Hitchhiker's Guide to Software Architecture and Everything Else - by Michael Stal

Monday, April 12, 2010

Functional Programming

In the last months I have intensified my skills in functional programming. My favourite programming languages have been Scala and F# so far. Only a few years ago I recovered my Lisp abilities when I had been ill for some weeks.  It is interesting how many functional languages currently evolve. Guess, it is closely related to the availabilty of virtual platforms such as the JVM and the CLR. No need to develop a whole bunch of APIs or IDEs anymore. just use the Java SDK or the .NET Framework Classes, and provide some plug-ins for Visual Studio, Eclipse, NetBeans, or any other IDE of your choice. A real paradise for language developers. Reminds me of the Eighties when all those OO languages appeared such as C++, Smalltalk, Objective C, or Eiffel. I anticipated several years ago that this would happen. Interesting, you might ask, but how is all this related to architecture? A lot if you ask me. Remember the book on object-oriented design patterns by Erich Gamma, Ralph Johnson, Richard Helm and the unforgettable John Vlissides. This book (as well as hopefully our POSA books) have changed the world in  that they brought software architecture in people’s minds. The same will happen through functional programming.

Functional programming enforces another way of thinking. Functions are first class entitites that can be assigned to values, passed as arguments to higher-order functions, or just created anonymously (called: closures). In pure functional programming there are no variables anymore, just immutable values. All of this was already specified by Church & all in the Thirties.  While the first functional languages such as Lisp, ML were difficult to understand for everyday programmers, new functional languages deviate from the academic approach and turn into hybrid languages that integrate object-oriented features, and permit mutability by supporting imperative programming styles.

Sometimes mutability is important such as for I/O and GUI operations or logging/tracing. But there are many situations where mutability is like shooting yourself in the foot. Think of race conditions in multithreaded applications. Most accidental complexity is caused by mutable state. No mutable state implies no race conditions. Or think of side-effects that make your application hard to understand and debug. These side-effects are simply missing in functional languages. Think of testing or validating your functionality. Guess why Joshua Bloch spends so much space in his book on Effective Java illustrating how to make Java classes immutable.

In contrast to object-oriented approaches functions are used to abstract functionality and function composition is the basic means of composing artifacts. That’s a perfect extension to object oriented abstraction and composition.  Hybrid languages such as Scala use this combination to make building internal DSLs surprisingly easy. For instance, the Actor functionality looks like an integral constituent of the language, while in fact it is just a library. If you wonder what actors are: they can be considered abstract tasks or objects running on their own threads. They do not provide any possibility for reading or changing their internal state. The only way to communicate with actors is by exchanging messages´with them. If these messages are immutable values, there is no chance of side-effects.  What a perfect way for implementing multithreaded applications.

Another famous example for functional features used to provide an internal DSL is LINQ (Language Integrated Query) in Microsoft .NET. Using extension functions, closures, anonymous types, and type inference helped to seamlessly integrate LINQ into languages such as C#.

Sometimes you need to deal with state. Languages like Clojure also support Shared Transactional Memory, a good way to encapsulate all state changes within transactions.

What makes the functional paradigma so effective, is it’s succinctness. As an example we’ll use F#:

let rec fib x =

     if x < 2 then 1

     else fib (x–1) + fib (x-2)

let results = Array.map fib [| 1 .. 40 |]

The code above introduces a recursive function for calculating fibonacci numbers, then builds an array containing the first fourty fibonacci numbers. Try this with Java, C# or C++.

Many problems can be described in a much more natural way using functional features.

Thus we already know several aspects where functional languages are beneficial for the architect:

  • introducing internal DSLs
  • Parallel and Asynchronous Programming (e.g, targeting Multicores)
  • Implementing some parts of an architecture in a much more succinct way
  • Improving testability
  • Understandability of design (expressiveness, simplicity)

As mentioned previously, functional approaches do not represent a panacea. Neither does Object-Oriented Programming. But they  surely offer an excellent extension to imperative or object-oriented design and implementation. Consider them a perfect extension of Object-Orientation.

It is time to follow the advice of the Pragmatic Programmers and learn at least one additional language per year. My recommendation: focus on functional languages for this purpose.   


  • Michael, have you checked on the benefits of supporting parallelization when using functional languages? It can support an implizit approach...

    By Blogger Maik G. Seewald, at 10:03 PM  

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