Groovy-type builders and JSON initializers in Xtend

September 3, 2012 Leave a comment

One of the nicer features of dynamic languages like Ruby, Groovy, etc. is the possibility to easily implement builders which are constructs to build up tree-like structures in a very succinct a syntactically noise free way. You can find some Groovy examples here – have a special look at the HTML example. Earlier, Sven Efftinge has written a blog on the implementing the same type of builders using Xtend. My blog post will expand a little on his post by providing the actual code and another example.

The main reason that builders come naturally in dynamic languages is that metaprogramming allows adding “keywords” to the language without the need to actually define them in the form of functions. In the case of HTML, these “keywords” are the tag names. Statically-typed languages like Java or Xtend do not have that luxury (or “luxury” as the construct can easily be misused) so we’ll have to do a little extra.

The HTML example

You’ll find Sven’s original example reproduced in HtmlDocumentExample . Note that because of the point mentioned above, we need to have compile-time representations of the HTML DOM elements we’re using. Sven has written these manually but I’m afraid that I’m lazy to do that so I opted for a generative approach. Apart from that, the example works exactly the same, so I’ll refer to his original blog for the magic details – some of which I’ll re-iterate for the JSON example below.


Some basic HTML DOM element types are provided by the BaseDomElements file. Note two nice features of Xtend 2.3+: one file can hold multiple Xtend classes and the use of the @Data annotation as a convenient way to define POJOs – or should those be called POXOs? ;) The POJOs for the other DOM elements are generated by the GenerateDomInfrastructure main class: note they are generated as POXOs which are then transpiled into Java. After running the GenerateDomInfrastructure main class and refreshing the Eclipse project, the  HelpDocumentExample class should compile.

A JSON example

You can find the JSON example in JsonResponseExample. For convenience and effect, I’ll reproduce it here:

class JsonResponseExample {

    @Inject extension JsonBuilder

    def example() {
            "dev"        => true,
            "myArray"    => array("foo", "bar"),
            "nested"     => object("answer" => 42)


To be able to compile this example, you’ll need my fork of Douglas Crockford’s Java JSON library with the main differences being that it’s wrapped as an Eclipse plug-in/OSGi bundle and it’s (as properly as manageable) generified. In addition to the GitHub repo, you can also directly download the JAR file.

As with the HTML example, the magic resides in the line which has a JsonBuilder Xtend class Guice-injected as an extension, meaning that you can use the functions defined in that class without needing to explicitly refer to it. This resembles a static import but without the functions/methods needing to be static themselves. The JsonBuilder class has two factory functions: object(..) builds a JSONObject from key-value pairs and array(..) builds a JSONArray from the given objects.

The fun part lies in the overloading of the binary => operator by means of  the operator_doubleArrow(..) function which simply returns a Pair object suitable for consumption by the object(..) factory function. This allows us to use the “key => value” syntax demonstrated in the example. Note that the => operator has no pre-existing meaning in Xtend – the makers of Xtend have been kind enough to provide hooks for a number of such “user-definable” operators: see the documentation.

I’m still trying to find a nice occasion to use the so-called “spaceship” or “Elvis” operators: now that would be positively…groovy ;)


I failed to notice earlier that Xtend already has an -> operator which does exactly the same thing that our => operator does. Also, the “Elvis” ?: operator already has a meaning: “x ?: y” returns x if it’s non-null and y otherwise. This makes for a convenient way to set up default values. You’ll find both overloading definitions in the org.eclipse.xtext.xbase.lib.ObjectExtensions class.

Categories: Xtend(2)

Polymorphic dispatch in Xtend

August 3, 2012 1 comment

Polymorphic dispatch (or or multimethods as its also called) is a programming language construct which chooses a code path based on runtime types instead of types that are inferred at compile. The poor man’s method of achieving such behavior would be to litter your code with prose like this:

if( x instanceof TypeA ) { (x as TypeA).exprA }
else if( x instanceof TypeB ) { (x as TypeB).exprB }
else ...

Xtend 2.x offers two much better constructs to do polymorphic dispatching:

  1. Through the use of the dispatch modifier for function defs – this construct is Xtend’s “official” polymorphic dispatch.
  2. Through the use of the switch statement and referring to types instead of cases.

