CSE 130 SP16- A Quick Tutorial On Parsing



In this note we consider an invaluable programming tool, the parser generator. The problem that we want to solve is: how do we parse strings, that is, convert (unstructured) strings, the lowest-level representation of a program text, into (highly structured) representations like expressions, statements, functions etc which can then be compiled or interpreted.

Of course, the problem is much more general and arises in pretty much every large scale system, how do you convert raw data strings, into structured objects that can be manipulated by the rest of the system.

Of course, one can imagine various convoluted algorithms for extracting structure from strings. Indeed, you may well think that the conversion routine depends heavily on the target of the conversion! However, it turns out that we can design a small domain-specific language that describes a large number of the kinds of target structures, and we will use a parser generator that will automatically convert the structure description into a parsing function!

An Arithmetic Interpreter

As a running example, let us build a small interpreter for a language of arithmetic expressions, described by the type

type aexpr =
  | Const  of int
  | Var    of string
  | Plus   of aexpr * aexpr
  | Minus  of aexpr * aexpr
  | Times  of aexpr * aexpr
  | Divide of aexpr * aexpr

shown in file (arithInterpreter.ml)0. This expression language is quite similar to what you saw for the random-art assignment, and we can write a simple recursive evaluator for it

let foo x = match x with
  | C1 ... -> e1
  | C2 ... -> e2

let foo = function
  | C1 ... -> e1
  | C2 ... -> e2

let rec eval env e = match e with
  | Const i         -> i
  | Var s           -> List.assoc s env
  | Plus (e1, e2)   -> eval env e1 + eval env e2
  | Minus (e1, e2)  -> eval env e1 - eval env e2
  | Times (e1, e2)  -> eval env e1 * eval env e2
  | Divide (e1, e2) -> eval env e1 / eval env e2

Here the env is a (string * int) list corresponding to a list of variables and their corresponding values. Thus, if you run the above, you would see something like

# eval [] (Plus (Const 2, Const 6)) ;;
- : int = 4

# eval [("x",16); ("y", 10)] (Minus (Var "x", Var "y")) ;;
- : int = 6

# eval [("x",16); ("y", 10)] (Minus (Var "x", Var "z")) ;;
Exception: NotFound.

Now it is rather tedious to write ML expressions like Plus (Const 2, Const 6), and Minus (Var "x", Var "z"). We would like to obtain a simple parsing function

val parseAexpr : string -> aexpr

that converts a string to the corresponding aexpr if possible. For example, it would be sweet if we could get

# parseAexpr "2 + 6" ;;
- : aexpr = Plus (Const 2, Const 6)

# parseAexpr "(x - y) / 2" ;;
- : aexpr = Divide (Minus (Var "x", Var "y"), Const 2)

and so on. Lets see how to get there.

Strategy

We will use a two-step strategy to convert raw strings into structured data.

Step 1 (Lexing) : From String to Tokens

Strings are really just a list of very low-level characters. In the first step, we will aggregate the characters into more meaningful tokens that contain more high-level information. For example, we will can aggregate a sequence of numeric characters into an integer, and a sequence of alphanumerics (starting with a lower-case alphabet) into say a variable name.

Thus, as a result of the lexing phase, we can convert a list of individual characters

into a list of tokens

Step 2 (Parsing) : From Tokens to Tree

Next, we will use a special description of the structures we are trying to generate called a grammar to convert the list of tokens into a tree-like representation of our final structure:

- : aexpr = Plus (Const 229, Times (Const 98, Var "x2"))

The actual algorithms for converting from lists of tokens to trees are very subtle and sophisticated. We will omit a detailed description and instead just look at how the structures can themselves be represented by grammars.

Next, we get into the details of our the above strategy, by describing exactly what the lexer and parser (generators) do in terms of their input and output.

Lexers

We will use the tool called ocamllex to automatically obtain a lexer from a high-level description of what the tokens are and what what sequences of characters should get mapped to tokens.

Tokens

The file (arithParser0.mly)1 describes the set of tokens needed to represent our simple language

%token <int> CONST
%token <string> VAR
%token PLUS MINUS TIMES DIVIDE
%token LPAREN RPAREN
%token EOF

Note that the first two tokens, CONST and VAR also carry values with them, respectively int and string.

Regular Expressions

Next, we must describe the sequences of characters that get aggregated into a particular token. This is done using (regular expressions)7 defined in the file (arithLexer.mll)2.

