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JavaCC, parse trees, and the XQuery grammar, Part 2
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JJTree basics
Step-by-step through a JJTree grammar
Working with the parse tree
Aids to navigation
Saving and restoring state
Putting it all together: A BNF snippet for XQuery
Walking the parse tree client-side
About the author
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JavaCC, parse trees, and the XQuery grammar, Part
An introduction to XQuery
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Building and walking a custom parse tree using JJTree

Level: Intermediate

Howard Katz (, parse trees, and the XQuery grammar, Part 2)
Proprietor, Fatdog Software
1 December 2002

Part 1 of this article took an introductory look at grammars, parsers, and BNF. It then introduced JavaCC, a popular parser generator. Part 2 shows you how to modify the sample code in Part 1 so that you can use an additional tool, JJTree, to build a parse tree representation of the same parse. You'll explore the advantages of this approach and look at how to write Java code to walk the parse tree at runtime in order to recover its state information, and evaluate the expression being parsed. The article concludes by showing you how to develop a generalizable routine for walking and evaluating a parse tree that you'll generate from a small portion of the XQuery grammar.

Using the JavaCC parser generator has one major downside: Much or most of your client-side Java code needs to be embedded in the .jj grammar script that encodes your BNF (Backus-Naur Form). This means you lose many of the advantages that a proper Java IDE can provide you during the development cycle.

Enter JJTree, JavaCC's companion tool. JJTree is set up to emit a parser whose main job at runtime is not to execute embedded Java actions, but to build an independent parse-tree representation of the expression that's being parsed. This lets you capture the state of the parse session in a single tree that's easy to walk and interrogate at runtime, independent of the parsing code that produced it. Working with a parse tree representation also makes debugging easy and speeds development time. JJTree is distributed as part of the JavaCC distribution (see Resources).

I'll note before we go any further that the terms parse tree and abstract syntax tree (or AST) describe very similar grammatical structures. Strictly speaking, what I refer to as a parse tree in the following, language theoreticians would more precisely call an AST.

To work with JJTree, you need to be able to:

  1. Create the .jjt script that JJTree takes as input
  2. Write client-side code to walk and evaluate the parse tree that's produced at runtime

This article shows you how to do both. It doesn't cover everything, but it'll certainly get you started.

JJTree basics
JJTree is a preprocessor, and generating a parser for a particular BNF is an easy two-step process:

  1. Run JJTree against a so-called .jjt file; this emits an intermediate .jj file
  2. Compile that with JavaCC (this process was covered in Part 1)

Fortunately, the structure of a .jjt file is a minor extension of the .jj format that I showed you in Part 1. The primary difference is that JJTree adds a new syntactic node-constructor construct which lets you specify where and under what conditions parse-tree nodes are to be generated during the parse. In other words, this governs the shape and content of the parse tree that's constructed by the parser.

Listing 1 shows a simple JavaCC .jj script that's similar to the ones you saw in Part 1. For simplicity, I'm showing productions only.

Listing 1. A JavaCC grammar for simpleLang

void simpleLang()   : {}  { addExpr() <EOF> }
void addExpr()    : {}  { integerLiteral() ( "+" integerLiteral() )? } 
void integerLiteral() : {}  { <INT> }

SKIP  : { " " | "\t" | "\n" | "\r" }
TOKEN : { < INT : ( ["0" - "9"] )+ > }

This grammar states that a legal expression in this language consists of either:

  1. a single integer literal, or
  2. an integer literal, followed by a plus sign, followed by another integer literal.

The corresponding JJTree .jjt script (again, slightly abbreviated) might look something like the following:

Listing 2. The JJTree equivalent to the JavaCC grammar in Listing 1

SimpleNode simpleLang() : #Root       {}  { addExpr() <EOF> { return jjtThis; }}
void addExpr()          :             {}  { integerLiteral() 
                                          ( "+" integerLiteral() #Add(2) )? } 
void integerLiteral()   : #IntLiteral {}  { <INT> } 

SKIP  : { " " | "\t" | "\n" | "\r" }
TOKEN : { < INT : ( ["0" - "9"] )+ > }

This script adds several new syntactic features to those you've already seen. Let's just touch on the highlights for the moment. I'll fill in the details later.

Step-by-step through a JJTree grammar
Note first that JavaCC's procedural syntax for the topmost simpleLang() production now specifies a return type: SimpleNode. This, together with the embedded Java action, return jjtThis (a bit of JJTree hand-waving), specifies that calling the parser's simpleLang() method from your application code returns the root of the parse tree, which is then available for treewalking.

