Is it possible to append terminals retrieved from a text file to a lexicon in Rascal? This would happen at run time, and I see no obvious way to achieve this. I would rather keep the data separate from the Rascal project. For example, if I had read in a list of countries from a text file, how would I add these to a lexicon (using the lexical keyword)?
In the data-dependent version of the Rascal parser this is even easier and faster but we haven't released this yet. For now I'd write a generic rule with a post-parse filter, like so:
rascal>set[str] lexicon = {"aap", "noot", "mies"};
set[str]: {"noot","mies","aap"}
rascal>lexical Word = [a-z]+;
ok
rascal>syntax LexiconWord = word: Word w;
ok
rascal>LexiconWord word(Word w) { // called when the LexiconWord.word rule is use to build a tree
>>>>>>> if ("<w>" notin lexicon)
>>>>>>> filter; // remove this parse tree
>>>>>>> else fail; // just build the tree
>>>>>>>}
rascal>[Sentence] "hello"
|prompt:///|(0,18,<1,0>,<1,18>): ParseError(|prompt:///|(0,18,<1,0>,<1,18>))
at $root$(|prompt:///|(0,64,<1,0>,<1,64>))
rascal>[Sentence] "aap"
Sentence: (Sentence) `aap`
rascal>
Because the filter function removed all possible derivations for hello, the parser eventually returns a parse error on hello. It does not do so for aap which is in the lexicon, so hurray. Of course you can make interestingly complex derivations with this kind of filtering. People sometimes write ambiguous grammars and use filters like so to make it unambiguous.
Parsing and filtering in this way is in cubic worst-case time in terms of the length of the input, if the filtering function is in amortized constant time. If the grammar is linear, then of course the entire process is also linear.
A completely different answer would be to dynamically update the grammar and generate a parser from this. This involves working against the internal grammar representation of Rascal like so:
set[str] lexicon = {"aap", "noot", "mies"};
syntax Word = ; // empty definition
typ = #Word;
grammar = typ.definitions;
grammar[sort("Word")] = { prod(sort("Word"), lit(x), {}) | x <- lexicon };
newTyp = type(sort("Word"), grammar);
This newType is a reified grammar + type for the definition of the lexicon, and which can now be used like so:
import ParseTree;
if (type[Word] staticGrammar := newType) {
parse(staticGrammar, "aap");
}
Now having written al this, two things:
I think this may trigger unknown bugs since we did not test dynamic parser generation, and
For a lexicon with a reasonable size, this will generate an utterly slow parser since the parser is optimized for keywords in programming languages and not large lexicons.
Related
Could someone help me with using context free grammars. Up until now I've used regular expressions to remove comments, block comments and empty lines from a string so that it can be used to count the PLOC. This seems to be extremely slow so I was looking for a different more efficient method.
I saw the following post: What is the best way to ignore comments in a java file with Rascal?
I have no idea how to use this, the help doesn't get me far as well. When I try to define the line used in the post I immediately get an error.
lexical SingleLineComment = "//" ~[\n] "\n";
Could someone help me out with this and also explain a bit about how to setup such a context free grammar and then to actually extract the wanted data?
Kind regards,
Bob
First this will help: the ~ in Rascal CFG notation is not in the language, the negation of a character class is written like so: ![\n].
