Fraktalio.FModel 0.1.0

f(model-c#) - Domain Modeling

The project is in experimental phase. Pre-release packages are available at nuget.org.

A stable release is one that's considered reliable enough to be used in production.

When you’re developing an information system to automate the activities of the business, you are modeling the business. The abstractions that you design, the behaviors that you implement, and the UI interactions that you build all reflect the business — together, they constitute the model of the domain.

IOR<Library, Inspiration>

This project can be used as a multiplatform library, or as an inspiration, or both. It provides just enough tactical Domain-Driven Design patterns, optimised for Event Sourcing and CQRS.

Abstraction and generalization

Abstractions can hide irrelevant details and use names to reference objects. It emphasizes what an object is or does rather than how it is represented or how it works.

Generalization reduces complexity by replacing multiple entities which perform similar functions with a single construct.

Abstraction and generalization are often used together. Abstracts are generalized through parameterization to provide more excellent utility.

Func<C, S, IEnumerable<E>> decide

On a higher level of abstraction, any information system is responsible for handling the intent (Command) and based on the current State, produce new facts (Events):

• given the current State/S on the input,
• when Command/C is handled on the input,
• expect list of new Events/E to be published/emitted on the output

Func<S, E, S> evolve

The new state is always evolved out of the current state S and the current event E:

• given the current State/S on the input,
• when Event/E is handled on the input,
• expect new State/S to be published on the output

Event-sourced or State-stored systems

• State-stored systems are traditional systems that are only storing the current State by overwriting the previous State in the storage.
• Event-sourced systems are storing the events in immutable storage by only appending.

Both types of systems can be designed by using only these two functions and three generic parameters:

• Func<C, S, IEnumerable<E>> decide
• Func<S, E, S> evolve

There is more to it! You can switch from one system type to another or have both flavors included within your systems landscape.

Two functions are wrapped in a datatype class (algebraic data structure), which is generalized with three generic parameters:

public class Decider<C, S, E>(Func<C, S, IEnumerable<E>> decide, Func<S, E, S> evolve)
{
    public Func<C, S, IEnumerable<E>> Decide { get; } = decide;
    public Func<S, E, S> Evolve { get; } = evolve;
}

Decider is the most important datatype, but it is not the only one. There are others:

Decider

Decider is a datatype that represents the main decision-making algorithm. It belongs to the Domain layer. It has three generic parameters C, S, E , representing the type of the values that Decider may contain or use. Decider can be specialized for any type C or S or E because these types do not affect its behavior. Decider behaves the same for C=Int or C=YourCustomType, for example.

Decider is a pure domain component.

• C - Command
• S - State
• E - Event

public class Decider<C, S, E>(Func<C, S, IEnumerable<E>> decide, Func<S, E, S> evolve, S initialState)
    : IDecider<C, S, E>
{
    public Func<C, S, IEnumerable<E>> Decide { get; } = decide;
    public Func<S, E, S> Evolve { get; } = evolve;
    public S InitialState { get; } = initialState;
}

Additionally, initialState of the Decider is introduced to gain more control over the initial state of the Decider. Notice that Decider implements an interface IDecider to communicate the contract.

Decider functions

Contravariant

• Decider<Cn, S, E> MapLeftOnCommand<Cn>(Func<Cn, C> f)

Profunctor (Contravariant and Covariant)

• Decider<C, S, En> DimapOnEvent<En>(Func<En, E> fl, Func<E, En> fr)
• Decider<C, Sn, E> DimapOnState<Sn>(Func<Sn, S> fl, Func<S, Sn> fr)

Commutative Monoid

public static Decider<C_SUPER?, Tuple<S, S2>, E_SUPER?> Combine<C, S, E, C2, S2, E2, C_SUPER, E_SUPER>(
        this Decider<C?, S, E?> x, Decider<C2?, S2, E2?> y)
        where C : class, C_SUPER
        where C2 : class, C_SUPER
        where E : class, E_SUPER
        where E2 : class, E_SUPER

A monoid is a type together with a binary operation (combine) over that type, satisfying associativity and having an identity/empty element. Associativity facilitates parallelization by giving us the freedom to break problems into chunks that can be computed in parallel.

combine operation is also commutative. This means that the order in which deciders are combined does not affect the result.

