ASP.NET Tutorial : Domain-Driven Design using Record in C#

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A software engineering project's success depends on effective domain logic modeling. Domain-Driven Design (DDD) is a paradigm for designing applications around the domain model, emphasizing the essential business concepts and their interactions. DDD relies heavily on modeling domain concepts as value objects that encapsulate small chunks of domain knowledge. C# 9.0 provides Records, a strong feature that perfectly matches with DDD concepts, particularly when modeling value objects. This article investigates how Records in C# can be used to improve DDD, with an emphasis on value objects and illustrative examples.

Understanding the Value Objects in DDD

DDD defines value objects as immutable objects that represent concepts or measurements. They are characterized exclusively by their characteristics and lack a distinct identity apart from their values. Value things include email addresses, money, and temperature. Value objects are essential to DDD because they assist describe domain logic in a succinct and understandable way.

Record in C#

Records, introduced in C# 9.0, are a new type that allows you to easily design immutable data structures. They are defined with the record keyword and provide built-in support for immutability, equality comparison, and other standard operations.

Let's look at 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.


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.

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