Book: Immutable Data Structures in C# and F# By Tomas Petricek

The Real World Functional Programming book explains essential concepts of this paradigm using examples in C# 3.0 and F#. In this article we look at immutability, which stands behind the clarity of functional programs.

Title                                     Real World Functional Programming
Author                                 Tomas Petricek
Publisher                             Manning
Published                             May 2009 (expected)
Electronic version               via Manning Early Access program
ISBN-13                              978-1933988924
Price                                    USD 49.99

This is a chapter excerpt from Real World Functional Programming authored by Tomas Petricek and published by Manning Publications. The content has been reformatted and edited to match the standard CodeProject article format.

In this article we'll take a look at one of the several concepts that together form the 'functional programming' paradigm. You probably noticed that the term functional programming has appeared in many areas recently - the C# 3.0 and LINQ have been largely influenced by this paradigm and many of the libraries that enable and simplify writing parallel code rely on functional ideas. Microsoft also recently announced that Visual Studio 2010 will include F# - a functional language - out of the box.

The functional paradigm is based on different principles than the imperative style. You may know some of the concepts already - for example 'anonymous functions' from C# 3.0 give us the ability to use function as an argument to a method. In functional programming, the ability to write functions that take other functions as an argument or return them as a result is one of the basic principles.

Immutable Data Structures

In this article we'll look at another concept that influences the way functional programs are written, which is 'immutability.' This means that objects used in the program cannot be modified once they are constructed. This has important practical consequences - the code written in this way can be more easily parallelized, because it doesn't suffer from race conditions. Immutability also makes the code more readable, because changes in the program state are more visible in the code, so we can see which operation changes the state and which doesn't. In this article, we'll look at the simplest functional data structure, a 'tuple' and we'll use it to demonstrate how we can work with immutable data types. We'll start by looking at examples in F#, but we'll also examine how to implement and use the same type in C# 3.0. We'll see more common functional data structures in the upcoming chapters.

I pointed out in the first chapter how we can write a function for processing data using immutable data types or objects. Instead of changing the internal state of the object (which isn't possible, because it is immutable) the processing function simply creates and returns a new object. The internal state of this new object will be initialized to a copy of the original object with a few differences in places where we wanted to change the state. This sounds a little abstract, but you'll see what I mean shortly in an example.

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Courtesy: Codeproject.com