9.2. Parsing#

You could code your own lexer and parser from scratch. But many languages include tools for automatically generating lexers and parsers from formal descriptions of the syntax of a language. The ancestors of many of those tools are lex and yacc, which generate lexers and parsers, respectively; lex and yacc were developed in the 1970s for C.

As part of the standard distribution, OCaml provides lexer and parser generators named ocamllex and ocamlyacc. There is a more modern parser generator named menhir available through opam; menhir is “90% compatible” with ocamlyacc and provides significantly improved support for debugging generated parsers.

9.2.1. Lexers#

Lexer generators such as lex and ocamllex are built on the theory of deterministic finite automata, which is typically covered in a discrete math or theory of computation course. Such automata accept regular languages, which can be described with regular expressions. So, the input to a lexer generator is a collection of regular expressions that describe the tokens of the language. The output is an automaton implemented in a high-level language, such as C (for lex) or OCaml (for ocamllex).

That automaton itself takes files (or strings) as input, and each character of the file becomes an input to the automaton. Eventually the automaton either recognizes the sequence of characters it has received as a valid token in the language, in which case the automaton produces an output of that token and resets itself to being recognizing the next token, or rejects the sequence of characters as an invalid token.

9.2.2. Parsers#

Parser generators such as yacc and menhir are similarly built on the theory of automata. But they use pushdown automata, which are like finite automata that also maintain a stack onto which they can push and pop symbols. The stack enables them to accept a bigger class of languages, which are known as context-free languages (CFLs). One of the big improvements of CFLs over regular languages is that CFLs can express the idea that delimiters must be balanced—for example, that every opening parenthesis must be balanced by a closing parenthesis.

Just as regular languages can be expressed with a special notation (regular expressions), so can CFLs. Context-free grammars are used to describe CFLs. A context-free grammar is a set of production rules that describe how one symbol can be replaced by other symbols. For example, the language of balanced parentheses, which includes strings such as (()) and ()() and (()()), but not strings such as ) or ((), is generated by these rules:

  • \(S \rightarrow (S)\)

  • \(S \rightarrow SS\)

  • \(S \rightarrow \epsilon\)

The symbols occurring in those rules are \(S\), \((\), and \()\). The \(\epsilon\) denotes the empty string. Every symbol is either a nonterminal or a terminal, depending on whether it is a token of the language being described. \(S\) is a nonterminal in the example above, and ( and ) are terminals.

In the next section we’ll study Backus-Naur Form (BNF), which is a standard notation for context-free grammars. The input to a parser generator is typically a BNF description of the language’s syntax. The output of the parser generator is a program that recognizes the language of the grammar. As input, that program expects the output of the lexer. As output, the program produces a value of the AST type that represents the string that was accepted. The programs output by the parser generator and lexer generator are thus dependent upon on another and upon the AST type.

9.2.3. Backus-Naur Form#

The standard way to describe the syntax of a language is with a mathematical notation called Backus-Naur form (BNF), named for its inventors, John Backus and Peter Naur. There are many variants of BNF. Here, we won’t be too picky about adhering to one variant or another. Our goal is just to have a reasonably good notation for describing language syntax.

BNF uses a set of derivation rules to describe the syntax of a language. Let’s start with an example. Here’s the BNF description of a tiny language of expressions that include just the integers and addition:

e ::= i | e + e
i ::= <integers>

These rules say that an expression e is either an integer i, or two expressions with the symbol + appearing between them. The syntax of “integers” is left unspecified by these rules.

Each rule has the form

metavariable ::= symbols | ... | symbols

A metavariable is variable used in the BNF rules, rather than a variable in the language being described. The ::= and | that appear in the rules are metasyntax: BNF syntax used to describe the language’s syntax. Symbols are sequences that can include metavariables (such as i and e) as well as tokens of the language (such as +). Whitespace is not relevant in these rules.

Sometimes we might want to easily refer to individual occurrences of metavariables. We do that by appending some distinguishing mark to the metavariable(s). For example, we could rewrite the first rule above as

e ::= i | e1 + e2

or as

e ::= i | e + e'

Now we can talk about e2 or e' rather than having to say “the e on the right-hand side of +”.

If the language itself contains either of the tokens ::= or |—and OCaml does contain the latter—then writing BNF can become a little confusing. Some BNF notations attempt to deal with that by using additional delimiters to distinguish syntax from metasyntax. We will be more relaxed and assume that the reader can distinguish them.