To use a context-free grammar in Rascal goes in three steps:
write it, like for example the syntax definition of the Func language here: http://docs.rascal-mpl.org/unstable/Recipes/#Languages-Func
Use it to parse input, like so:
// This is the basic parse command, but be careful it will not accept spaces and newlines before and after the TopNonTerminal text:
Prog myParseTree = parse(#Prog, "example string");
// you can do the same directly to an input file:
Prog myParseTree = parse(#TopNonTerminal, |home:///myProgram.func|);
// if you need to accept layout before and after the program, use a "start nonterminal":
start[Prog] myParseTree = parse(#start[TopNonTerminal], |home:///myProgram.func|);
Prog myProgram = myParseTree.top;
// shorthand for parsing stuff:
myProgram = [Prog] "example";
myProgram = [Prog] |home:///myLocation.txt|;
Once you have the tree you can start using visit and / deepmatch to extract information from the tree, or write recursive functions if you like. Examples can be found here: http://docs.rascal-mpl.org/unstable/Recipes/#Languages-Func , but here are some common idioms as well to extract information from a parse tree:
// produces the source location of each node in the tree:
myParseTree#\loc
// produces a set of all nodes of type Stat
{ s | /Stat s := myParseTree }
// pattern match an if-then-else and bind the three expressions and collect them in a set:
{ e1, e2, e3 | (Stat) `if <Exp e1> then <Exp e2> else <Exp e3> end` <- myExpressionList }
// collect all locations of all sub-trees (every parse tree is of a non-terminal type, which is a sub-type of Tree. It uses |unknown:///| for small sub-trees which have not been annotated for efficiency's sake, like literals and character classes:
[ t#\loc?|unknown:///| | /Tree t := myParseTree ]
That should give you a start. I'd go try out some stuff and look at more examples. Writing a grammar is a nice thing to do, but it does require some trial and error methods like writing a regex, but even more so.
For the grammar you might be writing, which finds source code comments but leaves the rest as "any character" you will need to use the longest match disambiguation a lot:
lexical Identifier = [a-z]+ !>> [a-z]; // means do not accept an Identifier if there is still [a-z] to add to it; so only the longest possible Identifier will match.
This kind of context-free grammar is called an "Island Grammar" metaphorically, because you will write precise rules for the parts you want to recognize (the comments are "Islands") while leaving the rest as everything else (the rest is "Water"). See https://dl.acm.org/citation.cfm?id=837160
So I have a grammar inside a one-dimensional array, given by the form
struct array
{
char left;
char right[3];
char number;
}
Example:
array.left = 'A';
array.right = "BC";
array.number = insert_some_conventional_null_character_here
This is translated to:
A->BC
------
Other examples:
A->3
C->BDE
X->9
Also, array.number is bounded by [0, 9].
array.right and array.left are literals in the interval [A, Z].
I need to return a linked-list containing all rules(grammar components) applied to get from an input string, called startString to another input string called stopString.
As you can see, this grammar is not given in the Chomsky Normal Form and I believe I cannot translate it into CNF because the grammar would change and I cannot return the linked list requested by the program.
How should I proceed? Just as a Post-Scriptum, there are at most 1000 such rules inside the grammar, so I guess that a recursive parser might not be the way to go. I've asked before and I was told to read about CYK algorithm, which I did. This is a problem I was given as a project. Please keep in mind I just started this level of programming. However, I do have all the basic knowledge.
I have not messed with building languages or parsers in a formal way since grad school and have forgotten most of what I knew back then. I now have a project that might benefit from such a thing but I'm not sure how to approach the following situation.
Let's say that in the language I want to parse there is a token that means "generate a random floating point number" in an expression.
exp: NUMBER
{$$ = $1;}
| NUMBER PLUS exp
{$$ = $1 + $3;}
| R PLUS exp
{$$ = random() + $3;}
;
I also want a "list" generating operator that will reevaluate an "exp" some number of times. Maybe like:
listExp: NUMBER COLON exp
{
for (int i = 0; i < $1; i++) {
print $3;
}
}
;
The problem I see is that "exp" will have already been reduced by the time the loop starts. If I have the input
2 : R + 2
then I think the random number will be generated as the "exp" is parsed and 2 added to it -- lets say the result is 2.0055. Then in the list expression I think 2.0055 would be printed out twice.
Is there a way to mark the "exp" before evaluation and then parse it as many times as the list loop count requires? The idea being to get a different random number in each evaluation.
Your best bet is to build an AST and evaluate the entire AST at the end of the parse. In-line evaluation is only possible for very simple (i.e. "calculator-like") projects.
Instead of an AST, you could construct code for a stack- or three-address- virtual machine. That's generally more efficient, particularly if you intend to execute the code frequently, but the AST is a lot simpler to construct, and executing it is a single depth-first scan.
