When defining the grammar for a language parser, how do you deal with things like comments (eg /* .... */) that can occur at any point in the text?
Building up your grammar from tags within tags seems to work great when things are structured, but comments seem to throw everything.
Do you just have to parse your text in two steps? First to remove these items, then to pick apart the actual structure of the code?
Thanks
Normally, comments are treated by the lexical analyzer outside the scope of the main grammar. In effect, they are (usually) treated as if they were blanks.
One approach is to use a separate lexer. Another, much more flexible way, is to amend all your token-like entries (keywords, lexical elements, etc.) with an implicit whitespace prefix, valid for the current context. This is how most of the modern Packrat parsers are dealing with whitespaces.
Related
I'm working on a reStructuredText transpiler in Rust, and am in need of some advice concerning how lexing should be structured in languages that have recursive structures. For example lists within lists are possible in rST:
* This is a list item
* This is a sub list item
* And here we are at the preceding indentation level again.
The default docutils.parsers.rst took the approach of scanning the input one line at a time:
The reStructuredText parser is implemented as a state machine, examining its
input one line at a time.
The state machine mentioned basically operates on a set of states of the form (regex, match_method, next_state). It tries to match the current line to the regex based on the current state and runs match_method while transitioning to the next_state if a match succeeds, doing this until it runs out of lines to scan.
My question then is, is this the best approach to scanning a language such as rST? My approach thus far has been to create a Chars iterator of the source and eat away at the source while trying to match against structures at the current Unicode scalar. This works to some extent when all I'm doing is scanning inline content, but I've now run into the realization that handling recursive body level structures like nested lists is going to be a pain in the butt. It feels like I'm going to need a whole bunch of states with duplicate regexes and related methods in many states for matching against indentations before new lines and such.
Would it be better to simply have and iterator of the lines of the source and match on a per-line basis, and if a line such as
* this is an indented list item
is encountered in State::Body, simply transition to a state such as State::BulletList and start lexing lines based on the rules specified there? The above line could be lexed for example as a sequence
TokenType::Indent, TokenType::Bullet, TokenType::BodyText
Any thoughts on this?
I don't know much about rST. But you say it has "recursive" structures. If that's that case, you can't fully lex it as a recursive structure using just state machines or regexes or even lexer generators.
But this the wrong way to think about it. The lexer's job is to identify the atoms of the language. A parser's job is to recognize structure, especially if it is recursive (yes, parsers often build trees recording the recursive structures they found).
So build the lexer ignoring context if you can, and use a parser to pick up the recursive structures if you need them. You can read more about the distinction in my SO answer about Parsers Vs. Lexers https://stackoverflow.com/a/2852716/120163
If you insist on doing all of this in the lexer, you'll need to augment it with a pushdown stack to track the recursive structures. Then what are you building is a sloppy parser disguised as lexer. (You will probably still want a real parser to process the output of this "lexer").
Having a pushdown stack actually useful if the language has different atoms in different contexts especially if the contexts nest; in this case what you want is mode stack that you change as the lexer encounters tokens that indicate a switch from one mode to another. A really useful extension of this idea is to have mode changes select what amounts to different lexers, each of which produces lexemes unique to that mode.
As an example you might do this to lex a language that contains embedded SQL. We build parsers for JavaScript; our lexer uses a pushdown stack to process the content of regexp literals and track nesting of { ... } [...] and (... ). (This has arguably a downside: it rejects versions of JQuery.js that contain malformed regexes [yes, they exist]. Javascript doesn't care if you define a bad regex literal and never use it, but that seems pretty pointless.)
A special case of the stack occurs if you only have track single "(" ... ")" pairs or the equivalent. In this case you can use a counter to record how many "pushes" or "pop" you might have done on a real stack. If you have two or more pairs of tokens like this, counters don't work.
What are some real-world (not-contrived) lexical-scanning problems where "inclusive scan conditions" (as opposed to "exclusive" ones) are a better solution?
That is, when is %s FOO any better than %x FOO in a (f)lex definition?
I understand the difference in function as well as how to implement the difference in a scanner generator. I'm just trying to get a sense of the kinds of situations where you would legitimately want to mash together different groups of scan rules into a single scan condition.