9.2.4. Example: SimPL#

As a running example, we’ll use a very simple programming language that we call SimPL. Here is its syntax in BNF:

e ::= x | i | b | e1 bop e2
    | if e1 then e2 else e3
    | let x = e1 in e2

bop ::= + | * | <=

x ::= <identifiers>

i ::= <integers>

b ::= true | false

Obviously there’s a lot missing from this language, especially functions. But there’s enough in it for us to study the important concepts of interpreters without getting too distracted by lots of language features. Later, we will consider a larger fragment of OCaml.

We’re going to develop a complete interpreter for SimPL. You can download the finished interpreter here: simpl.zip. Or, just follow along as we build each piece of it. The AST#

Since the AST is the most important data structure in an interpreter, let’s design it first. We’ll put this code in a file named ast.ml:

type bop =
  | Add
  | Mult
  | Leq

type expr =
  | Var of string
  | Int of int
  | Bool of bool
  | Binop of bop * expr * expr
  | Let of string * expr * expr
  | If of expr * expr * expr

There is one constructor for each of the syntactic forms of expressions in the BNF. For the underlying primitive syntactic classes of identifiers, integers, and booleans, we’re using OCaml’s own string, int, and bool types.

Instead of defining the bop type and a single Binop constructor, we could have defined three separate constructors for the three binary operators:

type expr =
  | Add of expr * expr
  | Mult of expr * expr
  | Leq of expr * expr

But by factoring out the bop type we will be able to avoid a lot of code duplication later in our implementation. The Menhir Parser#

Let’s start with parsing, then return to lexing later. We’ll put all the Menhir code we write below in a file named parser.mly. The .mly extension indicates that this file is intended as input to Menhir. (The ‘y’ alludes to yacc.) This file contains the grammar definition for the language we want to parse. The syntax of grammar definitions is described by example below. Be warned that it’s maybe a little weird, but that’s because it’s based on tools (like yacc) that were developed quite awhile ago. Menhir will process that file and produce a file named parser.ml as output; it contains an OCaml program that parses the language. (There’s nothing special about the name parser here; it’s just descriptive.)

There are four parts to a grammar definition: header, declarations, rules, and trailer.

Header. The header appears between %{ and %}. It is code that will be copied literally into the generated parser.ml. Here we use it just to open the Ast module so that, later on in the grammar definition, we can write expressions like Int i instead of Ast.Int i. If we wanted, we could also define some OCaml functions in the header.

open Ast

Declarations. The declarations section begins by saying what the lexical tokens of the language are. Here are the token declarations for SimPL:

%token <int> INT
%token <string> ID
%token TRUE
%token FALSE
%token LEQ
%token TIMES
%token PLUS
%token LPAREN
%token RPAREN
%token LET
%token EQUALS
%token IN
%token IF
%token THEN
%token ELSE
%token EOF

Each of these is just a descriptive name for the token. Nothing so far says that LPAREN really corresponds to (, for example. We’ll take care of that when we define the lexer.

The EOF token is a special end-of-file token that the lexer will return when it comes to the end of the character stream. At that point we know the complete program has been read.

The tokens that have a <type> annotation appearing in them are declaring that they will carry some additional data along with them. In the case of INT, that’s an OCaml int. In the case of ID, that’s an OCaml string.

After declaring the tokens, we have to provide some additional information about precedence and associativity. The following declarations say that PLUS is left associative, IN is not associative, and PLUS has higher precedence than IN (because PLUS appears on a line after IN).

%nonassoc IN
%nonassoc ELSE
%left LEQ
%left PLUS
%left TIMES

Because PLUS is left associative, 1 + 2 + 3 will parse as (1 + 2) + 3 and not as 1 + (2 + 3). Because PLUS has higher precedence than IN, the expression let x = 1 in x + 2 will parse as let x = 1 in (x + 2) and not as (let x = 1 in x) + 2. The other declarations have similar effects.

Getting the precedence and associativity declarations correct is one of the trickier parts of developing a grammar definition. It helps to develop the grammar definition incrementally, adding just a couple tokens (and their associated rules, discussed below) at a time to the language. Menhir will let you know when you’ve added a token (and rule) for which it is confused about what you intend the precedence and associativity should be. Then you can add declarations and test to make sure you’ve got them right.

