I'm writing a parser for an old proprietary report specification with ANTLR and I'm currently trying to implement a visitor of the generated parse tree extending the autogenerated abstract visito class.
I have little experience both with ANTLR (which I learned only recently) and with the visitor pattern in general, but if I understood it correctly, the visitor should encapsulate one single operation on the whole data structure (in this case the parse tree), thus sharing the same return type between each Visit*() method.
Taking an example from The Definitive ANTLR 4 Reference book by Terence Parr, to visit a parse tree generated by a grammar that parses a sequence of arithmetic expressions, it feels natural to choose the int return type, as each node of the tree is actually part of the the arithmetic operation that contributes to the final result by the calculator.
Considering my current situation, I don't have a common type: my grammar parses the whole document, which is actually split in different sections with different responsibilities (variable declarations, print options, actual text for the rows, etc...), and I can't find a common type between the result of the visit of so much different nodes, besides object of course.
I tried to think to some possible solutions:
I firstly tried implementing a stateless visitor using object as
the common type, but the amount of type casts needed sounds like a
big red flag to me. I was considering the usage of JSON, but I think
the problem remains, potentially adding some extra overhead in the
serialization process.
I was also thinking about splitting the visitor in more smaller
visitors with a specific purpose (get all the variables, get all the
rows, etc.), but with this solution for each visitor I would
implement only a small subset of the method of the autogenerated
interface (as it is meant to support the visit of the whole tree),
because each visiting operation would probably focus only on a
specific subtree. Is it normal?
Another possibility could be to redesign the data structure so that
it could be used at every level of the tree or, better, define a generic
specification of the nodes that can be used later to build the data
structure. This solution sounds good, but I think it is difficult to
apply in this domain.
A final option could be to switch to a stateful visitor, which
incapsulates one or more builders for the different sections that
each Visit*() method could use to build the data structure
step-by-step. This solution seems to be clean and doable, but I have
difficulties to think about how to scope the result of each visit
operation in the parent scope when needed.
What solution is generally used to visit complex ANTLR parse trees?
ANTLR4 parse trees are often complex because of recursion, e.g.
I would define the class ParsedDocumentModel whose properties would added or modified as your project evolves (which is normal, no program is set in stone).
Assuming your grammar be called Parser in the file Parser.g4, here is sample C# code:
public class ParsedDocumentModel {
public string Title { get; set; }
//other properties ...
}
public class ParserVisitor : ParserBaseVisitor<ParsedDocumentModel>
{
public override ParsedDocumentModel VisitNounz(NounzContext context)
{
var res = "unknown";
var s = context.GetText();
if (s == "products")
res = "<<products>>"; //for example
var model = new ParsedDocumentModel();
model.Title = res; //add more info...
return model;
}
}
Related
Extensible records were one of the most amazing Elm's features, but since v0.16 adding and removing fields is no longer available. And this puts me in an awkward position.
Consider an example. I want to give a name to a random thing t, and extensible records provide me a perfect tool for this:
type alias Named t = { t | name: String }
„Okay,“ says the complier. Now I need a constructor, i.e. a function that equips a thing with specified name:
equip : String -> t -> Named t
equip name thing = { thing | name = name } -- Oops! Type mismatch
Compilation fails, because { thing | name = ... } syntax assumes thing to be a record with name field, but type system can't assure this. In fact, with Named t I've tried to express something opposite: t should be a record type without its own name field, and the function adds this field to a record. Anyway, field addition is necessary to implement equip function.
So, it seems impossible to write equip in polymorphic manner, but it's probably not a such big deal. After all, any time I'm going to give a name to some concrete thing I can do this by hands. Much worse, inverse function extract : Named t -> t (which erases name of a named thing) requires field removal mechanism, and thus is not implementable too:
extract : Named t -> t
extract thing = thing -- Error: No implicit upcast
It would be extremely important function, because I have tons of routines those accept old-fashioned unnamed things, and I need a way to use them for named things. Of course, massive refactoring of those functions is ineligible solution.
At last, after this long introduction, let me state my questions:
Does modern Elm provides some substitute for old deprecated field addition/removal syntax?
If not, is there some built-in function like equip and extract above? For every custom extensible record type I would like to have a polymorphic analyzer (a function that extracts its base part) and a polymorphic constructor (a function that combines base part with additive and produces the record).
Negative answers for both (1) and (2) would force me to implement Named t in a more traditional way:
type Named t = Named String t
In this case, I can't catch the purpose of extensible records. Is there a positive use case, a scenario in which extensible records play critical role?
