Domain-Driven Design with Records in C#

Introduction

Effective modeling of domain logic is crucial for the success of a software engineering project. Domain-Driven Design (DDD) provides a framework for structuring applications around the domain model and focusing on the core business concepts and their relationships. A critical aspect of DDD is representing domain concepts as value objects that encapsulate small pieces of domain knowledge. C# 9.0 introduces a powerful feature called Records, which aligns seamlessly with the principles of DDD, particularly in modeling value objects. This article explores how Records in C# can be leveraged to enhance DDD, with a focus on value objects, accompanied by illustrative examples.

Understanding Value Objects in DDD

In DDD, value objects are immutable objects representing concepts or measurements. They are defined solely by their attributes and lack a distinct identity beyond their values. Examples of value objects include EmailAddress, Money, or Temperature. Value objects are fundamental to DDD as they help in expressing domain logic in a concise and meaningful manner.

Records in C#

Records, introduced in C# 9.0, are a new kind of type that makes it easy to create immutable data structures. They are defined using the record keyword and come with built-in support for immutability, equality comparison, and other common operations.

Let's delve into an example:

public record Point(int X, int Y);

In this snippet, Point is declared as a record with two properties: X and Y. Records automatically generate constructors, equality members, and other useful methods based on their properties.

Utilizing Records as Value Objects in DDD

Records offer several advantages when used to model value objects in DDD:

1. Immutability: Records are immutable by default, meaning once created, their state cannot be modified. This aligns perfectly with the nature of value objects, which should remain unchanged once instantiated.
2. Conciseness: Records eliminate boilerplate code typically associated with immutable classes, resulting in cleaner and more concise code. This enhances readability and reduces the chance of errors.
3. Built-in Equality Semantics: Records provide value-based equality semantics out of the box. Two record instances are considered equal if all their properties are equal. This simplifies equality comparisons, which are crucial in DDD.
4. Pattern Matching: C# pattern matching can be seamlessly integrated with records, enabling powerful and expressive domain logic. Pattern matching facilitates pattern-based algorithms and decision-making, further enhancing the flexibility of DDD implementations.

Example. Using Records for Value Objects

Let's consider modeling a Temperature value object using a record in C#.

public record Temperature(double Value, TemperatureUnit Unit);

public enum TemperatureUnit { Celsius, Fahrenheit }

public class WeatherForecast
{
    public Temperature MaxTemperature { get; init; }
    public Temperature MinTemperature { get; init; }
}

In this example, Temperature is defined as a record with two properties: Value and Unit. The TemperatureUnit enum represents the unit of measurement. The WeatherForecast class utilizes Temperature value objects to represent maximum and minimum temperatures.

Conclusion

Records in C# provide a powerful mechanism for defining immutable reference types, making them an excellent choice for modeling value objects in DDD. By leveraging records, developers can create clear, expressive, and maintainable domain models that accurately reflect the underlying business concepts.

Incorporating records into DDD practices enhances code readability, simplifies domain modeling, and promotes adherence to core DDD principles such as immutability and value-based equality. As C# evolves, records stand out as a valuable tool for building robust and domain-driven applications that effectively capture and represent complex domain logic.