Friday, 15 May 2020

JAX-RS integration under construction

Both Spring Web MVC and Spring Web Flux integrated.  See:

 - http://officefloor.net/tutorials/SpringWebMvcHttpServer
 - http://officefloor.net/tutorials/SpringWebFluxHttpServer

JAX-RS also now integrated:


Currently, adding additional CDI support.  Will then look at maven plugin for automated migration of project from Spring to OfficeFloor

Saturday, 28 March 2020

Migrating Spring Application to OfficeFloor

This series of articles looks at migrating Spring applications to OfficeFloor.

Why?

So the first question comes up.

Why migrate Spring applications to OfficeFloor?

Spring provides dependency injection to create a graph of objects. Spring, however, provides little management over threading and attempts to model behaviour through object composition. This is where OfficeFloor in it's Inversion of Coupling Control provides injection management of threading and functional behaviour.

Now this is not to say Spring is inferior.  Spring's focus has come from and stays with mainstream Object Orientation.  OfficeFloor has merely taken these Object Orientation concepts and extended them with Functional Programming composition concepts and Process/Threading concepts.

Now if you are happy with mainstream Object Orientation then by all means stick with Spring.  Spring is a great Object Oriented framework that deserves its success.

However, if you want to avoid writing your own threading or would like more seamless support for functional programming, then please read on.

Let's not replace Spring

It would be unreasonable to port a Spring application in its entirety.  Spring has been under active development since the turn of the millennium.  Ok, at the time of writing this article that is just under two decades. For some industries that could be considered a short time.  However, in the IT industry, where there are new JavaScript frameworks popping up every day, this longevity is testament to Spring's success.

For me, Spring's success has been because it got something fundamentally right. Now we could argue academically about Object Oriented composition vs Functional Programming composition.  We could argue about libraries vs frameworks.  We could even argue about Java vs new languages like Kotlin. But what I see in these arguments is focus on finding simpler and easier ways to write software.  And for me, Spring (and more specifically Spring Boot) did that by getting rid of the repetitive plumbing code.  This is so we could get on with writing the important functionality of our applications.

To enable focus on removing repetitive plumbing code there are a few things required:
  1. Extensible framework
  2. Plugins written for supporting the various infrastructure / existing solutions
  3. Open platform for community addition / management of plugins
Spring by wiring objects together enables this extensibility.  New functionality can be included by wiring in the objects to support that functionality

Plugins then extend the framework to cover including various infrastructure and existing solutions.  The plugins avoid us re-inventing the wheel so our focus can be on achieving the functionality of our application.

The final aspect is supporting the IT ecosystem. There are so many competing technologies and even platforms with the various cloud providers. A single group or company attempting to support this would be overwhelmed. Therefore, Spring has developed a strong open source community to write and maintain all the plugins. Even VMWare's acquisition of Spring mentions this open source community.

Therefore, it is unreasonable to rewrite Spring into something new.  There is too much of an ecosystem to replicate.

Integrating Spring

So rewriting everything Spring into OfficeFloor is not a feasible direction.

Rewriting is also a violation of the first point - an extensible framework.

OfficeFloor must subsequently be extensible to plugin Spring.  OfficeFloor supports extension via Object Orientation, Functional Programming and Threading.  Therefore, if OfficeFloor is not extensible via Object Oriented Spring, then OfficeFloor fails at being extensible.

OfficeFloor supports plugging in Spring via a SupplierSource.  This extension point of OfficeFloor allows for third party dependency injection frameworks to make their dependencies available for injection in OfficeFloor applications.

Now OfficeFloor's website provides detailed tutorials on various aspects.  OfficeFloor likes to adhere to the DRY (don't repeat yourself) principle, so this article series will direct you to the relevant tutorials for detailed aspects of Spring to OfficeFloor migration. Therefore, please see the Spring tutorial for how to plugin Spring dependencies into OfficeFloor.

The result of plugging Spring into OfficeFloor is that OfficeFloor gets a library of pre-written objects.  Spring focuses on wiring together a graph of objects.  OfficeFloor does not interfere with this, as Spring does this exceptionally well.  What OfficeFloor does is allow reference to the various objects in the Spring graph for injection into its own application.  This effectively allows OfficeFloor to be extended with Spring managed objects.