Type { t | name : String } means a record that has a name field. It does not extend the t type but, rather, extends the compiler’s knowledge about t itself.
So in fact the type of equip is String -> { t | name : String } -> { t | name : String }.
What is more, as you noticed, Elm no longer supports adding fields to records so even if the type system allowed what you want, you still could not do it. { thing | name = name } syntax only supports updating the records of type { t | name : String }.
Similarly, there is no support for deleting fields from record.
If you really need to have types from which you can add or remove fields you can use Dict. The other options are either writing the transformers manually, or creating and using a code generator (this was recommended solution for JSON decoding boilerplate for a while).
And regarding the extensible records, Elm does not really support the “extensible” part much any more – the only remaining part is the { t | name : u } -> u projection so perhaps it should be called just scoped records. Elm docs itself acknowledge the extensibility is not very useful at the moment.
You could just wrap the t type with name but it wouldn't make a big difference compared to approach with custom type:
type alias Named t = { val: t, name: String }
equip : String -> t -> Named t
equip name thing = { val = thing, name = name }
extract : Named t -> t
extract thing = thing.val
Is there a positive use case, a scenario in which extensible records play critical role?
Yes, they are useful when your application Model grows too large and you face the question of how to scale out your application. Extensible records let you slice up the model in arbitrary ways, without committing to particular slices long term. If you sliced it up by splitting it into several smaller nested records, you would be committed to that particular arrangement - which might tend to lead to nested TEA and the 'out message' pattern; usually a bad design choice.
Instead, use extensible records to describe slices of the model, and group functions that operate over particular slices into their own modules. If you later need to work accross different areas of the model, you can create a new extensible record for that.
Its described by Richard Feldman in his Scaling Elm Apps talk:
https://www.youtube.com/watch?v=DoA4Txr4GUs&ab_channel=ElmEurope
I agree that extensible records can seem a bit useless in Elm, but it is a very good thing they are there to solve the scaling issue in the best way.
I'm building an app that generates random sequences of musical notes and displays them to the user as musical notation. These sequences can be generated according to several parameters, including density and maximum consecutive notes of the same pitch.
Musical sequences are captured by a sequence object whose notes property is a simple string of notes such as "abcdaba".
My early attempts to generate random sequences involved a SequenceGenerator class that compiled random sequences using several private methods. This looks like a service to me. But I'm trying to honour the principle expressed in Domain-Driven Design (Evans 2003) to only use services where necessary and to prefer associating behaviour with domain objects.
So my question is:
Should the job of producing random sequences be taken care of by a public method on sequence itself (such as generateRandom()) or should it be kept separate?
I considered the possibility that my original design is more along the lines of a builder or factory pattern than a service, but the the code is very different for creating a random sequence than for creating one with a supplied string of notes.
One concern I have with the method route is that generateRandom() as a method on sequence changes the content of sequence but isn't actually generating a new sequence object. This just feels wrong, but I can't express why.
I'm still getting my head around some the core OO design principles, so any help is greatly appreciated.
Should the job of producing random sequences be taken care of by a public method on sequence itself (such as generateRandom()) or should it be kept separate?
I usually find that I get cleaner designs if I treat "random" the same way that I treat "time", or "I/O" -- as an input to the model, rather than as an aspect of the model itself.
If you don't consider time an input value, think about it until you do -- it is an important concept (John Carmack, 1998).
Within the constraints of DDD, that could either mean passing a "domain service" as an argument to your method, allowing your aggregate to invoke the service as needed, or it could mean having a method on the aggregate, so that the application can pass in random numbers when needed.
So any creation of a sequence would involve passing in some pattern or seed, but whether that is random or not is decided outside of the sequence itself?
Yes, exactly.
The creation of an object is not usually considered part of the logic for the object.
How you do that technically is a different matter. You could potentially use delegation. For example:
public interface NoteSequence {
void play();
}
public final class LettersNoteSequence implements NoteSequence {
public LettersNoteSequence(String letters) {
...
}
...
}
public final class RandomNoteSequence implements NoteSequence {
...
#Override
public void play() {
new LetterNoteSequence(generateRandomLetters()).play();
}
}
This way you don't have to have a "service" or a "factory", but this is only one alternative, may or may not fit your use-case.
I have been exploring the CQRS/DDD-principles and patterns for a while now and have started implementing a sample project where I have split my storage-model into a WriteModel and a ReadModel. The WriteModel will use a simple NoSQL-like database where aggregates are stored in a key-value style, with value being just a serialized version of the aggregate.