Depending on your language design there are at least 5 different points at which a token in the language could be bound to a value. They are:
Pre-processor (like C #define)
Lexer: recognise tokens
Parser: recognise token structure, output AST
Semantic analysis: analyse AST, assign types and conversions etc
Code generation: output executable code or execute code directly.
If you have a token that can occur multiple times and you want to assign it a different random value each time, then phase 4 is the place to do it. If you generate an AST, walk the tree and assign the values. If you go straight to code generation (or an interpreter) do it then.
I'm learning to write a simple parser-combinator. I'm writing the rules from bottom up and write unit-tests to verify as I go. However, I'm blocked at using repsep() with whitespace as the separator.
object MyParser extends RegexParsers {
lazy val listVal:Parser[List[String]]=elem('{')<~repsep("""\d+""".r,"""\s+""".r)~>elem('}')
}
The rule was simplified to illustrate the problem. When I feed the parser with "{1 2 3}", it always complains that it doesn't match:
[1.4] failure: `}' expected but 2 found
I'm wondering what's the correct way of writing a rule as I described?
Thanks
By default, RegexParsers-derived parsers skip whitespace before attempting to match any terminal symbol. Unless your whitespace interpretation is unusual, you can just work with that. If the particular character (sequences) you wish to treat as ignored whitespace is something other than the default (\s+), you can override the projected val whiteSpace: Regex = ... value in your RegexParsers parser. If you do not what any such whitespace skipping to occur, override def skipWhitespace = false.
Edit: So yes, changing this:
repsep("""\d+""".r,"""\s+""".r)
to this:
rep("""\d+""".r)
and leaving everything else defined in RegexParsers unchanged should do what you want.
By the way, the common use of repsep is for things like comma-separated lists where you need to ensure the commas are there but don't need to keep them in the resulting parse tree (or AST).
I have read the GOLD Homepage ( http://www.devincook.com/goldparser/ ) docs, FAQ and Wikipedia to find out what practical application there could possibly be for GOLD. I was thinking along the lines of having a programming language (easily) available to my systems such as ABAP on SAP or X++ on Axapta - but it doesn't look feasible to me, at least not easily - even if you use GOLD.
The final use of the parsed result produced by GOLD escapes me - what do you do with the result of the parse?
EDIT: A practical example (description) would be great.
Parsing really consists of two phases. The first is "lexing", which convert the raw strings of character in to something that the program can more readily understand (commonly called tokens).
Simple example, lex would convert:
if (a + b > 2) then
In to:
IF_TOKEN LEFT_PAREN IDENTIFIER(a) PLUS_SIGN IDENTIFIER(b) GREATER_THAN NUMBER(2) RIGHT_PAREN THEN_TOKEN
The parse takes that stream of tokens, and attempts to make yet more sense out of them. In this case, it would try and match up those tokens to an IF_STATEMENT. To the parse, the IF _STATEMENT may well look like this:
IF ( BOOLEAN_EXPRESSION ) THEN
Where the result of the lexing phase is a token stream, the result of the parsing phase is a Parse Tree.
So, a parser could convert the above in to:
if_statement
|
v
boolean_expression.operator = GREATER_THAN
| |
| v
V numeric_constant.string="2"
expression.operator = PLUS_SIGN
| |
| v
v identifier.string = "b"
identifier.string = "a"
Here you see we have an IF_STATEMENT. An IF_STATEMENT has a single argument, which is a BOOLEAN_EXPRESSION. This was explained in some manner to the parser. When the parser is converting the token stream, it "knows" what a IF looks like, and know what a BOOLEAN_EXPRESSION looks like, so it can make the proper assignments when it sees the code.
For example, if you have just:
if (a + b) then
The parser could know that it's not a boolean expression (because the + is arithmetic, not a boolean operator) and the parse could throw an error at this point.
Next, we see that a BOOLEAN_EXPRESSION has 3 components, the operator (GREATER_THAN), and two sides, the left side and the right side.
On the left side, it points to yet another expression, the "a + b", while on the right is points to a NUMERIC_CONSTANT, in this case the string "2". Again, the parser "knows" this is a NUMERIC constant because we told it about strings of numbers. If it wasn't numbers, it would be an IDENTIFIER (like "a" and "b" are).
