Lesson 1.3: BNF Syntax and Parser Generation

The purpose of this lesson is to explain the full syntax and semantics of productions in K as well as how productions and other syntactic sentences can be used to define grammars for use parsing both rules as well as programs.

K's approach to parsing

K's grammar is divided into two components: the outer syntax of K and the inner syntax of K. Outer syntax refers to the parsing of requires, modules, imports, and sentences in a K definition. Inner syntax refers to the parsing of rules and programs. Unlike the outer syntax of K, which is predetermined, much of the inner syntax of K is defined by you, the developer. When rules or programs are parsed, they are parsed within the context of a module. Rules are parsed in the context of the module in which they exist, whereas programs are parsed in the context of the main syntax module of a K definition. The productions and other syntactic sentences in a module are used to construct the grammar of the module, which is then used to perform parsing.

Basic BNF productions

To illustrate how this works, we will consider a simple K definition which defines a relatively basic calculator capable of evaluating Boolean expressions containing and, or, not, and xor.

Input the following program into your editor as file lesson-03-a.k:

module LESSON-03-A syntax Boolean ::= "true" | "false" | "!" Boolean [function] | Boolean "&&" Boolean [function] | Boolean "^" Boolean [function] | Boolean "||" Boolean [function] endmodule

You will notice that the productions in this file look a little different than the ones from the previous lesson. In point of fact, K has two different mechanisms for defining productions. We have previously been focused exclusively on the first mechanism, where the ::= symbol is followed by an alphanumeric identifier followed by a comma-separated list of sorts in parentheses. However, this is merely a special case of a more generic mechanism for defining the syntax of productions using a variant of BNF Form.

For example, in the previous lesson, we had the following set of productions:

module LESSON-03-B syntax Color ::= Yellow() | Blue() syntax Fruit ::= Banana() | Blueberry() syntax Color ::= colorOf(Fruit) [function] endmodule

It turns out that this is equivalent to the following definition which defines the same grammar, but using BNF notation:

module LESSON-03-C syntax Color ::= "Yellow" "(" ")" | "Blue" "(" ")" syntax Fruit ::= "Banana" "(" ")" | "Blueberrry" "(" ")" syntax Color ::= "colorOf" "(" Fruit ")" [function] endmodule

In this example, the sorts of the argument to the function are unchanged, but everything else has been wrapped in double quotation marks. This is because in BNF notation, we distinguish between two types of production items: terminals and non-terminals. A terminal represents simply a literal string of characters that is verbatim part of the syntax of that production. A non-terminal, conversely, represents a sort name, where the syntax of that production accepts any valid term of that sort at that position.

This is why, when we wrote the program colorOf(Banana()), krun was able to execute that program: because it represented a term of sort Color that was parsed and interpreted by K's interpreter. In other words, krun parses and interprets terms according to the grammar defined by the developer. It is automatically converted into an AST of that term, and then the colorOf function is evaluated using the function rules provided in the definition.

You can ask yourself: How does K match the strings between the double quotes? The answer is that K uses Flex to generate a scanner for the grammar. Flex looks for the longest possible match of a regular expression in the input. If there are ambiguities between 2 or more regular expressions, it will pick the one with the highest prec attribute. You can learn more about how Flex matching works here.

Bringing us back to the file lesson-03-a.k, we can see that this grammar has given a simple BNF grammar for expressions over Booleans. We have defined constructors corresponding to the Boolean values true and false, and functions corresponding to the Boolean operators for and, or, not, and xor. We have also given a syntax for each of these functions based on their syntax in the C programming language. As such, we can now write programs in the simple language we have defined.

Input the following program into your editor as and.bool in the same directory:

true && false

We cannot interpret this program yet, because we have not given rules defining the meaning of the && function yet, but we can parse it. To do this, you can run (from the same directory):

kast --output kore and.bool

kast is K's just-in-time parser. It will generate a grammar from your K definition on the fly and use it to parse the program passed on the command line. The --output flag controls how the resulting AST is represented; don't worry about the possible values yet, just use kore.

You ought to get the following AST printed on standard output, minus the formatting:

inj{SortBoolean{}, SortKItem{}}(

Don't worry about what exactly this means yet, just understand that it represents the AST of the program that you just parsed. You ought to be able to recognize the basic shape of it by seeing the words true, false, and And in there. This is Kore, the intermediate representation of K, and we will cover it in detail later.

Note that you can also tell kast to print the AST in other formats. For a more direct representation of the original K, while still maintaining the structure of an AST, you can say kast --output kast and.bool. This will yield the following output:


Note how the first output is largely a name-mangled version of the second output. The one difference is the presence of the inj symbol in the KORE output. We will talk more about this in later lessons.