I am now looking at ProtoBuf-Net for serializing and deserializing my domain model aggregates in and out of storage. Other than this post I haven't found any guidance or tips for using ProtoBuf-Net in this area. The point is that the (ideal) requirements for serialization and deserialization of aggregates is that the domain model should have as little knowledge as possible about this infrastructural concern, which implies the following:
No attributes on the classes
No constructors, getters, setters or any other piece of code just for the sake of serialization.
Ability to use any (custom) type possible and have it serialized/deserialized.
Thus far I have implemented just the serialization of the first versions of my aggregates which works perfectly fine. I use the RuntimeTypeModel.Default-instance to configure the MetaModel at runtime and have UseConstructor = false everywhere, which enables me to completely separate the serialization mechanics from my domain-assembly. I have even implemented a custom post-deserialization mechanism that enables me to just-in-time initialize fields after ProtoBuf-Net has deserialized it into a valid instance. So suppose I have class AggregateA like so:
[Version(1)]
public sealed class AggregateA
{
private readonly int _x;
private readonly string _y;
...
}
Then in my serialization-library I have code something along the following lines:
var metaType = RuntimeTypeModel.Default.Add(typeof(AggregateA), false);
metaType.UseConstructor = false;
metaType.AddField(1, "_x");
metaType.AddField(2, "_y");
...
However, I realize that up to this point I have only implemented the basic scenario, and I am now starting to think about how to approach versioning of my model. I am particularly interested in larger refactoring-scenario's, where type A has been split into type A1 and A2, for example:
[Version(2)]
public sealed class AggregateA1
{
private readonly int _x;
...
}
[Version(2)]
public sealed class AggregateA2
{
private readonly string _y;
...
}
Suppose I have a serialized bunch of instances of AggregateA, but now my domain model knows only AggregateA1 and AggregateA2, how would you handle this scenario with ProtoBuf-Net?
A second question deals with point 3: is ProtoBuf-Net capable of handling arbitrary types if you're willing to put in some extra configuration-effort? I've read about exceptions raised when using the DateTimeOffset-type, which makes me think not all types can be serialized by the framework out-of-the-box, but can I serialize these types by registering them in the RuntimeTypeModel? Should I even want to go there? Or better to forget about serializing common .NET types other than the simple ones?
protobuf-net is intended to work with predictable known models. It is true that everything can be configured at runtime, but I have not put any thought as to how to handle your A1/A2 scenario, precisely because that is not a supported scenario (in my defense, I can't see that working nicely with most serializers). Thinking off the top of my head, if you have the configuration/mapping data somewhere, then you could simply deserialize twice; i.e. as long as we still tell it that AggregateA1._x maps to 1 and AggregateA2._y maps to 2, you can do:
object a1 = model.Deserialize(source, null, typeof(AggregateA1));
source.Position = 0; // rewind
object a2 = model.Deserialize(source, null, typeof(AggregateA2));
However, more complex tweaks would require additional thought.
Re "arbitrary types"... define "arbitrary" ;p In particular, there is support for "surrogate" types which can be useful for some transformations - but without a very specific "problem statement" it is hard to answer completely.
Summary:
protobuf-net has an intended usage, which includes both serialization-aware (attributed, etc) and non-aware scenarios (runtime configuration, etc) - but it also works for a range of more bespoke scenarios (letting you drop to the raw reader/writer API if you want to). It does not and cannot guarantee to be a direct fit for every serialization scenario imaginable, and how well it behaves will depend on how far from that scenario you are.
I have a lot to learn in the way of OO patterns and this is a problem I've come across over the years. I end up in situations where my classes' sole purpose is procedural, just basically wrapping a procedure up in a class. It doesn't seem like the right OO way to do things, and I wonder if someone is experienced with this problem enough to help me consider it in a different way. My specific example in the current application follows.
In my application I'm taking a set of points from engineering survey equipment and normalizing them to be used elsewhere in the program. By "normalize" I mean a set of transformations of the full data set until a destination orientation is reached.
Each transformation procedure will take the input of an array of points (i.e. of the form class point { float x; float y; float z; }) and return an array of the same length but with different values. For example, a transformation like point[] RotateXY(point[] inList, float angle). The other kind of procedure wold be of the analysis type, used to supplement the normalization process and decide what transformation to do next. This type of procedure takes in the same points as a parameter but returns a different kind of dataset.