{ open ArithParser }

rule token = parse
  | eof                      { EOF }
  | [' ' '\t' '\r' '\n']     { token lexbuf }
  | ['0'-'9']+ as l          { CONST (int_of_string l) }
  | ['a'-'z']['A'-'z']* as l { VAR l }
  | '+'                      { PLUS }
  | '-'                      { MINUS }
  | '*'                      { TIMES }
  | '/'                      { DIVIDE }
  | '('                      { LPAREN }
  | ')'                      { RPAREN }

the first line at top simply imports the token definitions from arithParser.mly. Next, there is a sequence of rules of the form | <regexp> {ml-expr}.

Intuitively, each regular expression describes a sequence of characters, and when that sequence is matched in the input string, the corresponding ML expression is evaluated to obtain the token that is to be returned on the match. Let’s see some examples,

  | eof                      { EOF }
  | '+'                      { PLUS }
  | '-'                      { MINUS }
  | '*'                      { TIMES }
  | '/'                      { DIVIDE }
  | '('                      { LPAREN }
  | ')'                      { RPAREN }
  | [' ' '\t' '\r' '\n']     { token lexbuf }
  | ['0'-'9']+ as l          { CONST (int_of_string l) }
  | ['a'-'z']['A'-'z' '0'-'9']*  as l { VAR l }

Running the Lexer

We can run the lexer directly to look at the sequences of tokens found. The function Lexing.from_string simply converts an input string into a buffer on which the actual lexer operates.

# ArithLexer.token (Lexing.from_string "+");;
- : ArithParser.token = ArithParser.PLUS

# ArithLexer.token (Lexing.from_string "294");;
- : ArithParser.token = ArithParser.CONST 294

Next, we can write a function that recursively keeps grinding away to get all the possible tokens from a string (until it hits eof). When we call that function it behaves thus:

# token_list_of_string "23 + + 92 zz /" ;;
- : ArithParser.token list =
  [ArithParser.CONST 23; ArithParser.PLUS; ArithParser.PLUS;
   ArithParser.CONST 92; ArithParser.VAR "zz"; ArithParser.DIVIDE]

# token_list_of_string "23++92zz/" ;;
- : ArithParser.token list =
  [ArithParser.CONST 23; ArithParser.PLUS; ArithParser.PLUS;
   ArithParser.CONST 92; ArithParser.VAR "zz"; ArithParser.DIVIDE]

Note that the above two calls produce exactly the same result, because the lexer finds maximal matches.

# token_list_of_string "92z" ;;
- : ArithParser.token list = [ArithParser.CONST 92; ArithParser.VAR "z"]

Here, when it hits the z it knows that the number pattern has ended and a new variable pattern has begun. Of course, if you give it something that doesn’t match anything, you get an exception

# parse_string "%" ;;
Exception: Failure "lexing: empty token".

Parsers

Next, will use the tool called ocamlyacc to automatically obtain a parser from a high-level description of the target structure called a grammar. (Note: grammars are very deep area of study, we’re going to take a very superficial look here, guided by the pragmatics of how to convert strings to aexpr values.)

Grammars

A grammar is a recursive definition of a set of trees, comprising

nonterm :
  | term-or-nonterm-1 ... term-or-non-term-n { Ocaml-Expr }

that describe the possible configuration of children of each internal node, together with an Ocaml expression that generates a value that is used to decorate the node. This value is computed from the values decorating the respective children.

We can define the following simple grammar for arith expressions:

aexpr:
  | aexpr PLUS   aexpr        { Plus ($1, $3)   }
  | aexpr MINUS  aexpr        { Minus ($1, $3)  }
  | aexpr TIMES  aexpr        { Times ($1, $3)  }
  | aexpr DIVIDE aexpr        { Divide ($1, $3) }
  | CONST                     { Const $1        }
  | VAR                       { Var $1          }
  | LPAREN aexpr RPAREN       { $2              }

Note that the above grammar (almost) directly mimics the recursive type definition of the expressions. In the above grammar, the only non-terminal is aexpr (we could call it whatever we like, we just picked the same name for convenience.) The terminals are the tokens we defined earlier, and each rule corresponds to how you would take the sub-trees (i.e. sub-expressions) and stitch them together to get bigger trees.