These are better than the poor man’s method because they are declarative, i.e.: they express intent much more clearly and succinctly. Though both constructs have a lot in common, there are some marked differences and Best Practices for safe guarding type safety which I’ll discuss in the blog.

The example

Consider the following Xtend code – note that the syntax coloring is lacking a bit, but WordPress doesn’t fully understand Xtend – …yet…. Also note that since Xtend2.3 you can have more than one Xtend class in one file.

class CommonSuperType { ... }
class TypeA extends CommonSuperType { ... }
class TypeB extends CommonSuperType { ... }
class TypeC extends CommonSuperType { ... }
class UnrelatedType { ... }
class Handler {

  def dispatch foo(TypeA it) { it.exprA }
  def dispatch foo(TypeB it) { it.exprB }

  def bar(CommonSuperType it) {
    switch it {
      TypeA: it.exprA
      TypeB: it.exprB

For simplicity’s sake, let’s assume that exprA and exprB both return an int. The Xtend compiler generates two public methods in the Java class Handler – one for foo, one for bar. Both of these have the same signature: int f(CommonSuperType), where f = foo or bar. In addition, for each foo dispatch function, Xtend generates a public method with signature int _foo(t), where t=TypeA or TypeB – note the prefixed underscore. The actual polymorphic dispatch then happens in “combined” foo(CommonSuperType) method, actually through the previously demonstrated poor man’s method.

By the way: a user-friendly way to inspect the “combined” method is the Outline which will group the dispatch functions belonging together under the combined signature.

Note that the foo and bar method ends up with CommonSuperType as the type of its parameter. This is because CommonSuperType is the most specific common super type of TypeA and TypeB – deftly implied by the name – and Xtend infers that as the parameter’s type for the “combined” method. In general, Xtend will compute the most specific common super type across all dispatch functions, on a per-argument basis. In case of the bar method we declared ourselves what the parameter type is.

As demonstration, add the following code to the Handler class and see what happens:

  def dispatch foo(TypeC it) { it.exprC }

(Assume that exprC again returns an int.)

The generated foo and bar methods are functionally nearly identical, the difference being that foo explicitly throws an IllegalArgumentException mentioning the unhandled parameter type(s) in its message, in case you called it with something that is a CommonSuperType but neither of TypeA nor of TypeB. The bar method does no such thing and simply falls through the switch, returning the appropriate default value: typically null but 0 in our int-case. To remedy that, you’ll have to add a default case which throws a similar exception, like so:

  def bar(CommonSuperType it) {
    switch it {
      TypeA: it.exprA
      TypeB: it.exprB
        throw new IllegalArgumentException("don't how to handle sub type " + it.^class.simpleName)

In case you already have sensible default case, you’re basically out of luck.

Potential mistakes

Both approaches have their respective (dis-)advantages which I’ll list comprehensively below. In both cases, though, it’s relatively easy to make programmers’ mistakes. The most common and obvious ones are:

  1. The parameter type of the “combined” foo method is inferred, so if you add a dispatch function having a parameter type which does not extend CommonSuperType, then the foo method will wind up with a more general parameter type – potentially Object. This means that the foo method will accept a lot more types than usually intended and failing miserably (through a thrown IllegalArgumentException) on most of them. This is especially dangerous for public (which happens to be the default visibility!) function defs.
  2. Xtend will not warn you at editor/compile time about the “missing” case TypeC: it’s a sub type of CommonSuperType but not of TypeA nor of TypeB. At runtime, the bar method will simply fall through and return 0.
  3. The return type of the combined method is also inferred as the most specific common super type of the various return types – again, potentially Object. This is usually much less of a problem because that inferred type is checked against the parameter type of clients of the combined method.

This shows that these constructs require us to do a little extra to safe guard the type safety we so appreciate in Xtend.

Advantages and disadvantages of both constructs

We list some advantages and disadvantages of both constructs. Advantages of the dispatch construct:

  • Provides more visual code space. This is useful if the handling of the separate types typically needs more than 1 line of code.
  • Explicit handling of unhandled cases at runtime.

