That was certainly all a bit abstract and theoretical for many readers. Now we are ready to put some meat on these abstract concepts and implement the parser based on that grammar. We first add to our class Token that holds the information about the tokens in the input. Note how we made the fields public final.
A recursive-descent parser consists of a series of functions, usually one for each grammar rule. However, recursive-descent is less efficient for expression syntaxes, especially for languages with lots of operators at different precedence levels.
With one function per rule, you can easily end up with lots of calls even for short, trivial expressions, just to get to the right level in the grammar. In the early seventies, Vaughan Pratt published an elegant improvement to recursive-descent in his paper Top-down Operator Precedence.
And yes, there will be benchmarks too. Here, the right binding power is zero, and the next token is an operator, the implementation of which could look like: This causes the expression parser to treat everything with a higher power as a subexpression, and return its result.
The method then adds the left value from the literal, in this case to the return value from the expression parser, and returns the result. The end of the program is indicated by a special marker token, with binding power zero lower than any other token.
This makes sure that the expression parser stops when it reaches the end of the program. To use it, we need a tokenizer that can generate the right kind of token objects for a given source program. We need a few more token classes: We also need to add the classes to the tokenizer: The parser now understands the four basic math operators, and handles their precedence correctly.
Adding exponentiation is a bit trickier; first, we need to tweak the tokenizer to identify the two-character operator: A bigger problem is that the operator is right-associative that it, it binds to the right. With the new token implementations, the parser will return parse trees: Pratt uses associative arrays instead, and associates the operations with their tokens.
In Python, it could look something like: The identifier and the binding power are inserted as class attributes, and will thus be available in all instances of that class. We also need to update the tokenizer, to make it use classes from the registry: All other tokens have their own classes.
To do that, we can define them as ordinary functions, and then simply plug them into the symbol classes, one by one. The only thing that differs is the binding power, so we can simplify things quite a bit by moving the repeated code into a helper function: We can use a plain lambda for this: To do this, we first need a fancier tokenizer.Recursive Descent Parsing Parsing, you will recall, is the process of turning a stream of tokens into an abstract syntax tree.
Any parsing technique requires a grammar --a formal, detailed definition of what sequence of symbols constitutes a syntactically correct program.
C++ I can't figure out how to write a recursive descent parser for the following grammar: Program> -> Schemes: Facts. algorithm to parse a BL program and construct the corresponding Program object) 21 March !
OSU CSE! 3! A Recursive-Descent Parser Can you write the tokenizer for this language, so every number, add-op, and mult-op is a token? I know modern parser generators can do this as well.
It's just easier in a recursive descent parser. Learning to use parser generator is a learning experience in itself. Most can be pretty complicated to use, once you get past the basics. Yet nearly every programmer can understand a recursive descent parser.
Writing a Simple Recursive Descent Parser 30 July — A simple implementation of a field-based query string, with binary operations, using a recursive descent parser — 5-minute read Someone asked a question recently on the local ruby list.
Jun 29, · Blog TOC This post is one in a series on using LINQ to write a recursive-descent parser for SpreadsheetML formulas. You can find the complete list of posts here. For a typical professional developer, there are lots of benefits to understanding grammars, recursive descent parsers, and syntax trees.