Going beyond Objects

The rest of this article serious will look at how to migrate our Object Oriented Spring applications into OfficeFloor to start using OfficeFloor's Functional Programming and Threading extensions.  While objects link data with functionality (methods), objects still provide little in terms of threading.  This article series will show how to further simplify our Spring applications with these Functional Programming and Threading extensions/plugins by migrating to OfficeFloor.

Tuesday, 11 February 2020

DDD Perth 2019 Presentation

The DDD Perth 2019 presentation of Inversion of Coupling Control has been published.  Enjoy!


Saturday, 25 January 2020

Monad with IoCC provides Process/Thread model

This is the final article in the series on looking at Inversion of Coupling Control (IoCC) composition.  The previous articles covered:


This article looks at providing a mathematical model to explain the composition.

Just a little disclaimer that I'm not a mathematics boffin.  I've a degree in computer science but it did not cover much functional programming. Much of this is through my self taught understanding of functional programming and mathematics.  Therefore, I'm happy to take feedback from more capable mathematicians on better ways to express the model.  However, I'm hoping this article reasonably conveys the underlying model for composition with Inversion of Coupling Control.

From Category Theory, we have the associative law:

  f(x) . g(x) = f.g(x)

With this we can introduce dependencies:

  f(x)(d1) . g(x)(d2) = f.g(x)(d1, d2)

where:
  d is a set of dependencies

This makes the program very rigid, as changing d1 to d3 has significant impact for use of f(x)(d1 now d3).  For example, switching from database connection to REST end point.

ZIO attempts to reduce the rigidity by the following:

  f(x)(d1) . g(x)(d2) = f.g(x)(D)

where:
  D = d1 + d2
Or, in other words:
  D extends d1 with d2

Now, we can create lots of morphisms and at execution of resulting ZIO, provide a hom(D), which is the set of all required dependencies.

So, this model works.  It is certainly enabling injection of dependencies in functional programs.

Now, I'd like to take another tact to the problem.

The Imperative Functional Programming paper could not see how to remove the continuation type (z) from the signature. The authors did conclude Monads and CPS very similar, but due to the extra continuation type on the signature and the author's intuition, the IO Monad was the direction forward.

Now I certainly am not taking the tact to replace IO Monad with CPS. I'm looking to create a complementary model. A model where continuations decouple the IO Monads.

So introducing dependencies to the IO Monad, we get:

  IO[x](d)

where:
  d is the set of dependencies required

This then follows, that joining two IO together we get:

  IO[x](d1, d2)

So, maybe let's keep the IO Monad's separate and join them via CPS.   This changes the signature to:

  IO[x](d)(z)

where:
  z = Either[Throwable,x] -> ()

The pesky z that the Imperative Functional Programming paper was talking about.

However, discussed previously is Continuation Injection. This effectively hides the z from the signature, making it an injected function. As it's an injected function, the z becomes an indirection to another function. This indirection can be represented as:

  IO[_](d1) -> (Either[Throwable,y] -> IO[y](d2)) -> IO[y](d2)

Note: the joined IO need only handle y or any of it's super types. Hence, the relationship indicates the passed type. This makes it easy to inject in another IO for handling the continuation.

Now to start isolating the IO Monads from each other, we are going to start with Thread Injection.

  d -> Executor

This represents Thread Injection choosing the appropriate Executor from the dependencies.  Therefore, we can then introduce a Thread Injection Monad to choose the Executor.

  F[_](d)(Executor) -> (d -> Executor) -> TI[F[_](d)] 

where
  TI is the Thread Injection Monad that contains the dependency to Executor mapping to enable executing the IO Monad with the appropriate Executor.

This then has the above continuation between IO Monads relationship become.

  TI[IO[_](d1)] -> (Either[Throwable,y] -> IO[y](d2)(Executor)) -> TI[IO[y](d2)]

Now the IO Monads can be executed by the appropriate Executor via the TI Monad.