Note, that if we had something like:
if (a + b > "XYZ") then
That "parses" just fine (expression on the left, string constant on the right). We don't know from looking at this whether this is a valid expression or not. We don't know if "a" or "b" reference Strings or Numbers at this point. So, this is something the parser can't decided for us, can't flag as an error, as it simply doesn't know. That will happen when we evaluate (either execute or try to compile in to code) the IF statement.
If we did:
if [a > b ) then
The parser can readily see that syntax error as a problem, and will throw an error. That string of tokens doesn't look like anything it knows about.
So, the point being that when you get a complete parse tree, you have some assurance that at first cut the "code looks good". Now during execution, other errors may well come up.
To evaluate the parse tree, you just walk the tree. You'll have some code associated with the major nodes of the parse tree during the compile or evaluation part. Let's assuming that we have an interpreter.
public void execute_if_statment(ParseTreeNode node) {
// We already know we have a IF_STATEMENT node
Value value = evaluate_expression(node.getBooleanExpression());
if (value.getBooleanResult() == true) {
// we do the "then" part of the code
}
}
public Value evaluate_expression(ParseTreeNode node) {
Value result = null;
if (node.isConstant()) {
result = evaluate_constant(node);
return result;
}
if (node.isIdentifier()) {
result = lookupIdentifier(node);
return result;
}
Value leftSide = evaluate_expression(node.getLeftSide());
Value rightSide = evaluate_expression(node.getRightSide());
if (node.getOperator() == '+') {
if (!leftSide.isNumber() || !rightSide.isNumber()) {
throw new RuntimeError("Must have numbers for adding");
}
int l = leftSide.getIntValue();
int r = rightSide.getIntValue();
int sum = l + r;
return new Value(sum);
}
if (node.getOperator() == '>') {
if (leftSide.getType() != rightSide.getType()) {
throw new RuntimeError("You can only compare values of the same type");
}
if (leftSide.isNumber()) {
int l = leftSide.getIntValue();
int r = rightSide.getIntValue();
boolean greater = l > r;
return new Value(greater);
} else {
// do string compare instead
}
}
}
So, you can see that we have a recursive evaluator here. You see how we're checking the run time types, and performing the basic evaluations.
What will happen is the execute_if_statement will evaluate it's main expression. Even tho we wanted only BOOLEAN_EXPRESION in the parse, all expressions are mostly the same for our purposes. So, execute_if_statement calls evaluate_expression.
In our system, all expressions have an operator and a left and right side. Each side of an expression is ALSO an expression, so you can see how we immediately try and evaluate those as well to get their real value. The one note is that if the expression consists of a CONSTANT, then we simply return the constants value, if it's an identifier, we look it up as a variable (and that would be a good place to throw a "I can't find the variable 'a'" message), otherwise we're back to the left side/right side thing.
I hope you can see how a simple evaluator can work once you have a token stream from a parser. Note how during evaluation, the major elements of the language are in place, otherwise we'd have got a syntax error and never got to this phase. We can simply expect to "know" that when we have a, for example, PLUS operator, we're going to have 2 expressions, the left and right side. Or when we execute an IF statement, that we already have a boolean expression to evaluate. The parse is what does that heavy lifting for us.
Getting started with a new language can be a challenge, but you'll find once you get rolling, the rest become pretty straightforward and it's almost "magic" that it all works in the end.
Note, pardon the formatting, but underscores are messing things up -- I hope it's still clear.
I would recommend antlr.org for information and the 'free' tool I would use for any parser use.
GOLD can be used for any kind of application where you have to apply context-free grammars to input.
elaboration:
Essentially, CFGs apply to all programming languages. So if you wanted to develop a scripting language for your company, you'd need to write a parser- or get a parsing program. Alternatively, if you wanted to have a semi-natural language for input for non-programmers in the company, you could use a parser to read that input and spit out more "machine-readable" data. Essentially, a context-free grammar allows you to describe far more inputs than a regular expression. The GOLD system apparently makes the parsing problem somewhat easier than lex/yacc(the UNIX standard programs for parsing).