Disadvantages of the dispatch construct:

  • Automagically infers parameter types of the “combined” method as the most common super types. In case of a programmer error, this may be (much) too wide.
  • Takes up more visual code space/more syntactic noise.

Advantages of the switch construct:

  • Takes up less visual code space. This is useful if the handling of the separate types doesn’t need more than one line of code.
  • It’s a single expression, so you can use it as such inside the function it’s living in. Also, you can precompute “stuff” that’s useful for more than one case.

Disadvantages of the switch construct:

  • Fall-through of unhandled cases at runtime, resulting in an (often) non-sensical return value. You have to add an explicit default case to detect fall-through.

Mixing polymorphic and ordinary dispatch

Since Xtend version 2.3, you are warned about dispatch functions having a compatible signature as a non-dispatch function and vice versa. As an example, consider the following addition to the Handler class:

  def foo(TypeC it) { it.exprC  }
  def foo(UnrelatedType it) { it.someExpr }

Here, exprC again returns an int, but someExpr may return anything. Note that both functions are not of the dispatch persuasion.

The first line is flagged with the warning “Dispatch method has same name and number of parameters as non-dispatch method”, which is a just warning in my book. However, this warning is also given for the second line, as well as for the first two foo functions. (Note that the warnings are also given with only one of these extra functions present.) In that case, it’s not always a helpful warning but it does riddle your code file with warnings.

To get rid of the warnings, I frequently make use of the following technique:

  • “Hide” all dispatch functions by giving them (and only these) an alternate name. My personal preference is to postfix the name with an underscore, since the extra _ it’s visually inconspicuous enough to not dilute the intended meaning. Also, give them private visibility to prevent prying eyes.
  • Create an additional function with the same signature as the “combined” method for the dispatch functions, calling those.

The net result is that you get rid of the warnings, because there’s no more mixture of dispatch and non-dispatch functions with compatible signatures. Another upshot is that the signature of the “combined” method is now explicitly checked by the additional function calling it – more type safety, yeah! Of course, a disadvantage is that you need an extra function but that typically only is one line of code.

In the context of our example, the original two foo functions are replaced by the following code:

  def foo(CommonSuperType it) { foo_ }

  def private dispatch foo_(TypeA it) { it.exprA }
  def private dispatch foo_(TypeB it) { it.exprB }
Categories: The How, Xtend(2)

The ASmaP Principle (part 2)

April 23, 2012 Leave a comment

To recount the gist of the previous blog: the ASmAP-principle strives to minimize the footprint of your project/application in terms of code base size, dependencies and configuration complexity. (In fact, it’s a particular re-statement of the KISS-principle.)

What’s the use?

The main reason to follow this principle is that projects/applications tend to grow fast to a point where it’s quite impossible to fit a good mental model of it into your brain in any reasonable amount of time. In turn, this inhibits you in becoming productive on those projects and making the right coding decisions. By constantly making an effort to reduce incidental complexity, you’ll make development on the project more effective and productive – not only in the long run, but also in the short run. You should see a decrease of time-to-market, bug count, maintenance costs after a short time, while hooking up extra devs to the project and effectively communicating with your customer becomes easier.

The ASmaP Principle is not about being as smart as possible in as few lines of code, it’s about obtaining/using/achieving the simplest possible solution, but not simpler – free after Albert Einstein. It also pertains to documentation: provide just enough text to clarify what your code is doing beyond what the code already clearly expresses on its own. This is also an incentive to write your code in a way which makes documentation largely unnecessary. I usually get away with some explanation about a class as a whole and some usage patterns.

Now, I’m not advocating premature optimization (of the performance of implemented functionality) here. I do think that it is the root of at least a lot of evil and any optimization effort should be based on profiling. Moreover, optimization is usually the source of a lot of incidental complexity since it doesn’t expand functionality as such only the performance of the implementation. As an example, consider caching: it requires adding a layer of indirection, thinking about invalidation and usually comes with a bunch of assumptions and runtime behaviors which are

Oh, and I certainly don’t advocate minification or obfuscation :)

Kill your dependencies

Dependencies on external libraries, frameworks, components, runtimes, environments and what-have-you -i.e., all this is within your direct sphere of influence but which you didn’t actually create yourself- are often the biggest source of incidental complexity. Each of these dependencies add their own dependencies but more importantly, they add to the information you need to carry around in your head: what’s the library’s API like, how to include the library correctly, how to instantiate the component, what are the peculiarities of this runtime, what do I need to configure in that environment to have it switch between dev/test/acc/prod?