Further to this, we can model dependency injection with:

  F[_](d) -> (F[_](d) -> F[_]) -> DI[F[_]]

where
  DI is the Dependency Injection Monad that supplies dependencies to the function.

Note that DI Monad will also manage the life-cycle of the dependencies.  Discussion of how this is managed will be a topic for another article.

So the above IO Monad continuation relationship becomes:

  TI[DI[IO[_]]] -> (Either[Throwable,y] -> IO[y](d)(Executor)) -> TI[DI[IO[y]]]

where:
  DI propagates the same instances of dependencies across the continuation

Now, with Continuation Injection we are not limited to injecting in only one continuation.  We can inject in many:

  TI[DI[IO[_]]] -> (Either[Throwable,y] -> IO[y](d)(Executor)) -> TI[DI[IO[y]]]
                -> (Either[Throwable,w] -> IO[w](d)(Executor)) -> TI[DI[IO[w]]]
                ...

Note: I'm guessing this can be represented on a single line (possible as set of continuations from a particular IO) but I'll leave that to a boffin more mathematical than me.

This means we can remove the Either and have the (possibly many) exceptions handled by separate continuations to get:

  TI[DI[IO[_]]] -> (y -> IO[y](d)(Executor)) -> TI[DI[IO[y]]]
                -> (ex -> IO[ex](d)(Executor)) -> TI[DI[IO[ex]]]
                ...

This demonstrates that an IO may now actually have more than one output. By having the ability to inject multiple continuations, the IO is capable of multiple outputs.

It is also execution safe.  OfficeFloor (Inversion of Coupling Control) ensures the handling of one continuation completes before the next continuation begins executing. This ensures only one IO is ever being executed at one time.

Further to this we can qualify DI. Originally we had d1, d2 that was hidden by DI. We can qualify the scope of DI as follows:

  DI[P,T,_]

where:
  P is the set of process dependency instances
  T is the set of thread dependency instances

This allows for the following.

  Same thread = DI[P,T,_] -> (_ -> _) -> DI[P,T,_]
  Spawned thread = DI[P,T,_] -> (_ -> _) -> DI[P,S,_]
  New process = DI[P,T,_] -> (_ -> _) -> DI[Q,S,_]

In other words,
  • spawning a thread is creating a new set of thread dependencies instances
  • interprocess communication is a different set of process dependency instances
Further to this:
  • the set of T may only be the same if the set of P is same
  • context (eg transactions) apply only to dependencies in T
The resulting IO Monad relationship for a same thread continuation becomes.

  TI[DI[P,T,IO[_]]] -> (y -> IO[y](d)(Executor)) -> TI[DI[P,T,IO[y]]]

while a spawned thread continuation relationship is modelled as follows.

  TI[DI[P,T,IO[_]]] -> (y -> IO[y](d)(Executor)) -> TI[DI[P,S,IO[y]]]

What this essentially allows is multi-threading concurrency. Any continuation may spawn a new thread by starting a new set of thread dependencies. Furthermore, OfficeFloor will asynchronously process the continuation returning control immediately. This has the effect of spawning a thread.

The same goes for spawning a new process.

  TI[DI[P,T,IO[_]]] -> (y -> IO[y](d)(Executor)) -> TI[DI[Q,S,IO[y]]]

Therefore, with OfficeFloor, processes and threading are a configuration not a programming problem. Developers are no longer required to code thread safety into their possible imperative code within the IO. As the seldom used process dependencies are coded thread safe, this relationship introduces the ability for mutability within the IO that is thread safe. The isolation of dependencies prevents memory corruption (assuming dependencies respect not sharing static state).

OfficeFloor (Inversion of Coupling Control) is in this sense possibly the dark side. Functional programming strives for purity of functions being the light. Given OfficeFloor can handle:
  • multiple outputs from IOs including exceptions as continuations
  • mutability within the IOs that is thread safe
OfficeFloor enables modeling the darker impurities (or maybe I just watch too much StarWars).

What we now have is a possible "inversion" of the function:
  • Function: strives to be pure, may have multiple inputs and only a single output.    
  • IoCC: allows impurities, has a single input and may have multiple outputs.
I personally like to think of functions like parts of a machine.  They are highly coupled engine cogs providing always predictable output.