View

View is a datatype that represents the event handling algorithm, responsible for translating the events into denormalized state, which is more adequate for querying. It belongs to the Domain layer. It is usually used to create the view/query side of the CQRS pattern. Obviously, the command side of the CQRS is usually event-sourced aggregate/decider.

It has two generic parameters S, E, representing the type of the values that View may contain or use. View can be specialized for any type of S, E because these types do not affect its behavior. View behaves the same for E=Int or E=YourCustomType, for example.

View is a pure domain component.

• S - State
• E - Event

public class View<S, E>(Func<S, E, S> evolve, S initialState) : IView<S, E>
{
    public Func<S, E, S> Evolve { get; } = evolve;
    public S InitialState { get; } = initialState;
}

Notice that View implements an interface IView to communicate the contract.

View functions

Contravariant

• View<S, En> MapLeftOnEvent<En>(Func<En, E> f) => new InternalView<S, S, E>(Evolve, InitialState).MapLeftOnEvent(f).AsView();

Profunctor (Contravariant and Covariant)

• View<Sn, E> DimapOnState<Sn>(Func<Sn, S> fl, Func<S, Sn> fr) => new InternalView<S, S, E>(Evolve, InitialState).DimapOnState(fl, fr).AsView();

Commutative Monoid

public static View<Tuple<S, S2>, E_SUPER> Combine<S, E, S2, E2, E_SUPER>(this View<S, E?> x, View<S2, E2?> y)
        where E : class, E_SUPER
        where E2 : class, E_SUPER

A monoid is a type together with a binary operation (combine) over that type, satisfying associativity and having an identity/empty element. Associativity facilitates parallelization by giving us the freedom to break problems into chunks that can be computed in parallel.

combine operation is also commutative. This means that the order in which views are combined does not affect the result.

Saga

Saga is a datatype that represents the central point of control, deciding what to execute next (A). It is responsible for mapping different events from many aggregates into action results AR that the Saga then can use to calculate the next actions A to be mapped to commands of other aggregates.

Saga is stateless, it does not maintain the state.

It has two generic parameters AR, A, representing the type of the values that Saga may contain or use. Saga can be specialized for any type of AR, A because these types do not affect its behavior. Saga behaves the same for AR=Int or AR=YourCustomType, for example.

Saga is a pure domain component.

• AR - Action Result
• A - Action

public class Saga<AR, A>(Func<AR, IEnumerable<A>> react) : ISaga<AR, A>
{
    public IEnumerable<A> React(AR actionResult) => react(actionResult);
}

Notice that Saga implements an interface ISaga to communicate the contract.

Saga functions

Contravariant

• Saga<ARn, A> MapLeftOnActionResult<ARn>(Func<ARn, AR> f) => new(arn => react(f(arn)));

Covariant

• Saga<AR, An> MapOnAction<An>(Func<A, An> f) => new(ar => react(ar).Select(f));

Monoid

public static Saga<AR_SUPER, A_SUPER?> Combine<AR, A, AR2, A2, AR_SUPER, A_SUPER>(this Saga<AR?, A> sagaX,
        Saga<AR2?, A2> sagaY)
        where AR : AR_SUPER
        where A : A_SUPER
        where AR2 : AR_SUPER
        where A2 : A_SUPER

A monoid is a type together with a binary operation (combine) over that type, satisfying associativity and having an identity/empty element. Associativity facilitates parallelization by giving us the freedom to break problems into chunks that can be computed in parallel.

combine operation is also commutative. This means that the order in which sagas are combined does not affect the result.

Getting Started with fmodel-c#

The fmodel-c# library is available on nuget.org.

Note: fmodel-c# is in Pre-Release!

The fmodel-c# library is currently in pre-release. At this stage, it focuses exclusively on pure domain components that effectively model behavior.

The application layer will be included in future updates. This will provide guidance on composing and running the domain model in various scenarios, including:

• Event-sourced scenarios
• State-stored scenarios

FModel in other languages

• FModel in Kotlin
• FModel in TypeScript
• FModel in Rust

References and further reading

• https://www.youtube.com/watch?v=kgYGMVDHQHs
• https://fraktalio.com/fmodel/

Credits

Special credits to Jérémie Chassaing for sharing his research and Adam Dymitruk for hosting the meetup.

Thank you, Srdjan Zivojinovic and Crafters Cloud, for your significant contributions to this project.

Created with ❤️ by Fraktalio