Răzvan Petruescu bio photo

Răzvan Petruescu

Functional programming for the masses

Twitter LinkedIn Stackoverflow BitBucket Coursera

This is the first article in a series focused on finding and examining ideas, patterns, idioms that will increase the quality of software.

Naturally, I will dive into concepts like modularity, extensibility, design but also architectural patterns will be scrutinized.

As a first task, I chose to look into type classes and chose Scala as an instrument to facilitate my endeavor.

According to the official website, Scala is a “general purpose programming language designed to express common programming patterns in a concise, elegant, and type-safe way”.

For getting the most out of this article, basic familiarity with Scala’s syntax is required. Also object-oriented concepts like inheritance, subtyping or polymorphism should not be foreign.

Basic reasoning

One of the major breakthroughs in the history of computer programming has been the introduction of languages that offer the programmer new tools to conceptualize, to move away from the nitty-gritty details of the machine and build abstractions. These abstractions help us reason in a better way about our designs, and will also lead to more modular and decoupled programs with the benefits of easier extensibility and maintenance in the long term.

Therefore, when faced with the task of designing a new system, the programmer will attempt to ‘translate’ the concepts of the problem domain into abstractions in the solution domain. For example, when he has to design a document management system, the programmer will recognize the concept of a Document as a key abstraction in his problem/solution domain. In object-oriented jargon, he will create a Document interface. When using Scala, the Document becomes a type (in scala an interface is called a trait). For an introduction to types in Scala, read this article.

He will then discover that his abstractions carry several properties, related to the problem or application domain. In the case of the Document, it could be persisted, or you can add paragraphs to it, or it can be printed, and so on. The object-oriented world will recognize these properties as methods of an interface.

Fundamentally, the programmer will look for a way to create a contract and to enforce it across several entities that embody the essence of that contract. For example, the programmer will discover a contract called Eq for things that can be equated. The contract could define the properties == (equal) and /= (not equal) applicable for that contract. If then we have another abstraction (say, Document) and it makes sense to apply the equality functions to a document, the programmer can enforce the contract of Eq on Document.


To make things clearer, I’ll give an example.

Let’s consider the concept of aggregating. This is an abstraction since you can ‘aggregate’ many ‘things’, like, datastore columns/rows, in-memory collection elements, files, Documents, and so on.

I have defined a trait, Aggregate, which models this abstract concept. In this hypothetical example, only a couple of operations are supported: inserting into an aggregate and querying the size of the aggregate (the number of parts that comprise the aggregate).

trait Aggregate[T] {

  def insert(o: T): Aggregate[T]

  def size: Int


Since this aggregate behavior can be shared by many abstractions, the Aggregate type is parameterized, or, more formally, the operations it supports can be applied identically to different types, a characteristic which is sometimes defined as parametric polymoprphism. You can find here an introduction to parameterized types.

The usual way to model the fact that an abstraction ‘supports’ a contract is through inheritance.

trait Document extends Aggregate[Document] {

  def addParagraph(p: String): Document = ???

  def numberOfWords: Int = ???

  override def insert(o: Document): Aggregate[Document] = ???

  override def size: Int = ???

trait FileSystem extends Aggregate[FileSystem] {

  def numberOfFiles: Int = ???

  override def insert(o: FileSystem): Aggregate[FileSystem] = ???

  override def size: Int = ???

The implementations have been purposely omitted.


There are a few interesting comments to be made by looking at this example.

A first observation is the fact that Documents or FileSystems themselves represent concepts in the domain they are modeling. They have properties relevant to the problem to be solved but it can be argued that representing a Document as an aggregate of Documents is an orthogonal matter, that can ‘cut across’ many different abstractions and that does not necessarily concern the Document itself.

Furthermore, using this ‘traditional’ approach based on inheritance, for a class or a trait to be ‘member’ of an interface, it must declare that at the site of its own definition (using the extends or with keywords in our case). In other words, the Document type ‘is aware’ that it is also an aggregate. Therefore, all Document implementations will be strongly coupled to the Aggregate contract.

This raises another interesting question. What if, at some point in time, someone decides that Documents need to implement another contract? Not only that every consumer of the Document API is forced to deal with characteristics that might not be interesting to him (the Document interface becomes ‘fatter’), but also the source code of the Document needs to be changed. Also, all types implementing the Document contract (all implementations) need to be adapted to the new change (they need to implement the new contract and their source code needs to be changed too).

While it is possible, via polymorphism, or because of the elasticity of the type system, to have different clients talk only to the interface they are interested in (in our case, a method expecting a parameter of type Aggregate[Document] can be passed a Document instance because a Document can also be seen as an Aggregate[Document]), this solution will only partially mitigate some of these problems.

Adapters to the rescue

I’ll assume that the creator of the Document abstraction is aware of the aforementioned disadvantages. As an alternative, he designs an adapter that is responsible for encapsulating the Aggregate behavior of the target type.

trait AggregateAdapter[T] {

  def toAggregate(target: T): Aggregate[T]

object DocumentAggregateAdapter
  extends AggregateAdapter[Document] {

  override def toAggregate(target: Document): Aggregate[Document] = {

    new Aggregate[Document] {

      override def insert(o: Document): Aggregate[Document] = ???

      override def size: Int = ???

However, this approach comes with disadvantages, too. Leaving aside the ones that are commonly associated with the ‘Adapter’ pattern, the most important is that, ideally, the client code would want to code against the Document adaptee interface, but also retain the possibility to view the Document as an Aggregate without the forced shift that the adapter option represents.

So at this point, it seems like the designers have reached a dead end.

Closing remarks

In the second part of this article, I will show that it’s possible to have ‘the best of the two worlds’, meaning, to code against the Document interface while still being able to use the Aggregate[Document] view and at the same time, keep the Document interface decoupled and free of other orthogonal concerns.