Obviously, you can document much of this, but documentation has to be kept up-to-date and you’ll always need to remember a non-trivial amount of information to even be able to get things working at all, let alone productively.

Furthermore, dependencies tend to solve only half of a problem that technical rather than functional in nature – in other words: it’s falls squarely in the category of incidental complexity. My favorite example is Hibernate: it gives you (un-)marshalling of Java objects from/to a relational database, but at the price of having to write XML mapping files (well, in the pre-@annotation days, at least) which you need to keep in sync with both the Java classes and DB schema. Were I to generate the latter, I could just as well generate the necessary (un-)marshalling methods. (With annotations most of the meta data resides in the Java class, at least.)

To gauge whether you have too many dependencies in your Java project, I propose the following:

The Maven Rule: if your project uses Maven for dependency management, you have too many dependencies. Period.

While Maven undeniably makes the whole dependency management problem more bearable, it generally expands the same problem by making it just too friggin’ easy to drag in more dependencies without every really wondering whether that’s a good idea. Think about what you really need from dependency #37 that you put in your project. Some questions you could ask yourself:

  1. Is the same functionality already implemented (more-or-less equivalently) somewhere else in your project (typically using another dependency-of-ill-repute)? – If so, Refactor and remove all but the most-used dependency. Sometimes, you’ll find that you’re better off writing your own implementation without using external dependencies to snugly fit your needs.
  2. Does it solve your entire technical problem? If not, are better frameworks available?
  3. Does it provide an complete paradigm/way-of-thinking/-working (such as the Google Guice or Apache Wicket frameworks) or does it “only” provide some utility functions (such as Google Guava)? In the latter case, see the first point.

Note that I’m not advocating NIH here, but mind that there’s also no point in shoehorning a problem in a particular shape so that it happens to fit some “reusable” code: the fit is often quite bad and the primary code not very aesthetically pleasing. That’s a general problem with reuse (I have): all code makes a lot of implicit assumptions and unless these assumptions are met by your problem (domain) on a grand scale, things are not going to fly. The most rewarding uses of reusable components are often those where the component either matches the problem domain perfectly or is completely functionally orthogonal.

Not only can you reduce the sheer number of artifacts on which you’re dependent, you can also make sure that the number of direct dependencies (i.e., part X makes direct use of dependency Y by explicit reference such as an import) is as small as possible. This is analogous to your project architect insisting that application layers only interact in very controlled ways (and preferably through DTOs). Often, you can hide a large number of dependencies in a specific sub system which then governs use of and acces to its dependencies.

Categories: SD in general

Language Workbench Challenge 2012

March 31, 2012 Leave a comment

Apologies for the radio silence: it’s been way too long since I’ve done some blogging.

In my defense, the last couple of months have been pretty busy: I’ve been working a lot on my language workbench (my own startup) and I also got heavily involved with another startup. Last week I was in Cambridge, UK for the Code Generation 2012 conference and the co-located Language Workbench Challenge during which I presented said language workbench for the first time – more on that in a minute.

As it turns out, the next couple of months are going to be slightly less busy and should allow me to write some more blogs. I got some material pent up already that’s good to go after a little spit-shine.

By the way: I was thrilled to notice that views have not really dropped all that much during the hiatus since my last blog post! :)

Language Workbench Challenge 2012

The #lwc2012 is an event that co-located with the Code Generation conference and takes places a day before that. The essence of the #lwc2012 -at least: to me- is to challenge the various language workbench creators with new ideas, levels of maturity, etc.. The sheer variance among the “contenders” is so big that it’s quite impossible to judge them on any objective and/or quantitative scale – this explains why the nomer Competition would be quite unjust. For more information on the event itself, I’m going to refer to the official site. This will probably be updated soon by organizers Angelo Hulshout and Paul Zenden with a nice summary of the event and possibly even videos of the various presentations (including mine).