I then like to think of IoCC like signals. This is a more organic structure of loosely coupled events triggering other loosely coupled events. The result is a mostly predictable output. This is more similar to human decisioning outputs.

Regardless, we now have a typed model that can be represented as a directed graph of interactions. The IO Monads are the nodes with the various continuations edges between them. An edge in the graph is qualified as follows.

  TI[DI[IO]] == y,p,t ==> TI[DI[IO]]

where:
  y indicates the data type provided to the continuation
  p indicates if a new process is spawned (represented as 0 for no and 1 for yes)
  t indicates if a new thread is spawned (again represented as 0 for no and 1 for yes)

The result is the following example graph.
which, is essentially the OfficeFloor Continuation Injection configuration.

Summary

All of the above is already implemented in OfficeFloor.

The previous articles demonstrated the type system of Inversion of Coupling Control to enable composition. The type system also enabled encapsulation in First-Class Modules for easy assembly and comprehension of OfficeFloor applications. This was then demonstrated with a simple example application.

What this article has attempted to cover is the core underlying model. It has looked at how injected continuations can be used to join together IO instances. Further, it looked at the dependencies and how they can be used to model processes and threads.

Future Work

At the moment, we're focused on making building non-distributed applications a pleasure with OfficeFloor. This runs on the premise that if you are not enjoying building smaller applications with a toolset, why would you want to build larger more complex applications with that toolset.

However, we are nearing the completion of the bulk of this work.

We will be looking to simplify building distributed applications soon.

This will be achieved by looking at algorithms to examine the directed graph of continuations to decide on best places to separate the IOs into different containers.  What the algorithms will take into account are the above relationships. In particular:
  • the directed graph of continuations
  • isolating sub graphs by the process (and possibly thread) dependency rules
  • identifying which sub graphs to isolate to another container by incorporating run time metrics of the IOs
Note that we can model interprocess communication as:

  Async (e.g. queue) = DI[P,T,_] -> (message -> _) -> DI[Q,S,_] -> ()
  Sync (e.g. REST)  = D[P,T,_] -> (request -> _) -> D[Q,S,_] -> (response -> _) -> D[P,T,_]

This can provide type safe modeling of distributing the IOs within the directed continuation graph.

Note that we may have to mark dependency instances that carry non-replicatable state between IO Monads.  In other words, a database connection (not in transactional context) can be replicated by obtaining another database connection from the pool.  However, a dependency that stores some value in it from one IO Monad that is used by the next IO Monad is non-replicable.

In practice, this has only been variable dependencies to further remove the parameter coupling between IO Monads (see OfficeFloor tutorials).

However, we are also finding in practice that it is relatively intuitive to find sub graphs to isolate to their own containers.  Endeavours in this work will likely look at automation of dynamically isolating sub graphs to containers as load changes (effectively having selective elastic scale of functions not arbitrarily bounded microservices).

Tuesday, 14 January 2020

compose Cats, Reactor, ZIO, ... Effects

This is the third in a series of articles looking at the type system for Inversion of Coupling Control to provide composition.

The previous articles covered:
This article will look at taking the theory into practice.  It will use the concepts to build an application composing Effects from various Effect libraries.

Note that the Effects used is kept deliberately simple to focus on the composition of the effects.  This is mainly because this article is not to compare libraries.  This article is to compose them.  We show how using Inversion of Coupling Control they can be seamlessly composed together in a simple application.  Also, order of discussing the libraries is nothing more than alphabetical.

To keep matters simple the effect will be retrieving a message from the database.

Cats

Let's begin with Cats Effect.

  def cats(request: ServerRequest)(implicit repository: MessageRepository): IO[ServerResponse] =
    for {
      message <- catsGetMessage(request.getId)
      response = new ServerResponse(s"${message.getContent} via Cats")
    } yield response

  def catsGetMessage(id: Int)(implicit repository: MessageRepository): IO[Message] =
    IO.apply(repository findById id orElseThrow)

The catsGetMessage function wraps the repository retrieving message effect within an IO.   This can then be used to service the request to provide a response (as per the cats function).

