which is inefficient when dealing with large strings in a loop.

Instead, let’s rewrite it with StringBuilder:

fun concatenateStrings(strings: List<String>): String {
    val stringBuilder = StringBuilder()
    for (str in strings) {
        stringBuilder.append(str)
    }
    return stringBuilder.toString()
}

In this improved example, we use a StringBuilder to efficiently build the concatenated String. StringBuilder is designed for efficient string manipulation, especially within loops, as it avoids creating multiple intermediate String objects. This results in better performance and reduced memory usage.

5.5. Tight Coupling

Tight coupling occurs when different parts of our code are highly dependent on each other, making it challenging to modify or maintain the code. In Kotlin, tight coupling can manifest as direct references to concrete classes, lack of abstractions, and global state dependencies.

To address tight coupling:

  • Use dependency injection to pass dependencies into classes instead of creating them within the class.
  • Encapsulate dependencies behind interfaces or abstract classes, allowing for flexibility in choosing different implementations.
  • Favor composition over inheritance, as it reduces class hierarchies and makes our code more flexible.

Let’s look at an example with tight coupling:

class OrderProcessor {
    private val paymentProcessor = PaymentProcessor()

    fun processOrder(order: Order) {
        paymentProcessor.processPayment(order)
    }
}

To reduce coupling, we should rewrite our code to expect things they depend on to be provided, instead of directly managing their own dependencies:

class OrderProcessor(private val paymentProcessor: PaymentProcessor) {
    fun processOrder(order: Order) {
        paymentProcessor.processPayment(order)
    }
}

In the example above, we demonstrated how to reduce tight coupling in Kotlin code. The initial implementation had tight coupling because it directly instantiated the PaymentProcessor class within the OrderProcessor, making it difficult to replace or modify the payment processing logic without altering the OrderProcessor class.

By introducing dependency injection and passing the PaymentProcessor as a constructor parameter, we decoupled the OrderProcessor from its dependency.

5.6. Primitive Obsession

Primitive obsession occurs when we rely on primitive data types such as Ints and Strings to represent domain-specific concepts instead of creating dedicated domain classes. This can lead to code that is harder to understand, maintain, and extend.

To address primitive obsession:

  • Create domain-specific classes to encapsulate data and behavior related to a particular concept.
  • Use these domain classes to represent and manage domain-specific data.

Let’s look at an example where we convey a complex concept with primitives only:

fun rectangleArea(width: Int, height: Int): Int width * height

In this code smell, we’re using the primitive data type Int to represent a concept that deserves its own class.

Let’s take a look at how we can reduce this primitive obsession:

class Rectangle(val width: Int, val height: Int) {
    fun calculateArea(): Int {
        return width * height
    }
}

In the improved version, we’ve created a Rectangle class to encapsulate the width and height properties and provide a method to calculate the area, which is a common way to refactor our code to eliminate the primitive obsession code smell.

6. Conclusion

In this article, we’ve discussed several code smells that are indicators of potential issues and inefficiencies in our Kotlin code. We’ve explored a variety of these code smells, ranging from long and nested functions to inappropriate exception handling, and provided examples of each. Understanding these code smells and how to address them is vital for producing high-quality Kotlin software.

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