Full disclosure: Answers will inspire example code for this project.
"Mashing together" lexical rules is pretty common. Consider backslash-escape handling, which you might want to do more or less the same way in different quoting syntaxes and even regex literals. But those are likely to be combined explicitly.
For an only slightly contrived example of where implicit combination with the INITIAL state might be used, consider lexical analysis of a Python-like language with contextually meaningful leading whitespace. Here, there are two almost-identical lexical contexts: the normal context, in which a newline character is a syntactic marker and leading whitespace needs to be turned into INDENT/DEDENT sequences, and the parenthesised context in which newlines and leading whitespace are both just whitespace, which is not forwarded to the parser. These contexts will only differ in a couple of patterns; the vast majority of rules will be shared. So having an inclusive state which contains only something like:
<IN_PAREN>[[:space:]]+ /* Ignore all whitespace */
might be a simple solution. Of course, that rule would have to be placed before normal whitespace handling so that it overrides while IN_PAREN is active.
I was thinking to make a Pug parser but besides the indents are well-known to be context-sensitive (that can be trivially hacked with a lexer feedback loop to make it almost context-free which is adopted by Python), what otherwise makes it not context-free?
XML tags are definitely not context-free, that each starting tag needs to match an end tag, but Pug does not have such restriction, that makes me wonder if we could just parse each starting identifier as a production for a tag root.
The main thing that Pug seems to be missing, at least from a casual scan of its website, is a formal description of its syntax. Or even an informal description. Perhaps I wasn't looking in right places.
Still, based on the examples, it doesn't look awful. There will be some challenges; in particular, it does not have a uniform tokenisation context, so the scanner is going to be complicated, not just because of the indentation issue. (I got the impression from the section on whitespace that the indentation rule is much stricter than Python's, but I didn't find a specification of what it is exactly. It appeared to me that leading whitespace after the two-character indent is significant whitespace. But that doesn't complicate things much; it might even simplify the task.)
What will prove interesting is handling embedded JavaScript. You will at least need to tokenise the embedded JS, and the corner cases in the JS spec make it non-trivial to tokenise without parsing. Anyway, just tokenising isn't sufficient to know where the embedded code terminates. (For the lexical challenge, consider the correct identification of regular expression literals. /= might be the start of a regex or it might be a divide-and-assign operator; how a subsequent { is tokenised will depend on that decision.) Template strings present another challenge (recursive embedding). However, JavaScript parsers do exist, so you might be able to leverage one.
In other words, recognising tag nesting is not going to be the most challenging part of your project. Once you've identified that a given token is a tag, the nesting part is trivial (and context-free) because it is precisely defined by the indentation, so a DEDENT token will terminate the tag.
However, it is worth noting that tag parsing is not particularly challenging for XML (or XML-like HTML variants). If you adopt the XML rule that close tags cannot be omitted (except for self-closing tags), then the tagname in a close tag does not influence the parse of a correct input. (If the tagname in the close tag does not match the close tag in the corresponding open tag, then the input is invalid. But the correspondence between open and close tags doesn't change.) Even if you adopt the HTML-5 rule that close tags cannot be omitted except in the case of a finite list of special-case tagnames, then you could theoretically do the parse with a CFG. (However, the various error recovery rules in HTML-5 are far from context free, so that would only work for input which did not require rematching of close tags.)
Ira Baxter makes precisely this point in the cross-linked post he references in a comment: you can often implement context-sensitive aspects of a language by ignoring them during the parse and detecting them in a subsequent analysis, or even in a semantic predicate during the parse. Correct matching of open- and close tagnames would fall into this category, as would the "declare-before-use" rule in languages where the declaration of an identifier does not influence the parse. (Not true of C or C++, but true in many other languages.)
Even if these aspects cannot be ignored -- as with C typedefs, for example -- the simplest solution might be to use an ambiguous CFG and a parsing technology which produces all possible parses. After the parse forest is generated, you could walk the alternatives and reject the ones which are inconsistent. (In the case of C, that would include an alternative parse in which a name was typedef'd and then used in a context where a typename is not valid.)