My question is, what is a good pattern to use in this situation? The one I was about to code in was a Normalization class which inherits class types of RotationXY for instance. But RotationXY's sole purpose is to rotate the points, so it would basically be implementing a single function. This doesn't seem very nice, though, for the reasons I mentioned in the first paragraph.
Thanks in advance!
The most common/natural approach for finding candidate classes in your problem domain is to look for nouns and then scan for the verbs/actions associated with those nouns to find the behavior that each class should implement. While this is generally a good advise, it doesn't mean that your objects must only represent concrete elements. When processes (which are generally modeled as methods) start to grow and become complex, it is a good practice to model them as objects. So, if your transformation has a weight on its own, it is ok to model it as an object and do something like:
class RotateXY
{
public function apply(point p)
{
//Apply the transformation
}
}
t = new RotateXY();
newPoint = t->apply(oldPoint);
in case you have many transformations you can create a polymorphic hierarchy and even chain one transformation after another. If you want to dig a bit deeper you can also take a look at the Command design pattern, which closely relates to this.
Some final comments:
If it fits your case, it is a good idea to model the transformation at the point level and then apply it to a collection of points. In that way you can properly isolate the transformation concept and is also easier to write test cases. You can later even create a Composite of transformations if you need.
I generally don't like the Utils (or similar) classes with a bunch of static methods, since in most of the cases it means that your model is missing the abstraction that should carry that behavior.
HTH
Typically, when it comes to classes that contain only static methods, I name them Util, e.g. DbUtil for facading DB access, FileUtil for file I/O etc. So find some term that all your methods have in common and name it that Util. Maybe in your case GeometryUtil or something along those lines.
Since the particulars of the transformations you apply seem ad-hoc for the problem and possibly prone to change in the future you could code them in a configuration file.
The point's client would read from the file and know what to do. As for the rotation or any other transformation method, they could go well as part of the Point class.
I see nothing particularly wrong with classes/interfaces having just essentially one member.
In your case the member is an "Operation with some arguments of one type that returns same type" - common for some math/functional problems. You may find convenient to have interface/base class and helper methods that combine multiple transformation classes together into more complex transformation.
Alternative approach: if you language support it is just go functional style altogether (similar to LINQ in C#).
On functional style suggestion: I's start with following basic functions (probably just find them in standard libraries for the language)
collection = map(collection, perItemFunction) to transform all items in a collection (Select in C#)
item = reduce (collection, agregateFunction) to reduce all items into single entity (Aggregate in C#)
combine 2 functions on item funcOnItem = combine(funcFirst, funcSecond). Can be expressed as lambda in C# Func<T,T> combined = x => second(first(x)).
"bind"/curry - fix one of arguments of a function functionOfOneArg = curry(funcOfArgs, fixedFirstArg). Can be expressed in C# as lambda Func<T,T> curried = x => funcOfTwoArg(fixedFirstArg, x).
This list will let you do something like "turn all points in collection on a over X axis by 10 and shift Y by 15": map(points, combine(curry(rotateX, 10), curry(shiftY(15))).
The syntax will depend on language. I.e. in JavaScript you just pass functions (and map/reduce are part of language already), C# - lambda and Func classes (like on argument function - Func<T,R>) are an option. In some languages you have to explicitly use class/interface to represent a "function" object.
Alternative approach: If you actually dealing with points and transformation another traditional approach is to use Matrix to represent all linear operations (if your language supports custom operators you get very natural looking code).
What is it called when an object has an object of the same type inside of itself?
Example:
public class Foo{
public Foo myFoo;
}
I don't think there's any specific name for this. Although this concept is used in many different common programming constructs. For instance, when representing a graph, tree, or linked list, the nodes usually have references to other nodes that they are linked/connected to.
It means that Foo is a 'recursive data structure'. Examples of this are trees, graphs, linked lists, etc. There aren't many significant programs written that don't use at least some recursive structures, e.g. in any SQL server implementation it's pretty common that the query plan that gets executed will be defined in a similar way. As a tiny example, the WHERE clause might get translated to a FilterNode that acts on data received from some other Node (like a table scan):
public interface Node { }
public class FilterNode implements Node {
public Node underlyingNode;
public Condition filterCondition;
}
In many cases the overall structure forms a directed acyclic graph, which means it's easy to safely traverse it recursively. But if it's got cycles then you need to be careful that you don't get into infinite recursion (which is what another answer above is humorously warning about).
Recursive containment.... :)
To add to what Kibbee said, this is a type of a composite pattern