Parse the expression false || true with --output kast. See if you can predict approximately what the corresponding output would be with --output kore, then run the command yourself and compare it to your prediction.


Now let's try a slightly more advanced example. Input the following program into your editor as and-or.bool:

true && false || false

When you try and parse this program, you ought to see the following error:

[Error] Inner Parser: Parsing ambiguity.
1: syntax Boolean ::= Boolean "||" Boolean [function]

2: syntax Boolean ::= Boolean "&&" Boolean [function]


This error is saying that kast was unable to parse this program because it is ambiguous. K's just-in-time parser is a GLL parser, which means it can handle the full generality of context-free grammars, including those grammars which are ambiguous. An ambiguous grammar is one where the same string can be parsed as multiple distinct ASTs. In this example, it can't decide whether it should be parsed as (true && false) || false or as true && (false || false). As a result, it reports the error to the user.


Currently there is no way of resolving this ambiguity, making it impossible to write complex expressions in this language. This is obviously a problem. The standard solution in most programming languages to this problem is to use parentheses to indicate the appropriate grouping. K generalizes this notion into a type of production called a bracket. A bracket production in K is any production with the bracket attribute. It is required that such a production only have a single non-terminal, and the sort of the production must equal the sort of that non-terminal. However, K does not otherwise impose restrictions on the grammar the user provides for a bracket. With that being said, the most common type of bracket is one in which a non-terminal is surrounded by terminals representing some type of bracket such as (), [], {}, <>, etc. For example, we can define the most common type of bracket, the type used by the vast majority of programming languages, quite simply.

Consider the following modified definition, which we will save to lesson-03-d.k:

module LESSON-03-D syntax Boolean ::= "true" | "false" | "(" Boolean ")" [bracket] | "!" Boolean [function] | Boolean "&&" Boolean [function] | Boolean "^" Boolean [function] | Boolean "||" Boolean [function] endmodule

In this definition, if the user does not explicitly define parentheses, the grammar remains ambiguous and K's just-in-time parser will report an error. However, you are now able to parse more complex programs by means of explicitly grouping subterms with the bracket we have just defined.

Consider and-or-left.bool:

(true && false) || false

Now consider and-or-right.bool:

true && (false || false)

If you parse these programs with kast, you will once again get a single unique AST with no error. If you look, you might notice that the bracket itself does not appear in the AST. In fact, this is a property unique to brackets: productions with the bracket attribute are not represented in the parsed AST of a term, and the child of the bracket is folded immediately into the parent term. This is the reason for the requirement that a bracket production have a single non-terminal of the same sort as the production itself.


Write out what you expect the AST to be arising from parsing these two programs above with --output kast, then parse them yourself and compare them to the AST you expected. Confirm for yourself that the bracket production does not appear in the AST.


So far we have seen how we can define the grammar of a language. However, the grammar is not the only relevant part of parsing a language. Also relevant is the lexical syntax of the language. Thus far, we have implicitly been using K's automatic lexer generation to generate a token in the scanner for each terminal in our grammar. However, sometimes we wish to define more complex lexical syntax. For example, consider the case of integers in C: an integer consists of a decimal, octal, or hexadecimal number followed by an optional suffix indicating the type of the literal.

In theory it would be possible to define this syntax via a grammar, but not only would it be cumbersome and tedious, you would also then have to deal with an AST generated for the literal which is not convenient to work with.

Instead of doing this, K allows you to define token productions, where a production consists of a regular expression followed by the token attribute, and the resulting AST consists of a typed string containing the value recognized by the regular expression.

For example, the builtin integers in K are defined using the following production:

.k .exclude
syntax Int ::= r"[\\+\\-]?[0-9]+" [token]

Here we can see that we have defined that an integer is an optional sign followed by a nonzero sequence of digits. The r preceding the terminal indicates that what appears inside the double quotes is a regular expression, and the token attribute indicates that terms which parse as this production should be converted into a token by the parser.

It is also possible to define tokens that do not use regular expressions. This can be useful when you wish to declare particular identifiers for use in your semantics later. For example:

.k .exclude
syntax Id ::= "main" [token]

Here, we declare that main is a token of sort Id. Instead of being parsed as a symbol, it gets parsed as a token, generating a typed string in the AST. This is useful in a semantics of C because the parser generally does not treat the main function in C specially; only the semantics treats it specially.

