.NET/Java PDF, Tiff, Barcode SDK Library

You could produce different derivations depending on what nonterminal you expand at each step. In the previous derivation, we chose to always expand the leftmost nonterminals, but you could just as easily expand from the right or even mix the two strategies. Usually, we stick to either left or rightmost derivation using LL or LR parsers, respectively, and if your grammar is written in a well-defined way, you will get the same parse tree. On the other hand, if given a particular derivation strategy you get more than one parse tree for a given input, the grammar is said to be ambiguous. As we mentioned in the example, recursive-descent parsers are LL(n) parsers; in other words, they perform leftmost derivation. Typically only a single look-ahead symbol is used to drive parsing these are LL(1) parsers but our example can be extended to LL(n) for some n>1, since inside a given parsing function you can retrieve several look-ahead symbols and make the appropriate parsing decisions. This is possible because our lookahead calculation is nondestructive; in other words, there is no global parsing state. Instead, we pass around the particular input string (the remaining token stream) instance on which we want to base our parsing. LR parsers are a special subset of bottom-up parsers; they read their input from left to right and produce a rightmost derivation (that is, always the rightmost nonterminal is expanded during parsing). Special subsets include Simple LR (SLR) and Look-Ahead LR (LALR; as generated by the yacc family of parser generators, including fsyacc, as you will see in the coming sections), and extensions include LR(1) (where the parse tables are typically larger because of the one symbol look-ahead), and Generalized LR (GLR), which can handle nondeterminism and ambiguous grammars.

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Figure 3-2. The Page object s ancestors and descendants (with version 2.0 partial classes) While some folks talk about partial classes supporting really big classes, this is not the real driving force behind adding the feature. It s true that a large class could be split among several physical files, but the true benefits come into the picture when you start to consider code generators. The .NET Framework is constantly generating code: code for COM Interop, code for proxies, code based on markup. The Framework team realized during version 1.0 development that they were going to be doing so much code generation that they decided to create a set of types to help them do this programmatically: System.CodeDom. The problem with generated code has always been that it can step on your toes. If you ve spent any amount of time coding traditional ASP you ve likely experienced an HTML-generating , tool squashing your server-side script blocks. Or maybe you ve added some code to the InitializeComponent method of the Page class, only to have the VS .NET Designer strip it out later. With partial classes, code generation can occur in the code generator s own file. This file is declared as being a partial definition of the class the code is being generated for, and when it comes time to compile, the compiler simply merges the files to create a single class definition in the resulting Intermediate Language (IL) that s generated. This removes any possibility of having your own code squashed. The Page object orchestrates the entire construction of the web page. It houses the process life cycle, the event infrastructure, and the hierarchical control tree that results in the generation of the web page s HTML.

We check the command-line parameters. The first argument is the database name, and the second optional argument is the fetch size used in selects for the external tables: if( args.length != 1 && args.length != 2 ) { System.err.println(" Usage: java <program_name> <database_name> [prefetch_size]"); Runtime.getRuntime().exit( 1 ); } int prefetchSize = 20; if( args.length == 2 ) { prefetchSize = Integer.parseInt( args[1] ); } System.out.println( "Prefetch size for external table: " + prefetchSize ); Connection conn = null; try { // get connection (autocommit is off ) In the try catch block, we obtain the connection, prepare our benchmark statements, and invoke the method _runBenchmark(), which contains the bulk of the logic: conn = JDBCUtil.getConnection("benchmark", "benchmark", args[0]); _prepareBenchmarkStatements( conn ); new BenchmarkReadUsingBfileAndExternalTables()._runBenchmark( conn, prefetchSize ); } finally { // release resources associated with JDBC in the finally clause. _closeBenchmarkStatements( conn ); JDBCUtil.close( conn ); } } The method _runBenchmark() times the first and the second method of the JBenchmark passing the connection and the fetch size passed in (or a default fetch size of 20): private void _runBenchmark( Connection conn, int prefetchSize ) throws Exception { Object[] params = new Object[ 1 ]; params[0] = new Integer( prefetchSize ); timeMethod( JBenchmark.FIRST_METHOD, conn, params, BFILE_DESC ); timeMethod( JBenchmark.SECOND_METHOD, conn, params, EXTERNAL_TABLE_DESC ); }

There are various limitations you cannot handle with recursive-descent parsers For instance, if you translate a left-recursive production into code, you get an infinite recursion, like so: <polynomial> ::= <polynomial> '+' <term> | <term> which would correspond to the following: let rec parsePolynomial src = let poly, src = parsePolynomial src .. Another common problem with LL(k) parsing for some k>=1 is that the grammar rules for a given nonterminal cannot start with the same symbols, or else there is no easy way to decide which rule to apply (because each is decided to be applicable upon checking k number of symbols) In such cases, left-factoring can be applied.