The use of implicit may be overkill for the single repository dependency.  However, it shows how dependency injection can remove dependency clutter from the servicing logic.  This is especially useful when the number of dependencies grows.

Reactor

Reactor has the following servicing logic.
  def reactor(request: ServerRequest)(implicit repository: MessageRepository): Mono[ServerResponse] =
    reactorGetMessage(request.getId).map(message => new ServerResponse(s"${message.getContent} via Reactor"))

  def reactorGetMessage(id: Int)(implicit repository: MessageRepository): Mono[Message] =
    Mono.fromCallable(() => repository.findById(id).orElseThrow())

Again, there is a reactorGetMessage function wrapping the retrieving message effect into a Mono.  This is then used to service the request.

ZIO

For ZIO the logic is slightly different, as ZIO provides it's own dependency injection.

  def zio(request: ServerRequest, repository: MessageRepository): ZIO[Any, Throwable, ServerResponse] = {
    // Service logic
    val response = for {
      message <- zioGetMessage(request.getId)
      response = new ServerResponse(s"${message.getContent} via ZIO")
    } yield response

    // Provide dependencies
    response.provide(new InjectMessageRepository {
      override val messageRepository = repository
    })
  }

  def zioGetMessage(id: Int): ZIO[InjectMessageRepository, Throwable, Message] =
    ZIO.accessM(env => ZIO.effect(env.messageRepository.findById(id).orElseThrow()))

  trait InjectMessageRepository {
    val messageRepository: MessageRepository
  }

The zioGetMessage again wraps the retrieve database message effect within a ZIO.  However, it extracts the injected trait to retrieve the repository.

Encapsulating into a Module

The above functions (cats, reactor, zio) are configured as First-Class Procedures into the following Module.
This module has an output being the Response with inputs Cats, Reactor, ZIO and Imperative.

As First-Class Procedures are lazily evaluated they can also wrap imperative code containing effects.  The imperative function is the following.

  def imperative(request: ServerRequest, repository: MessageRepository): ServerResponse = {
    val message = repository.findById(request.getId).orElseThrow()
    new ServerResponse(s"${message.getContent} via Imperative")
  }

Using the Module

The following configuration uses the module to service REST requests.  It is configured as the Synchronous module.

This demonstrates how easy it is to configure the module into servicing requests.

What is further interesting is the Asynchronous module has the same interface of inputs/outputs as the Synchronous module.  Now, this could quite possibly be the above module re-used (just badly named).   However, it is not.  The Asynchronous module undertakes the same logic, but just asynchronously (code available in demo project).

What is important for modules is the contractual interface of inputs and outputs.  We could quite happily swap the Synchronous / Asynchronous modules around in the configuration and the application will still continue to work.  This allows the complexity to be encapsulated.

A more real world example is we could start out with the quicker to write and easier to debug synchronous effects.  Then as the application grows in scale, we may decide to swap in an asynchronous module to better handle scale.  The amount of refactoring to swap the Synchronous module to the Asynchronous module would be:
  1. Drop in new Asynchronous module
  2. Re-wire flows to the Asynchronous module
  3. Delete the Synchronous module
As Inversion of Coupling Control removes the function coupling, there is no code to change except providing the implementation of the new module.

With modules able to contain modules, this provides a means to encapsulate complexity of the application for easier comprehension.  It also makes importing modules simple.  Drop them in and wire them up.  And is especially useful when libraries of third party modules are available for composition of ready to use functionality.

Composing Effects

This demonstrates First-Class Procedures and First-Class Modules of the previous articles in this series.

Hey, but this article promised composing effects!

Well I could tell you the send is an effect and that composing this after the above effects is that composition.   However, that's taking a lot of my word for it.

