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For example, given a sentence in the English language, such as the dog barked , we might transform the sentence into a sequence of (part-of-speech word) 2-tuples, ((DEFINITE_ARTICLE, "the"), (NOUN, "dog"), (VERB, "barked")) We would then perform syntactic analysis to see if this is a valid English sentence In this case it is, but our parser would have to reject, say, the barked dog The lexing phase is used to convert the data into a stream of tokens In typical cases, each token holds at least two pieces of information: the token s type (the kind of data or language construct being represented), and the token s value (which may be empty if the type stands for itself for example, a keyword in a programming language) The parsing phase is where a parser reads each token and performs some semantic action The parser operates according to a prede ned set of grammar rules that de ne the syntax that the data is expected to follow (If the data doesn t follow the syntax rules the parser will correctly fail) In multiphase parsers, the semantic action consists of building up an internal representation of the input in memory (called an Abstract Syntax Tree AST), which serves as input to the next phase Once the AST has been constructed, it can be traversed, for example, to query the data, or to write the data out in a different format, or to perform computations that correspond to the meanings encoded in the data Data formats and DSLs (and programming languages generally) can be described using a grammar a set of syntax rules that de ne what is valid syntax for the data or language Of course, just because a statement is syntactically valid doesn t mean that it makes sense for example, the cat ate democracy is syntactically valid English, but meaningless Nonetheless, being able to de ne the grammar is very useful, so much so that there is a commonly used syntax for describing grammars BNF (Backus Naur Form) Creating a BNF is the rst step to creating a parser, and although not formally necessary, for all but the most trivial grammars it should be considered essential Here we will describe a very simple subset of BNF syntax that is suf cient for our needs In a BNF there are two kinds of item: terminals and nonterminals A terminal is an item which is in its nal form, for example, a literal number or string A nonterminal is an item that is de ned in terms of zero or more other items (which themselves may be terminals or nonterminals) Every nonterminal must ultimately be de ned in terms of zero or more terminals Figure 141 shows an example BNF that de nes the syntax of a le of attributes , to put things into perspective.

In practice, parsing English and other natural languages is a very dif cult problem; see, for example, the Natural Language Toolkit (wwwnltkorg) for more information

[ Team LiB ]

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There are two ways to describe the integration between WCF and WF From the WCF perspective, WF enables you to implement a service as a work ow From the WF viewpoint, WCF enables you to service enable a work ow Both are saying the same thing: That is, by combining WCF and WF, you model and implement logic that is exposed through a standards-based interface Your logic can be compatible with many standards, such as SOAP, JSON, or X509, and can be hosted by IIS, WAS, Windows Service, or any other WCF-supported hosting environment In addition, the tracing, diagnostics, and unit testing tools available in Visual Studio can also be used with WCF and WF WF integrates with WCF by leveraging WCF extensibility So although WF knows about WCF, WCF does not know about WF The integration in NET 35 is by WF plugging deeply into the WCF extensibility points With NET 35, WF updated its visual modeling tools in Visual Studio and added runtime support that leverages WCF Three elements are needed for integration between WCF and WF First, you need a way to model service interactions WF is good at de ning a

ATTRIBUTE_FILE ATTRIBUTE NAME VALUE ::= ::= ::= ::=

(ATTRIBUTE '\n')+ NAME '=' VALUE [a-zA-Z]\w* 'true' | 'false' | \d+ | [a-zA-Z]\w*

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The CLDC Specification version 10, completed in May 2000, was the result of the work of a Java Community Process (JCP) expert group JSR 30 consisting of a large number of industrial partners The following 18 companies (in alphabetical order) were members of the CLDC 10 expert group:

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