The parser invocation that looked like this in JavaCC:

    SimpleParser parser = new SimpleParser(new StringReader( expression ));


now looks like this:

    SimpleParser parser = new SimpleParser(new StringReader( expression ));

    SimpleNode rootNode = parser.simpleLang();

Note that the root node you're grabbing isn't simply of type SimpleNode. It's really of type Root, as indicated by the #Root directive in Listing 2 (although you don't use that fact in your calling code above). Root is a SimpleNode descendant, as is every node constructed by a JJTree-generated parser. I'll show you several of SimpleNode's built-in methods below.

The #Add(2) construct in the addExpr() production differs from the #Root directive above it in several ways:

  • It's parameterized. The tree builder uses a node stack during tree construction; the default behavior for a node constructor with no parameters is to place itself at the top of the parse tree that's under construction, popping all the nodes off the node stack that were created in the same node scope and hoisting itself into position as the parent of those nodes. The argument 2 tells the new parent (an Add node in this case) to adopt exactly two children, the two IntLiteral subnodes described in the following bullet. The JJTree documentation describes this process in more detail. Walking through the parse tree at runtime with a good debugger is another invaluable adjunct to understanding how tree building works in JJTree.
  • Of equal importance, the placement of the #Root directive outside the body of its production means that a Root node is generated every time this production is traversed (which admittedly only happens once in this particular case). However, the placement of the #Add(2) directive inside an optional "zero or one" term means that an Add node is only generated conditionally if the optional clause containing it is traversed during the parse -- in other words, if this production represents a true addition operation. When that happens, integerLiteral() is traversed twice, contributing a single IntLiteral node to the tree on each invocation. Both IntLiteral nodes become children of the Add node that invokes them. However, if the expression being parsed is a single integer, then the resulting IntLiteral node becomes a child of Root directly.

Pictures are worth a kiloword (to bring a old saw up to date). Here's a graphic representation of the two types of parse trees generated by the above grammar:

Figure 1: Parse tree for a single integer expression
Picture of parse tree for a single integer expression

Figure 2: Parse tree for an addition operation
Picture of parse tree for an addition operation

Let's look at the class hierarchy for SimpleNode in a bit more detail.

Working with the parse tree
Every node you declare in a .jjt script instructs the parser to generate a subclass of a JJTree SimpleNode. SimpleNode, in turn, implements a Java interface called Node. The source files for both of these classes are generated automatically by every JJTree script, along with a custom .jj file. Listing 1 shows the current example of a custom .jj file. In the current example, JJTree also emits source files for your own classes -- Root, Add, and IntLiteral -- as well as several additional helper classes not looked at here.

All SimpleNode subclasses inherit useful behavior. The SimpleNode method dump() is a case in point. It also serves as an example of my earlier contention that using parse trees makes debugging easier and consequently speeds development time. The following three-line snippet of client-side code instantiates the parser, invokes it, grabs the parse tree that's returned, and dumps a straightforward, textual representation of the tree to the console:

    SimpleParser parser = new SimpleParser(new StringReader( expression ));

    SimpleNode rootNode = parser.simpleLang();

The debug output for the tree in Figure 2 would be:


Aids to navigation
Another useful built-in SimpleNode method is jjtGetChild(int). When you're navigating downward through the parse tree on the client side and encounter an Add node, you'll want to grab its IntLiteral children, extract the integer values they represent, and add them together -- that, after all, is the purpose of the exercise. Assuming that addNode, shown in the next bit of code, is a variable representing the Add-type node we're interested in, we can access addNode's two children. (lhs and rhs are commonly used abbreviations for left-hand side and right-hand side, respectively.)

     SimpleNode lhs = addNode.jjtGetChild( 0 );
     SimpleNode rhs = addNode.jjtGetChild( 1 );

With everything you've done so far, however, you still don't have quite enough information to calculate the results of the arithmetic operation represented by this parse tree. Your current script has omitted one important detail: The two IntLiteral nodes in the tree don't actually contain the integers they purport to represent. That's because you didn't save their values into the tree when the tokenizer encountered them in the input stream; you need to modify your integerLiteral() production to do that. You also need to add a few simple accessor methods to SimpleNode.

Saving and restoring state
To store the value of scanned tokens into the appropriate nodes, add the following modifications to SimpleNode:

    public class SimpleNode extends Node
        String m_text;

        public void   setText( String text ) { m_text = text; }
        public String getText()              { return m_text; }

Change the following production in your JJTree script:

    void integerLiteral() : #IntLiteral {} <INT> } 

to this:

    void integerLiteral() : #IntLiteral { Token t; } 
                                        { t=<INT> { jjtThis.setText( t.image );} }

This production grabs the raw text value of the integer it's just encountered from t.image and uses your setText() setter to store that string in the current node. The client-side eval() code in Listing 5 shows how to use the corresponding getText() getter.