After declaring associativity and precedence, we need to declare what the starting point is for parsing the language. The following declaration says to start with a rule (defined below) named prog. The declaration also says that parsing a prog will return an OCaml value of type Ast.expr.

%start <Ast.expr> prog

Finally, %% ends the declarations section.


Rules. The rules section contains production rules that resemble BNF, although where in BNF we would write “::=” these rules simply write “:”. The format of a rule is

  | production1 { action1 }
  | production2 { action2 }
  | ...

The production is the sequence of symbols that the rule matches. A symbol is either a token or the name of another rule. The action is the OCaml value to return if a match occurs. Each production can bind the value carried by a symbol and use that value in its action. This is perhaps best understood by example, so let’s dive in.

The first rule, named prog, has just a single production. It says that a prog is an expr followed by EOF. The first part of the production, e=expr, says to match an expr and bind the resulting value to e. The action simply says to return that value e.

  | e = expr; EOF { e }

The second and final rule, named expr, has productions for all the expressions in SimPL.

  | i = INT { Int i }
  | x = ID { Var x }
  | TRUE { Bool true }
  | FALSE { Bool false }
  | e1 = expr; LEQ; e2 = expr { Binop (Leq, e1, e2) }
  | e1 = expr; TIMES; e2 = expr { Binop (Mult, e1, e2) }
  | e1 = expr; PLUS; e2 = expr { Binop (Add, e1, e2) }
  | LET; x = ID; EQUALS; e1 = expr; IN; e2 = expr { Let (x, e1, e2) }
  | IF; e1 = expr; THEN; e2 = expr; ELSE; e3 = expr { If (e1, e2, e3) }
  | LPAREN; e=expr; RPAREN {e}
  • The first production, i = INT, says to match an INT token, bind the resulting OCaml int value to i, and return AST node Int i.

  • The second production, x = ID, says to match an ID token, bind the resulting OCaml string value to x, and return AST node Var x.

  • The third and fourth productions match a TRUE or FALSE token and return the corresponding AST node.

  • The fifth, sixth, and seventh productions handle binary operators. For example, e1 = expr; PLUS; e2 = expr says to match an expr followed by a PLUS token followed by another expr. The first expr is bound to e1 and the second to e2. The AST node returned is Binop (Add, e1, e2).

  • The eighth production, LET; x = ID; EQUALS; e1 = expr; IN; e2 = expr, says to match a LET token followed by an ID token followed by an EQUALS token followed by an expr followed by an IN token followed by another expr. The string carried by the ID is bound to x, and the two expressions are bound to e1 and e2. The AST node returned is Let (x, e1, e2).

  • The last production, LPAREN; e = expr; RPAREN says to match an LPAREN token followed by an expr followed by an RPAREN. The expression is bound to e and returned.

The final production might be surprising, because it was not included in the BNF we wrote for SimPL. That BNF was intended to describe the abstract syntax of the language, so it did not include the concrete details of how expressions can be grouped with parentheses. But the grammar definition we’ve been writing does have to describe the concrete syntax, including details like parentheses.

There can also be a trailer section after the rules, which like the header is OCaml code that is copied directly into the output parser.ml file. The Ocamllex Lexer#

Now let’s see how the lexer generator is used. A lot of it will feel familiar from our discussion of the parser generator. We’ll put all the ocamllex code we write below in a file named lexer.mll. The .mll extension indicates that this file is intended as input to ocamllex. (The ‘l’ alludes to lexing.) This file contains the lexer definition for the language we want to lex. Menhir will process that file and produce a file named lexer.ml as output; it contains an OCaml program that lexes the language. (There’s nothing special about the name lexer here; it’s just descriptive.)

There are four parts to a lexer definition: header, identifiers, rules, and trailer.

Header. The header appears between { and }. It is code that will simply be copied literally into the generated lexer.ml.

open Parser

Here, we’ve opened the Parser module, which is the code in parser.ml that was produced by Menhir out of parser.mly. The reason we open it is so that we can use the token names declared in it, e.g., TRUE, LET, and INT, inside our lexer definition. Otherwise, we’d have to write Parser.TRUE, etc.

Identifiers. The next section of the lexer definition contains identifiers, which are named regular expressions. These will be used in the rules section, next.