Therefore, the last module in the server configuration is the following.
This module composes an effect from each of the libraries.  The code for each effect is the following.
  def seed: String = "Hi"

  def cats(@Parameter param: String): IO[String] = IO.pure(s"$param, via Cats")

  def reactor(@Parameter param: String): Mono[String] = Mono.just(s"$param, via Reactor")

  def zio(@Parameter param: String): ZIO[Any, Nothing, String] = ZIO.succeed(s"$param, via ZIO")

  def imperative(@Parameter param: String): String = s"$param, via Imperative"

  def response(@Parameter message: String): ServerResponse = new ServerResponse(message)

Each effect just takes the input of the previous and appends it's library name.  The resulting response is a string containing all the effect library names.

No adapters

Astute readers may be thinking that under the hood of OfficeFloor there may be some fabulous adapters between the libraries.  Hmmm, can we extract these and make use of them?

Sadly and for that matter quite happily there are no adapters between the libraries.  What actually happens is that each First-Class Procedure unsafely executes its effect and retrieves the resulting output.  With the output OfficeFloor then invokes the next First-Class Procedure.  By doing so, we do not need to adapt the libraries with each other.  We can run each effect in isolation and interface them via their typed inputs/outputs.

This makes integration of new effect libraries very simple.  Just write a once off adapter to encapsulate the library's effects within a First-Class Procedure.  The effect library is then able to integrate with all the other effect libraries.  As First-Class Procedures are actually a specialised First-Class Module, this demonstrates the composition capabilities of Inversion of Coupling Control.

Summary

This article has been code and configuration heavy to demonstrate how First-Class Procedures and First-Class Modules compose.

It has demonstrated that the type system of Inversion of Coupling Control makes composition easy (essentially drawing lines).

Now you need not take my word on the code examples in this article.  They are extracted from the demonstration project you can clone and run yourself (found at https://github.com/officefloor/ComposeEffectsDemo).

Also, if we've missed your favourite effects library please excuse me.  We're happy, if enough interest, to work with you incorporate adapters to provide further demonstration of integrating the beloved effect library.  Focus of OfficeFloor is not to be opinionated but rather provide an open platform to integrate software.

The next article in the series tests my self taught mathematics to attempt to explain the underlying model of why this ease of composition is possible.

Wednesday, 25 December 2019

First-Class Module

This is the second in a series looking at the Inversion of Coupling Control type system for composition.  This article discusses a more general Module type system than the previous article's First-Class Procedure Type.

Note: some functional programming languages also attempt to define First-Class Modules.  The First-Class Modules defined in this article are created from inverted functions.

First-Class Procedure

To recap the last article, the First-Class Procedure's type is defined as follows.  Note that we exclude the dependency type, as dependencies are auto-wired.

FirstClassProcedureType {
    Class<?> parameterType;
    ContinuationType[] continuations;
}

ContinuationType {
    String name;
    Class<?> argumentType;
}

This defines the First-Class Procedure to have a single input parameter and multiple continuations out for further composition of logic and handling of exceptions.

Module

Having a single input with multiple outputs is fine for methods, functions, etc wrapped in First-Class Procedures.   However, when systems grow we don't want the complexity to make the inputs/outputs suffer similar increased complexity.  We want the inputs/outputs to provide an interface to encapsulate the complexity of the Module.  Note that without encapsulation, we don't get the ability to modularise the complexity of the application.

To enable an interface to the Module, let's create the following input / output types:

InputType {
    String name;
    Class<?> parameterType;
}

OutputType {
    String name;
    Class<?> argumentType;
}

To understand why these types are created, we are going to use the visual configuration of Inversion of Coupling Control to better aid understanding what is happening.

The following Module configuration represents a single input, handled by a First-Class Procedure that sends its result to an output:


In the above configuration, the First-Class Procedure is encapsulated in the Module.  All that is exposed from the Module is the Inputs and Outputs.  The resulting type of the above Module would be the following:
  • Input named "Input" with a parameter passed to the First-Class Procedure
  • Output named "Output" with the argument provided by the result of the First-Class Procedure execution
This, however, provides little improvement on the First-Class Procedure interface.

What becomes useful is the encapsulation of multiple First-Class Procedures to undertake functionality of the Module:


While a new procedure was included within the Module, there was no change to the interface of the Module.  Other configuration using the Module would be unaware of the internal addition of another First-Class Procedure.