The line %type <ArithInterpreter.aexpr> aexpr at the top stipulates that each aexpr node will be decorated with a value of type ArithInterpreter.aexpr – that is, by a structured arithmetic expression.

Next, let us consider each of the rules in turn.

  | CONST                     { Const $1        }
  | VAR                       { Var $1          }
  | aexpr PLUS   aexpr        { Plus ($1, $3)   }
  | aexpr MINUS  aexpr        { Minus ($1, $3)  }
  | aexpr TIMES  aexpr        { Times ($1, $3)  }
  | aexpr DIVIDE aexpr        { Divide ($1, $3) }
  | LPAREN aexpr RPAREN       { $2              }

Running the Parser

Great, lets take our parser out for a spin! First, lets build the different elements

$ cp arithParser0.mly arithParser.mly

$ make clean
rm -f *.cm[io] arithLexer.ml arithParser.ml arithParser.mli

$ make
ocamllex arithLexer.mll
11 states, 332 transitions, table size 1394 bytes
ocamlyacc arithParser.mly
16 shift/reduce conflicts.
ocamlc -c arithInterpreter.ml
ocamlc -c arithParser.mli
ocamlc -c arithLexer.ml
ocamlc -c arithParser.ml
ocamlc -c arith.ml
ocamlmktop arithLexer.cmo arithParser.cmo arithInterpreter.cmo arith.cmo -o arith.top

Now, we have a specialize top-level with the relevant libraries baked in. So we can do:

$ rlwrap ./arith.top
        Objective Caml version 3.11.2

# open Arith;;

# eval_string [] "1 + 3 + 6" ;;
- : int = 10

# eval_string [("x", 100); ("y", 20)] "x - y" ;;
- : int = 80

And lo! we have a simple calculator that also supports variables.

Precedence and Associativity

Ok, looks like our calculator works fine, but lets try this

# eval_string [] "2 * 5 + 5" ;;
- : int = 20

Huh?! you would think that the above should yield 15 as * has higher precedence than + , and so the above expression is really (2 * 5) + 5. Indeed, if we took the trouble to put the parentheses in, the right thing happens

# eval_string [] "(2 * 5) + 5" ;;
- : int = 15

Indeed, the same issue arises with a single operator

# eval_string [] "2 - 1 - 1" ;;
- : int = 2

What happens here is that the grammar we gave is ambiguous as there are multiple ways of parsing the string 2 * 5 + 5, namely

We want the former, but ocamlyacc gives us the latter! Similarly, there are multiple ways of parsing 2 - 1 - 1, namely

Again, since - is left-associative, we want the former, but we get the latter! (Incidentally, this is why we got those wierd grumbles about shift/reduce conflicts when we ran ocamlyacc above, but lets not go too deep into that…)

There are various ways of adding precedence, one is to hack the grammar by adding various extra non-terminals, as done here (arithParser2.mly)[5]. Note how there are no conflicts if you use that grammar instead.

However, since this is such a common problem, there is a much simpler solution, which is to add precedence and associativity annotations to the .mly file. In particular, let us use the modified grammar (arithParser1.mly)3.

$ cp arithParser1.mly arithParser.mly
$ make
ocamllex arithLexer.mll
11 states, 332 transitions, table size 1394 bytes
ocamlyacc arithParser.mly
ocamlc -c arithInterpreter.ml
ocamlc -c arithParser.mli
ocamlc -c arithLexer.ml
ocamlc -c arithParser.ml
ocamlc -c arith.ml
ocamlmktop arithLexer.cmo arithParser.cmo arithInterpreter.cmo arith.cmo -o arith.top

check it out, no conflicts this time! The only difference between this grammar and the previous one are the lines

%left PLUS MINUS
%left TIMES DIVIDE

This means that all the operators are left-associative
so e1 - e2 - e3 is parsed as if it were (e1 - e2) - e3. As a result we get

# eval_string []  "2 - 1 - 1" ;;
- : int = 0

Furthermore, we get that addition and subtraction have lower precedence than multiplication and division (the order of the annotations matters!)

# eval_string []  "2 * 5 + 5" ;;
- : int = 15
# eval_string []  "2 + 5 * 5" ;;
- : int = 27

Hence, the multiplication operator has higher precedence than the addition, as we have grown to expect, and all is well in the world.

This concludes our brief tutorial, which should suffice for your NanoML programming assignment. However, if you are curious, I encourage you to look at (this)6 for more details.