Does there exist a formal definition of the purpose, or at a clear best practice of usage, of lexical analysis (lexer) during/before parsing?
I know that the purpose of a lexer is to transform a stream of characters to a stream of tokens, but can't it happen that in some (context-free) languages the intended notion of a "token" could nonetheless depend on the context and "tokens" could be hard to identify without complete parsing?
There seems to be nothing obviously wrong with having a lexer that transforms every input character into a token and lets the parser do the rest. But would it be acceptable to have a lexer that differentiates, for example, between a "unary minus" and a usual binary minus, instead of leaving this to the parser?
Are there any precise rules to follow when deciding what shall be done by the lexer and what shall be left to the parser?
Does there exist a formal definition of the purpose [of a lexical analyzer]?
No. Lexical analyzers are part of the world of practical programming, for which formal models are useful but not definitive. A program which purports to do something should do that thing, of course, but "lexically analyze my programming language" is not a sufficiently precise requirements statement.
… or a clear best practice of usage
As above, the lexical analyzer should do what it purports to do. It should also not attempt to do anything else. Code duplication should be avoided. Ideally, the code should be verifiable.
These best practices motivate the use of a mature and well-document scanner framework whose input language doubles as a description of the lexical grammar being analyzed. However, practical considerations based on the idiosyncracies of particular programming languages normally result in deviations from this ideal.
There seems to be nothing obviously wrong with having a lexer that transforms every input character into a token…
In that case, the lexical analyzer would be redundant; the parser could simply use the input stream as is. This is called "scannerless parsing", and it has its advocates. I'm not one of them, so I won't enter into a discussion of pros and cons. If you're interested, you could start with the Wikipedia article and follow its links. If this style fits your problem domain, go for it.
can't it happen that in some (context-free) languages the intended notion of a "token" could nonetheless depend on the context?
Sure. A classic example is found in EcmaScript regular expression "literals", which need to be lexically analyzed with a completely different scanner. EcmaScript 6 also defines string template literals, which require a separate scanning environment. This could motivate scannerless processing, but it can also be implemented with an LR(1) parser with lexical feedback, in which the reduce action of particular marker non-terminals causes a switch to a different scanner.
But would it be acceptable to have a lexer that differentiates, for example, between a "unary minus" and a usual binary minus, instead of leaving this to the parser?
Anything is acceptable if it works, but that particular example strikes me as not particular useful. LR (and even LL) expression parsers do not require any aid from the lexical scanner to show the context of a minus sign. (Naïve operator precedence grammars do require such assistance, but a more carefully thought out op-prec architecture wouldn't. However, the existence of LALR parser generators more or less obviates the need for op-prec parsers.)
Generally speaking, for the lexer to be able to identify syntactic context, it needs to duplicate the analysis being done by the parser, thus violating one of the basic best practices of code development ("don't duplicate functionality"). Nonetheless, it can occasionally be useful, so I wouldn't go so far as to advocate an absolute ban. For example, many parsers for yacc/bison-like production rules compensate for the fact that a naïve grammar is LALR(2) by specially marking ID tokens which are immediately followed by a colon.
Another example, again drawn from EcmaScript, is efficient handling of automatic semicolon insertion (ASI), which can be done using a lookup table whose keys are 2-tuples of consecutive tokens. Similarly, Python's whitespace-aware syntax is conveniently handled by assistance from the lexical scanner, which must be able to understand when indentation is relevant (not inside parentheses or braces, for example).
I wish to understand how does a parser work. I learnt about the LL, LR(0), LR(1) parts, how to build, NFA, DFA, parse tables, etc.
Now the problem is, i know that a lexer should extract tokens only on the parser demand in some situation, when it's not possible to extract all the tokens in one separated pass. I don't exactly understand this kind of situation, so i'm open to any explanation about this.
The question now is, how should a lexer does its job ? should it base its recognition on the current "contexts", the current non-terminals supposed to be parsed ? is it something totally different ?
What about the GLR parsing : is it another case where a lexer could try different terminals, or is it only a syntactic business ?