We also need not limit ourselves to single inputs and outputs.   We could have an arbitrarily complex Module that has multiple Inputs and Outputs:


The resulting Module encapsulated the detail to have the following interface:
  • Input "Input"
  • Input "Input-2"
  • Output "Output"
  • Output "Output-2"
  • Output "Output-3"

Module Type

The resulting type for the Module is the following:

SectionType {
    InputType[] inputs;
    OutputType[] outputs
}
Note that OfficeFloor's naming is derived from its foundation in business concepts and subsequently calls a Module a "Section".

The Module (Section) has multiple inputs and multiple outputs.  These inputs/outputs can then be connected to respective outputs/inputs of other Modules.

Furthermore, Modules may themselves contain other Modules.  As inputs/outputs are connected for composition, Modules have the same input/output connectivity as First-Class Procedures.  The following configuration demonstrates embedding the Module at the start of this article within another Module:


Whether it is the Module containing a single First-Class Procedure or two First-Class Procedures is encapsulated and not of concern within the above configuration.  The use of the Module is only on the Inputs / Outputs exposed by the Module.  The rest of the complexity of the Module is encapsulated. This allows modularising the application's complexity.

First-Class Module

So the title mentioned "First-Class Modules", yet we've only discussed visually wiring together the Modules.

To essentially be "First-Class" the Module needs to be assigned to a variable.  Yes, there are other conditions.  However, for me, this is the simplest way of thinking about something being first class.

Well the above graphical configuration is built on Sections (Modules) being configured together programmatically.  The graphical configuration is actually a layer above the First-Class Modules (Sections) to enable easier comprehension of how the application is modularised.

You can see this in OfficeFloor's implementation of the graphical configuration used above in this article.  The above graphical configuration is via an Activity. An Activity is a specific specialisation of a Section (ActivityLoaderImpl source here).  The Activity translates the XML from the graphical configuration into the creation of Sections, First-Class Procedures, Inputs, Outputs.  Each of these in the Activity implementation are assigned to variables, stored in data structures, passed to functions, returned from functions, etc.  This makes the Section (Module) essentially "First-Class".

This input / output interface based on continuations is extremely flexible.  It is so much so that First-Class Procedures themselves are also just a specialised implementation of a Section (see ProcedureEmployer).

Summary

We have seen how we can encapsulate First-Class Procedures within First-Class Modules, and even First-Class Modules within themselves.

We have shown how the graphical configuration is actually taking advantage of the "First-Class" nature.  The graphical configuration is actually a higher level composition that provides both:
  • easier to comprehend modularising of the application
  • quicker configuration of the application (effectively just draw lines for composition)
Note that it is quite possible to programmatically configure up our application.  However, this requires understanding First-Class Procedures / Modules in significantly more depth.  Much more than junior developers may want to initially.

The graphical configuration of First-Class Modules, therefore, provides the simplicity for building modularised applications.  This is without having to deal with the complexity of the underlying constructs.  Something I'm finding other composition strategies are still having trouble with.

In the next article we look at how First-Class Modules can provide composition of varying existing composition strategies.  You may find that existing composition strategies only really consider programming in the small, rather than programming in the much larger - where First-Class Modules become a lot more effective in modularising and simplifying your applications.

Thursday, 21 November 2019

First-Class Procedure Type System for Composition

This is the first article in a series looking at the Inversion of Coupling Control type system for composition.  The series will demonstrate how the resulting type system allows for easy composition.  This avoids much of the complexity of Functional / Object-Oriented composition.  The resulting type system and it's resulting composition is simple enough even for junior developers to comprehend.

This series has four articles:

  1. This article discussing the First-Class Procedure type system
  2. First-Class Module
  3. Demonstration application
  4. The underlying theoretical model for composition

First-Class Procedure

This article will look at the type system and composition of First-Class Procedures.

We've previously talked about the OO Matrix and how the method (and for that matter the function) suffers from coupling. We've also discussed how this coupling can be reduced by Inversion of Coupling Control. We've also shown how these inverted methods/functions can be weaved seamlessly together. We've even seen the industry moving towards these concepts with microservices.

What we haven't yet discussed is the type system and composition available with First-Class Procedures.