You can easily modify SimpleNode.dump() to emit the value of m_text for any node that's stored it during a parse -- I'll leave that as a proverbial exercise for you. This gives an even better visualization of what the parse tree looks like for debugging purposes. For example, if you parsed "42 + 1", a slightly modified dump() routine can produce the following useful output:


Putting it all together: A BNF snippet for XQuery
Let's put it all together and conclude by looking at a snippet of an actual, real-world grammar. I'll show you a very small subset of the BNF for XQuery, the W3C's specification for a query language for XML. (See Resources.) Most of what I'm saying here applies to XPath as well, since the two share much of the same grammar in common. I'll also look briefly at the issue of operator precedence and generalize the treewalking code into a full-fledged recursive routine that's able to handle arbitrarily complex parse trees.

Listing 3 shows the piece of the XQuery grammar that you'll work with. This snippet of BNF is from the November 15, 2002 working draft:

Listing 3: A portion of the XQuery grammar

[21]  Query              ::= QueryProlog QueryBody
[23]  QueryBody          ::= ExprSequence?
[24]  ExprSequence       ::= Expr ( "," Expr )*
[25]  Expr               ::= OrExpr
[35]  RangeExpr          ::= AdditiveExpr ( "to"  AdditiveExpr )*
[36]  AdditiveExpr       ::= MultiplicativeExpr (("+" | "-") MultiplicativeExpr )*
[37]  MultiplicativeExpr ::= UnionExpr (("*" | "div" | "idiv" | "mod") UnaryExpr )*

You're going to build just enough of a JJTree grammar script to handle the +, -, *, and div operators in productions [36] and [37], again with the simplifying assumption that the only datatype this grammar knows about is integers. This sample grammar is extremely small and does no justice to the richness of expression and data types supported by XQuery. However, it should give you a good head start in using JavaCC and JJTree, if you're going to build parsers for larger, more complex grammars.

Listing 4 shows the .jjt script. Note the options{} block at the top of the file. These options (there are a number of other switches available as well) specify, among other things, that tree building in this case operates in multi mode, where node constructors are used to explicitly name the types of generated nodes. The alternative (not explored here) is for productions to contribute only SimpleNode nodes to the parse tree and not subclasses thereof. That option is useful if you want to avoid proliferating node classes.

Note also that the original XQuery BNF frequently multiplexes multiple operators into the same production. I've demultiplexed these into separate productions in the JJTree script in Listing 4, since this makes the code on the client side more straightforward. To mulitiplex, simply store away the scanned operator's value, exactly as you did for integers.

Listing 4: The JJTree script for the XQuery grammar in Listing 3

options {

PARSER_BEGIN( XQueryParser )
package examples.example_2;
public class XQueryParser{}
PARSER_END( XQueryParser )

SimpleNode query()     #Root      : {} { additiveExpr() <EOF> { return jjtThis; }}
void additiveExpr()               : {} { subtractiveExpr() 
                                       ( "+" subtractiveExpr() #Add(2) )* }
void subtractiveExpr()            : {} { multiplicativeExpr() 
                                       ( "-" multiplicativeExpr() #Subtract(2) )* }
void multiplicativeExpr()         : {} { divExpr() ( "*" divExpr() #Mult(2) )* }
void divExpr()                    : {} { integerLiteral() 
                                       ( "div" integerLiteral() #Div(2) )* }
void integerLiteral() #IntLiteral :    { Token t; }  
                                       { t=<INT> { jjtThis.setText(t.image); }}

SKIP  : { " " | "\t" | "\n" | "\r" }
TOKEN : { < INT : ( ["0" - "9"] )+ > }

This .jjt file introduces several new features. For one, the arithmetic productions in this grammar are now iterative: Their optional second terms are expressed using a * (zero or more) occurrence indicator, as opposed to the ? (zero or one) notation in Listing 2. The parser emitted by this script can parse arbitrarily long expressions such as "1 + 2 * 3 div 4 + 5".

Implementing precedence
This grammar also knows about operator precedence. You would expect multiplication, for example, to have a higher precedence than addition. In practical terms, this means an expression like "1 + 2 * 3" would be evaluated as "1 + ( 2 * 3 )" and not "( 1 + 2 ) * 3".