I would also want to understand what it's related to, for example is it related to the kind of parsing technique (LL, LR, etc) or only the grammar ?
Thanks a lot
The simple answer is that lexeme extraction has to be done in context. What one might consider be lexemes in the language may vary considerably in different parts of the language. For example, in COBOL, the data declaration section has 'PIC' strings and location-sensitive level numbers 01-99 that do not appear in the procedure section.
The lexer thus to somehow know what part of the language is being processed, to know what lexemes to collect. This is often handled by having lexing states which each process some subset of the entire language set of lexemes (often with considerable overlap in the subset; e.g., identifiers tend to be pretty similar in my experience). These states form a high level finite state machine, with transitions between them when phase changing lexemes are encountered, e.g., the keywords that indicate entry into the data declaration or procedure section of the COBOL program. Modern languages like Java and C# minimize the need for this but most other languages I've encountered really need this kind of help in the lexer.
So-called "scannerless" parsers (you are thinking "GLR") work by getting rid of the lexer entirely; now there's no need for the lexer to produce lexemes, and no need to track lexical states :-} Such parsers work by simply writing the grammar down the level of individual characters; typically you find grammar rules that are the exact equivalent of what you'd write for a lexeme description. The question is then, why doesn't such a parser get confused as to which "lexeme" to produce? This is where the GLR part is useful. GLR parsers are happy to process many possible interpretations of the input ("locally ambiguous parses") as long as the choice gets eventually resolved. So what really happens in the case of "ambiguous tokens" is the the grammar rules for both "tokens" produce nonterminals for their respectives "lexemes", and the GLR parser continues to parse until one of the parsing paths dies out or the parser terminates with an ambiguous parse.
My company builds lots of parsers for languages. We use GLR parsers because they are very nice for handling complex languages; write the context-free grammar and you have a parser. We use lexical-state based lexeme extractors with the usual regular-expression specification of lexemes and lexical-state-transitions triggered by certain lexemes. We could arguably build scannerless GLR parsers (by making our lexers produce single characters as tokens :) but we find the efficiency of the state-based lexers to be worth the extra trouble.
As practical extensions, our lexers actually use push-down-stack automata for the high level state machine rather than mere finite state machines. This helps when one has high level FSA whose substates are identical, and where it is helpful for the lexer to manage nested structures (e.g, match parentheses) to manage a mode switch (e.g., when the parentheses all been matched).
A unique feature of our lexers: we also do a little tiny bit of what scannerless parsers do: sometimes when a keyword is recognized, our lexers will inject both a keyword and an identifier into the parser (simulates a scannerless parser with a grammar rule for each). The parser will of course only accept what it wants "in context" and simply throw away the wrong alternative. This gives us an easy to handle "keywords in context otherwise interpreted as identifiers", which occurs in many, many languages.
Ideally, the tokens themselves should be unambiguous; you should always be able to tokenise an input stream without the parser doing any additional work.
This isn't always so simple, so you have some tools to help you out:
Start conditions
A lexer action can change the scanner's start condition, meaning it can activate different sets of rules.
A typical example of this is string literal lexing; when you parse a string literal, the rules for tokenising usually become completely different to the language containing them. This is an example of an exclusive start condition.
You can separate ambiguous lexings if you can identify two separate start conditions for them and ensure the lexer enters them appropriately, given some preceding context.
Lexical tie-ins
This is a fancy name for carrying state in the lexer, and modifying it in the parser. If a certain action in your parser gets executed, it modifies some state in the lexer, which results in lexer actions returning different tokens. This should be avoided when necessary, because it makes your lexer and parser both more difficult to reason about, and makes some things (like GLR parsers) impossible.
The upside is that you can do things that would require significant grammar changes with relatively minor impact on the code; you can use information from the parse to influence the behaviour of the lexer, which in turn can come some way to solving your problem of what you see as an "ambiguous" grammar.
Logic, reasoning
It's probable that it is possible to lex it in one parse, and the above tools should come second to thinking about how you should be tokenising the input and trying to convert that into the language of lexical analysis. :)
The fact is, your input is comprised of tokens—whether you like it or not!—and all you need to do is find a way to make a program understand the rules you already know.