To discuss this, let's start with the well known concept of Dependency Injection.

Dependency Injection

Meta-data of dependency injection describes a list of dependencies with the following three attributes:
  • Field (or constructor parameter) to inject the dependency (providing the dependency's name - e.g. field name)
  • Type of the dependency
  • Optional qualifier (distinguishes dependencies of the same type)
With this information, the matching to dependencies can be undertaken. Note, some dependency injection frameworks have improvements on this.  However, the above meta-data is typically adequate for auto-wiring dependencies of the object.

Continuation Injection

Continuation Injection reduces a function/method invocation to a similarly simple set of attributes as Dependency Injection.

As only a single parameter can be passed (remaining are dependency injected), there is only one type required.   This is the optional parameter type.

Also, the continuations from the First-Class Procedure are all named.

Note that auto-wiring continuations is deemed error prone.   Automatically wiring continuation to matching First-Class Procedures requires differing parameter types for each continuation in the system.  In practice, most of the time it is the same simple domain data types being passed around.   So you end up having to qualify every continuation.

Furthermore, qualifying continuations provides little improvement on reducing complexity.  In qualifying all continuations you end up writing configurations for each continuation. In other words, you end up providing a mapping of each continuation name to servicing First-Class Procedure.  This configuration is very error prone.  We will show how this is made less error prone and easily comprehensible shortly.

Therefore, each required continuation by the First-Class Procedure is described with the following meta-data:
  • Name of the continuation
  • Type of the parameter for the continuation (i.e. type of argument sent to continuation)
Note that exceptions from the method/function are also modeled as continuations.  The type is the exception type. The name is the name of the exception type.

First-Class Procedure Type System

Putting the Continuation Injection meta-data together with the Dependency Injection meta-data, we get the following meta-data (type) information for the First-Class Procedure:

FirstClassProcedureType {
    Class<?> parameterType;
    ContinuationType[] continuations;
    DependencyType[] dependencies;
}

ContinuationType {
    String name;
    Class<?> argumentType;
}

DependencyType {
    String name;
    Class<?> objectType;
    String qualifier;
}


The above type can describe all First-Class Procedures.  As a method/function requires parameters, these are described by the DependencyType listing.  As method/functions require calling other method/functions, this is described by the ContinuationType listing.  As there is only one parameter to the First-Class Procedure, the parameter type describes the type of argument that must be supplied by invoking ContinuationType.

Note that we have not discussed Thread Injection typing.  This is actually derived from the DependencyType listing by matching on object's type to thread pool.  See Thread Injection for more information.

As we now can type the First-Class Procedure, we can look at using this type system for composition.

First-Class Procedure Composition

The composition of First-Class Procedures is focused on wiring together the continuations.  Dependency Injection provides the objects (state) to the methods/functions.  This wiring of dependencies is done separate to the continuations.  Therefore, we need only focus on continuations being wired to their servicing First-Class Procedures.

Now it is possible to do this in code and even configuration files.  However, as the system grows in complexity this listing of continuation name to servicing First-Class Procedures becomes very unwieldy.  Trying to decipher the system behaviour from lists of linkages becomes very difficult.

Therefore, we look at the First-Class Procedure as the following:
  • a processing node with an input anchor
  • varying number of output anchors for each of it's continuations
  • linkages as lines from output anchor to input anchor
This representation makes for graphical configuration of the composition.  The First-Class Procedure is nodes in the graph with lines representing the continuations between them.  Therefore, composition of First-Class Procedures is quite literally drawing lines between them.

As the graphical configuration is visually easy to comprehend, it makes it very easy for even junior developers to understand the application.

Summary

We have demonstrated how Continuation Injection simplifies invocation of methods/functions.  This simple meta-data model for Continuation Injection is similar to Dependency Injection for objects.

This simple meta-data enables a type system for First-Class Procedures.  This type system enables graphical composition of First-Class Procedures.

Furthermore, being graphical, the composition is very easy for junior developers to comprehend.

The next article will discuss how the First-Class Procedure type system is actually made more general to enable modularising of the application.  However, these modules still maintain a similar type system for inclusion in the graphical configuration.