Precedence is achieved using the cascading style, where each production calls the higher-precedent production immediately following it. That, as well as the placement and format of the node constructors, guarantees that the parse tree is generated in the proper conformation so that treewalking does the right thing. It might be easier to grasp this with some visual aids.

Figure 3 shows the parse tree generated by this grammar that correctly enables you to evaluate "1 + 2 * 3" as "1 + ( 2 * 3 )". Note that the Mult operator binds its terms tighter than does Plus, which is exactly what you want:

Figure 3. A properly formed tree
Picture of a properly formed tree

And, Figure 4 shows a tree (which this grammar doesn't generate) indicating that you (incorrectly) wanted to evaluate this as "(1 + 2) * 3".

Figure 4. An incorrectly formed tree
Picture of an incorrectly formed tree

Walking the parse tree client-side
I conclude as promised with a listing for the client-side code that invokes this parser and walks the parse tree it generates, using a simple but powerful, recursive eval() function to do the right thing with each node it encounters during the treewalk. Comments in Listing 5 provide additional detail on internal JJTree workings.

Listing 5. An easily generalizable eval() routine

    // return the arithmetic result of evaluating 'query'
    public int parse( String query )
        SimpleNode root = null;

   // instantiate the parser
        XQueryParser parser = new XQueryParser( new StringReader( query ));

            // invoke it via its topmost production
            // and get a parse tree back

            root = parser.query();
        catch( ParseException pe ) {
            System.out.println( "parse(): an invalid expression!" ); 
        catch( TokenMgrError e )  { 
            System.out.println( "a Token Manager error!" );  

        // the topmost root node is just a placeholder; ignore it.

        return eval( (SimpleNode) root.jjtGetChild(0) );

    int eval( SimpleNode node )
        // each node contains an id field identifying its type.
        // we switch on these. we could use instanceof, but that's less efficient
        // enum values such as JJTINTLITERAL come from the interface file
        // SimpleParserTreeConstants, which SimpleParser implements.
        // This interface file is one of several auxilliary Java sources 
        // generated by JJTree. JavaCC contributes several others.
        int id =;

        // eventually the buck stops here and we unwind the stack
        if ( == JJTINTLITERAL )
            return Integer.parseInt( node.getText() );

        SimpleNode lhs =  (SimpleNode) node.jjtGetChild(0);
        SimpleNode rhs =  (SimpleNode) node.jjtGetChild(1);

        switch( id )
            case JJTADD :       return eval( lhs ) + eval( rhs );
            case JJTSUBTRACT :  return eval( lhs ) - eval( rhs );           
            case JJTMULT :      return eval( lhs ) * eval( rhs );
            case JJTDIV :       return eval( lhs ) / eval( rhs );
            default :

                throw new java.lang.IllegalArgumentException(
                                  "eval(): invalid operator!" );

If you want to see a much beefier version of an eval() function that handles much of the real XQuery grammar, feel free to download a copy of my open-source XQuery implementation, XQEngine. (See Resources.) Its TreeWalker.eval() routine cases on some 30-odd XQuery node types. A .jjt script is provided.


  • Participate in the discussion forum on this article. (You can also click Discuss at the top or bottom of the article to access the forum.)

  • Review Part 1 of this article for a brief discussion of grammars, parsers, and BNF, and an introduction to JavaCC. You'll also find sample code that uses JavaCC to build a custom parser, starting from a BNF description of the grammar.

  • Check out the free (though not open-source) distribution for JavaCC and JJTree.

  • Find out more about the W3C's XQuery and XPath specifications at the XML Query home page.

  • XQEngine is the author's Java-based open-source implementation of an XQuery engine.

  • Want to find out more about BNF? Check out

  • Find more information on the technologies covered in this article at the developerWorks XML and Java technology zones.

  • IBM WebSphere Studio provides a suite of tools that automate XML development, both in Java and in other languages. It is closely integrated with the WebSphere Application Server, but can also be used with other J2EE servers.

  • Find out how you can become an IBM Certified Developer in XML and related technologies.

About the author
Howard Katz lives in Vancouver, Canada, where he is the sole proprietor of Fatdog Software, a company that specializes in software for searching XML documents. He's been an active programmer for nearly 35 years (with time off for good behavior) and is a long-time contributor of technical articles to the computer trade press. Howard cohosts the Vancouver XML Developer's Association and is the editor of an upcoming book from Addison Wesley, The Experts on XQuery, a compendium of technical perspectives on XQuery by members of the W3C's Query working group. He and his wife do ocean kayaking in the summer and backcountry skiing in the winter. You can contact Howard at

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