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For example, the functional programming design methodology places great importance on constructs that are compositional. For example, in F#, you can map a function over a list of lists as follows: let map2 f inp = List.map (List.map f) inp This is a simple example of the inherent compositionality of generic functions: the expression List.map f produces a new function that can in turn be used as the argument to List.map. Understanding compositionality is the key to understanding much of what goes by the name of functional programming. For example, functional programmers aren t interested in a lack of side effects just for the sake of it instead, they like programs that don t use side effects because such program tend to be more compositional than those that do. Functional programming often goes further by emphasizing transformations that preserve behavior. For example, you expect to be able to make the following refactorings to your code regardless of the function f or of the values inp, x, or rest: List.hd (x :: rest) x List.filter f (List.concat inp)

It is often necessary to convert string data between different formats. For example, files read using the ReadLine method on the System.IO.StreamReader type are read with respect to a Unicode encoding; you can specify this when creating the StreamReader; if left unspecified, the .NET libraries attempt to determine the encoding for you. One common requirement is to convert strings to and from ASCII representations, assuming that all the characters in the strings are in the ASCII range 0 to 127. You can do this using System.Text.Encoding.ASCII.GetString and System.Text.Encoding.ASCII.GetBytes. Table 10-8 shows the predefined encodings and commonly used members in the System. Text.Encoding type. Table 10-8. Types and Members Related to Unicode Encodings

List.concat (List.map (List.filter f) inp)

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Caution BitKeeper stores the very latest version, forks (branches), and all other development artifacts for the MySQL source code. It is what the MySQL AB developers use on a daily basis to store their revisions to the code. As such, it isn t always in the most stable of states. Use caution when choosing this method. Most of the new features will be incomplete or in some stage of refinement. If you have to have a stable build, use the code snapshots (described later in this chapter) or a release of the source code.

s 11 to 19 deal with applied topics in F# programming 11, Working with Windows Forms and Controls, shows how to design and build graphical user interface applications using F# and the NET Windows Forms library We also show how to design new controls using standard object-oriented design patterns and how to script applications using the controls offered by the NET libraries directly 12, Working with Symbolic Representations, applies some of the techniques from 9 and 11 in two case studies The first is symbolic expression differentiation and rendering, an extended version of a commonly used case study in symbolic programming The second is verifying circuits with propositional logic, where you will learn how to use symbolic techniques to represent digital circuits, specify properties of these circuits, and verify these properties using binary decision diagrams (BDDs).

Equations like these can be a source of useful documentation and test cases, and in some situations they can even be used to specify entire programs. Furthermore, good programmers routinely manipulate and optimize programs in ways that effectively assume these transformations are valid. If these transformations are not valid, then it s easy to accidentally insert bugs when you re working with code. That said, many important transformation equations aren t guaranteed to always be valid they typically hold only if additional assumptions are made for example, in the first example, the expression rest shouldn t have side effects. Transformational reasoning works well for some kinds of code and badly for others. Table 19-1 lists some of the F# and .NET constructs that are highly compositional and for which transformational reasoning tends to work well in practice. Table 19-1. Some Compositional F# Library Constructs Amenable to Equational Reasoning

The first thing you need to do is remember the old adage about patience. This process can be a bit frustrating as it is very error prone. Although it seems to work well for most people, some users have had trouble getting and using the BitKeeper client. If you stick to my instructions, you shouldn t have any problems.

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