Of course, languages can have more complex lexical syntax. For example, if we wish to define the syntax of integers in C, we could use the following production:

.k .exclude
syntax IntConstant ::= r"(([1-9][0-9]*)|(0[0-7]*)|(0[xX][0-9a-fA-F]+))(([uU][lL]?)|([uU]((ll)|(LL)))|([lL][uU]?)|(((ll)|(LL))[uU]?))?" [token]

As you may have noted above, long and complex regular expressions can be hard to read. They also suffer from the problem that unlike a grammar, they are not particularly modular.

We can get around this restriction by declaring explicit regular expressions, giving them a name, and then referring to them in productions.

Consider the following (equivalent) way to define the lexical syntax of integers in C:

.k .exclude
syntax IntConstant ::= r"({DecConstant}|{OctConstant}|{HexConstant})({IntSuffix}?)" [token] syntax lexical DecConstant = r"{NonzeroDigit}({Digit}*)" syntax lexical OctConstant = r"0({OctDigit}*)" syntax lexical HexConstant = r"{HexPrefix}({HexDigit}+)" syntax lexical HexPrefix = r"0x|0X" syntax lexical NonzeroDigit = r"[1-9]" syntax lexical Digit = r"[0-9]" syntax lexical OctDigit = r"[0-7]" syntax lexical HexDigit = r"[0-9a-fA-F]" syntax lexical IntSuffix = r"{UnsignedSuffix}({LongSuffix}?)|{UnsignedSuffix}{LongLongSuffix}|{LongSuffix}({UnsignedSuffix}?)|{LongLongSuffix}({UnsignedSuffix}?)" syntax lexical UnsignedSuffix = r"[uU]" syntax lexical LongSuffix = r"[lL]" syntax lexical LongLongSuffix = r"ll|LL"

As you can see, this is rather more verbose, but it has the benefit of both being much easier to read and understand, and also increased modularity. Note that we refer to a named regular expression by putting the name in curly brackets. Note also that only the first sentence actually declares a new piece of syntax in the language. When the user writes syntax lexical, they are only declaring a regular expression. To declare an actual piece of syntax in the grammar, you still must actually declare an explicit token production.

One final note: K uses Flex to implement its lexical analysis. As a result, you can refer to the Flex Manual for a detailed description of the regular expression syntax supported. Note that for performance reasons, Flex's regular expressions are actually a regular language, and thus lack some of the syntactic convenience of modern "regular expression" libraries. If you need features that are not part of the syntax of Flex regular expressions, you are encouraged to express them via a grammar instead.

Ahead-of-time parser generation

So far we have been entirely focused on K's support for just-in-time parsing, where the parser is generated on the fly prior to being used. This benefits from being faster to generate the parser, but it suffers in performance if you have to repeatedly parse strings with the same parser. For this reason, it is generally encouraged that when parsing programs, you use K's ahead-of-time parser generation. K makes use of GNU Bison to generate parsers.

By default, you can enable ahead-of-time parsing via the --gen-bison-parser flag to kompile. This will make use of Bison's LR(1) parser generator. As such, if your grammar is not LR(1), it may not parse exactly the same as if you were to use the just-in-time parser, because Bison will automatically pick one of the possible branches whenever it encounters a shift-reduce or reduce-reduce conflict. In this case, you can either modify your grammar to be LR(1), or you can enable use of Bison's GLR support by instead passing --gen-glr-bison-parser to kompile. Note that if your grammar is ambiguous, the ahead-of-time parser will not provide you with particularly readable error messages at this time.

If you have a K definition named foo.k, and it generates a directory when you run kompile called foo-kompiled, you can invoke the ahead-of-time parser you generated by running foo-kompiled/parser_PGM <file> on a file.


  1. Compile lesson-03-d.k with ahead-of-time parsing enabled. Then compare how long it takes to run kast --output kore and-or-left.bool with how long it takes to run lesson-03-d-kompiled/parser_PGM and-or-left.bool. Confirm for yourself that both produce the same result, but that the latter is faster.

  2. Define a simple grammar consisting of integers, brackets, addition, subtraction, multiplication, division, and unary negation. Integers should be in decimal form and lexically without a sign, whereas negative numbers can be represented via unary negation. Ensure that you are able to parse some basic arithmetic expressions using a generated ahead-of-time parser. Do not worry about disambiguating the grammar or about writing rules to implement the operations in this definition.

  3. Write a program where the meaning of the arithmetic expression based on the grammar you defined above is ambiguous, and then write programs that express each individual intended meaning using brackets.

Next lesson

Once you have completed the above exercises, you can continue to Lesson 1.4: Disambiguating Parses.