My primary goal was to gather feedback on my ideas around and implementation of Más which a Cloud-based domain language workbench that makes creation of domain-specific languages and using these to model “stuff”. The feedback I got during the challenge was quite positive, in general. I already knew that UI and the editing behavior still leaves much to be desired but I was positively surprised by the fact that people other than myself were able to use it to do parts of the extension assignment. The fact that you can do graphical modeling with nothing more than regular HTML, CSS, Javascript plus a bit of HTML5 Canvas seemed to surprise plenty of people.

On the whole, the assignment -creating a modeling environment for the Piping & Instrumentation domain, including code generation and preferably doing or triggering simulation- itself was somewhat cumbersome for several reasons.

First of all, the reference implementation made use of a rather old-fashioned piece of proprietary Windows software which didn’t really provide a very clear for the code generation and triggering of the simulation. To get around that, I simply took the MetaEdit+ implementation which the nice people of MetaCase were good enough to share with the world at large, ran their code generation against an equivalent model and re-implemented that. I didn’t bother with the Windows thing beyond that.

Secondly, the two “domain experts” (or at least, the two people most knowledgeable on the domain, being Paul Zenden and Juha-Pekka Tolvanen) on site were also two challengers. Especially the extension assignment could have benefited from a clarification by unbiased domain stakeholders. Angelo and I have already exchanged some ideas on how to do that differently next year – in particular: it would be nice to be able to consult real, on-site domain stakeholders which would be available during the preparation of the assignment as well. The extension assignment also didn’t really address the workbenches’ capability to really extend the language.

Overall, the event was quite inspiring to me and has provided me with encouragement to continue with the development of Más as well as with a couple of ideas I didn’t have beforehand. Stay tuned for more on that in the future :)

Categories: DSLs, MDSD

New Year’s Resolution: the ASmAP Principle (part 1)

January 2, 2012 14 comments

Happy New Year, everyone!

Seeing that we’ve safely progressed into 2012, it’s time for New Year’s Resolutions. As a suggestion for a NYR in software engineering, I’d like to suggest following the

ASmAP-principle, where ASmAP == As Small As Possible

Ever since I started to program on the MSX2, I’ve been wondering where all that extra computing power, memory and disk space that all my subsequent work horses have been endowed with, went to. Obviously, the amount of pixel estate has grown quite a bit (from a measly 0.1Mpixel in 4-bit color to over 1.2 in 32-bit color on the quite modest screen of my MBP 15″), but that doesn’t really explain why my Eclipse typically reports around 200MB of heap space in use: I sincerely doubt that the size of my source code (or even the sheer bytecode size of my compiled classes for a fairer comparison) has grown by a factor of  7000 from the roughly 24KB of memory that was available for MSX BASIC. It also doesn’t explain why whole slews of applications aren’t really more responsive these days than they were in “ye’ olden days”.

Of course, I know that running a JVM and OO languages on it is intrinsically more memory intensive than assembler or what are essentially token streams (the in-memory representation of an MSX BASIC program). But I simply refuse to accept that we need so many more bytes to write even the simplest of programs on our modern-day OSs, VMs and IDEs. I think a large part of this growth stems precisely from Moore’s Law in action: because we have a lot of memory and extra CPU cycles per second, we tend to use them – not per se for more functionality, nicer graphics and such, but also to make programming easier for ourselves without actually delivering more business value or quality.

I’ve seen my fair share of “programming by copy-paste” and the consequences of that: bloated code bases with a lot of (usually inconsistent) duplication, a build process that takes ages to finish and is brittle, a development environment that takes days to set up (possibly after sacrificing a few kittens in the process, just to get it to work at all) and an enormous amount of dependencies (“Maven makes this so easy to manage”) consisting of all kinds of stop-gap frameworks which never seem to solve a business problem and only seem to solve halve of a technical problem. The end result is a gargantuan and monolithic Thing™ that’s hard to fix, hard to alter and hard to hand off to anyone so you’re stuck with it until eternity. Sounds familiar? :)

I think it’s this tendency to copy-paste our way around development, without taking the time to properly Refactor your stuff and reflect on your solutions, which accounts for the enormous gap between a typical application’s footprint and the value it delivers. As a solution, I propose to optimize something that’s relatively easy to measure: the footprint of your code base, in terms of pure source size but also taking into account the amount of re-used “stuff” such as libraries/frameworks, the time needed to build your project and deploy the application and the number of dependencies. In other words: make your project As Small As Possible. (Note that size is a lot easier to quantify than, say, complexity or quality.)