Here are the identifiers we’ll use with SimPL:

let white = [' ' '\t']+
let digit = ['0'-'9']
let int = '-'? digit+
let letter = ['a'-'z' 'A'-'Z']
let id = letter+

The regular expressions above are for whitespace (spaces and tabs), digits (0 through 9), integers (non-empty sequences of digits, optionally preceded by a minus sign), letters (a through z, and A through Z), and SimPL variable names (non-empty sequences of letters) aka ids or “identifiers”—though we’re now using that word in two different senses.

FYI, these aren’t exactly the same as the OCaml definitions of integers and identifiers.

The identifiers section actually isn’t required; instead of writing white in the rules we could just directly write the regular expression for it. But the identifiers help make the lexer definition more self-documenting.

Rules. The rules section of a lexer definition is written in a notation that also resembles BNF. A rule has the form

rule name =
  | regexp1 { action1 }
  | regexp2 { action2 }
  | ...

Here, rule and parse are keywords. The lexer that is generated will attempt to match against regular expressions in the order they are listed. When a regular expression matches, the lexer produces the token specified by its action.

Here is the (only) rule for the SimPL lexer:

rule read =
  | white { read lexbuf }
  | "true" { TRUE }
  | "false" { FALSE }
  | "<=" { LEQ }
  | "*" { TIMES }
  | "+" { PLUS }
  | "(" { LPAREN }
  | ")" { RPAREN }
  | "let" { LET }
  | "=" { EQUALS }
  | "in" { IN }
  | "if" { IF }
  | "then" { THEN }
  | "else" { ELSE }
  | id { ID (Lexing.lexeme lexbuf) }
  | int { INT (int_of_string (Lexing.lexeme lexbuf)) }
  | eof { EOF }

Most of the regular expressions and actions are self-explanatory, but a couple are not:

  • The first, white { read lexbuf }, means that if whitespace is matched, instead of returning a token the lexer should just call the read rule again and return whatever token results. In other words, whitespace will be skipped.

  • The two for ids and ints use the expression Lexing.lexeme lexbuf. This calls a function lexeme defined in the Lexing module, and returns the string that matched the regular expression. For example, in the id rule, it would return the sequence of upper and lower case letters that form the variable name.

  • The eof regular expression is a special one that matches the end of the file (or string) being lexed.

Note that it’s important that the id regular expression occur nearly last in the list. Otherwise, keywords like true and if would be lexed as variable names rather than the TRUE and IF tokens. Generating the Parser and Lexer#

Now that we have completed parser and lexer definitions in parser.mly and lexer.mll, we can run Menhir and ocamllex to generate the parser and lexer from them. Let’s organize our code like this:

- <some root folder>
  - dune-project
  - src
    - ast.ml
    - dune
    - lexer.mll
    - parser.mly

In src/dune, write the following:

 (name interp))

 (modules parser))

(ocamllex lexer)

That organizes the entire src folder into a library named Interp. The parser and lexer will be modules Interp.Parser and Interp.Lexer in that library.

Run dune build to compile the code, thus generating the parser and lexer. If you want to see the generated code, look in _build/default/src/ for parser.ml and lexer.ml. The Driver#

Finally, we can pull together the lexer and parser to transform a string into an AST. Put this code into a file named src/main.ml:

open Ast

let parse (s : string) : expr =
  let lexbuf = Lexing.from_string s in
  let ast = Parser.prog Lexer.read lexbuf in

This function takes a string s and uses the standard library’s Lexing module to create a lexer buffer from it. Think of that buffer as the token stream. The function then lexes and parses the string into an AST, using Lexer.read and Parser.prog. The function Lexer.read corresponds to the rule named read in our lexer definition, and the function Parser.prog to the rule named prog in our parser definition.

Note how this code runs the lexer on a string; there is a corresponding function from_channel to read from a file.

We could now use parse interactively to parse some strings. Start utop and load the library declared in src with this command:

$ dune utop src

Now Interp.Main.parse is available for use:

# Interp.Main.parse "let x = 3110 in x + x";;
- : Interp.Ast.expr =
Interp.Ast.Let ("x", Interp.Ast.Int 3110,
 Interp.Ast.Binop (Interp.Ast.Add, Interp.Ast.Var "x", Interp.Ast.Var "x"))

That completes lexing and parsing for SimPL.