The overruling motivation for doing this is something which hasn’t changed the last few millennia: the amount of information our brains can interpret, process and store (in a limited amount of time). It is this characteristic which is the prime limitation in any project and especially those involving more than one developer – i.e., the typical ones. The amount of information in a software project is a lot bigger than the sheer code size conveys because there are all kinds of connections between various parts of the code base which you need to understand in order to add or change anything in the code. It’s my impression that the complexity is roughly a function of the code size base multiplied by the number of layers/aspects in the architecture.

So, the larger a project’s footprint, the harder it is to understand: not only for your co-workers (who are presumably stupid gits which couldn’t program their way out of a tin can), but even for yourself. The less you understand about your project, the less effective and productive you’re going to be. In other words: you need to build up a mental model of the project (which is something I’ve blogged about earlier) and hope it will fit in your brain in the short time you have. Given that you and your team mates can’t grow extra brains, you’ll have to utilize the available mental processing power as efficiently as possible. Note that adding extra single brains to the project doesn’t provide a solution, because each individual brain will not be able to grok the entire project if you couldn’t do so yourself to begin with.

In the next installment, I’ll discuss some simple approaches to follow the ASmAP-principle.

Xtext tip: “synthetic” parser rules

December 22, 2011 2 comments

This is a quick one to share a simple trick which may come in handy when creating an Xtext grammar.

Let’s say your grammar has a type rule T1 (i.e., a rule which corresponds to an EClass in the Ecore meta model). Let’s also say that some other type rule T2 composes that type somehow, i.e., it has a feature someT1 to which something of type T1 is assigned. Let’s say that you want to limit the syntactic possibilities for the composition of a T1 instance somewhat, e.g. in the case that T1 is a group of alternatives but a few alternatives are invalid when used inside T2.

This is a wholly legitimate situation because Xtext grammars usually have a number of responsibilities at the same time, amongst which are defining (1) a mapping to an Ecore meta model and defining (2) the syntax of the DSL.

Let’s sum this situation up in some grammar code:

T1: A1 | A2 | A3;

T2: 'a-t2' someT1=T1;

Let’s say that we would want to exclude A3 from the possible T1‘s in any T2. We could do this via a validation which simply checks the someT1 feature of any T2, reporting an error if it’s an A3. But that means that the parser itself still allows an A3 at that spot which could open up a whole can of smelly worms – e.g., left-recursion or some ambiguity. Also, the content assist that comes out-of-the-box will make syntax suggestions for A3.

Hence, we would like to inform the parser about the restricted syntax. One possibility would be:

T1: T1WithoutA3 | A3;

T1WithoutA3: A1 | A2;

T2: 'a-t2' someT1=T1WithoutA3;

This works perfectly, but it also ‘pollutes’ the meta model a bit. Since the meta model is mostly consumed by downstream clients like interpreters and code generators, this would only cause confusion. But more importantly: if we re-use an existing Ecore meta model (by means of the returns clause) this solution is not possible, since we would have to add a super type T1WithoutA3 to the A1 and A2 types which are sealed inside the re-used Ecore meta model – Xtext will issue an error as soon as we try it.

The clean solution consists of using something which I’ve termed a “synthetic parser rule” and has the following form:

T1:  A1 | A2 | A3;

T1WithoutA3 returns T1: A1 | A2;

T2: 'a-t2' someT1=T1WithoutA3;

Now there’s no pollution of the meta model, but the syntax will be restricted as we’d like it. Note that is very much something which is part of the standard Xtext repertoire but this trick works especially well in the face of type hierarchies and re-used Ecore meta model or inheriting Xtext grammars.

Using syntactic predicates in Xtext, part 2

December 20, 2011 2 comments

This blog is a continuation of the previous one about how to use syntactic predicates in Xtext. As promised, I’ll provide a few more examples, most of which come from the realm of GPL-like languages.

But first, a little summary is in order. As stated in the previous blog, a syntactic predicate is an annotation in an Xtext grammar which indicates to the ANTLR parser generator how a (potential) ambiguity should be resolved by picking the (first) one which is decorated with ‘=>‘. The annotation can be applied to:

  • a(n individual) keyword (such as ‘else‘),
  • a rule call (unassigned or as part of an assignment) and
  • a grouped parse expression, i.e. a parse expression between parentheses.

One thing to keep in mind -not only for syntactic predicates but in general- that an Xtext grammar has at least three and often four responsibilities:

  1. defining the lexing behavior through definition and inclusion of terminals;
  2. defining the parsing behavior through parser rules which determine how tokens are matched and consumed;
  3. defining how the model is populated;
  4. (when not using an existing Ecore model) defining the meta model.

Syntactic predicates influence the second of these but not the others. It is, after all, a syntactic predicate, not a semantic one – which Xtext doesn’t have in any case. Just as without using syntactic predicates, parsing behavior is not influenced by how the model is populated: instead, it is governed solely by the types of the tokens it receives from the lexer. This is easily forgotten when you’re trying to write grammars with cross-references like this:

SomeParserRule: Alternative1 | Alternative2;
Alternative1: ref1=[ReferencedType1|ID];
Alternative1: ref2=[ReferencedType2|ID];

In this case, the parser will always consume the ID token as part of Alternative1 even if its value is the (qualified) name of something of ReferencedType2. In fact, ANTLR will issue a warning about alternative 2 being unreachable so it is disabled. For a workaround this problem, see this older blog: it uses a slightly different use case as motivation but the details are the same. The only thing a syntactic predicate can do here is to explicitly favor one alternative over the other.

Some examples from Xbase

The Xtend and the Xbase languages that Xtext ships with both use plenty of syntactic predicates to avoid ambiguities in their grammars and to avoid having to use backtracking altogether. This already indicates that syntactic predicates are a necessary tool, especially when creating GPL-like or otherwise quite expressive DSLs. Note again that syntactic predicates are typically found near/inside optional parts of grammar rules since optionality automatically implies an alternative parsing route.

A good example can be found in the Xbase grammar in the form of the XReturnExpression rule: see GitHub. It uses a syntactic predicate on an assignment to force the optional XExpression following the ‘return‘ keyword to be parsed as part of the XReturnExpression rather than being an XExpression all on its own – which would have totally different semantics, but could be a viable interpretation considering Xtend doesn’t require separating/ending semi-colons.

The Xbase grammar also shows that syntactic predicates are an effective way to disambiguate the use of pairs of parentheses for denoting a list of arguments to a function call from that for grouping inside an expression: once again, see GitHub – here, the syntactic predicate applies to a grouped parse expression, i.e. everything between the parentheses pair starting just before the ‘=>‘.

Unforeseen consequences

Even if you don’t (have to) use syntactic predicates yourself, it’s important to know of their existence. As an example, the other day I was prototyping a DSL which used the JvmTypeReference type rule from Xbase followed by an angled bracket pair (‘<‘, ‘>’) which held ID tokens functioning as cross-references. I was momentarily surprised to see parse errors arise in my example along the lines of “Couldn't resolve reference to JvmType 'administrator'.” The stuff between the angled brackets was being interpreted as a generic type parameter!

It turns out that the  JvmTypeReference parser rule uses a syntactic predicate on an angled bracket pair surrounding generic type parameters. This explains both the behavior and the lack of warnings by ANTLR about grammar ambiguities. You’d probably have a hard time figuring out this behavior before finding an innocuous ‘=>here. In the end, I changed “my” angled brackets to square brackets to resolve this. This shows that syntactic predicates, just like backtracking, can be a double-edged sword: it can solve some of your problems but you have to really know how it works to be able to understand what’s going on.

I hope that this was useful for you: please let me know whether it is! I’m not planning on a third installment but you never know: a particular enticing use case might just do the trick.


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