Pitfalls of c# generics and their solution using concepts

Belyakova Julia; Mikhalkovich Stanislav

Pitfalls of C# Generics and Their Solution Using Concepts

Julia Belyakova <[email protected]>, StanislavMikhalkovich <[email protected]> Institute for Mathematics, Mechanics and Computer Science, Southern Federal University, 344006, B. Sadovaya str., 105/42, Rostov-on-Don, Russia

Abstract. In comparison with Haskell type classes and C++ concepts, such object-oriented languages as C# and Java provide much limited mechanisms of generic programming based on F-bounded polymorphism. Main pitfalls of C# generics are considered in this paper. Extending C# language with concepts which can be simultaneously used with interfaces is proposed to solve the problems of generics; a design and translation of concepts are outlined.

Keywords: generic programming; (C++) concepts; generics; C# language; concept pattern; recursive constraints; generic interfaces.

1. Introduction

Generic programming is supported in different programming languages by various techniques such as C++ templates, C# and Java generics, Haskell type classes, etc. Some of these techniques were found more expressive and suitable for generic programming, other ones more verbose and worse maintainable [1]. Thus, for example, the mechanism of expressive and flexible C++ unconstrained templates suffers from unclear error messages and a late stage of error detection [2], [3]. A new language construct called concepts1 was proposed for C++ language as a possible substitution of unconstrained templates. A design of C++ concepts2 conforms to main principles of effective generic tools design [1].

In comparison with concepts and Haskell type classes [1], [7], such mainstream object-oriented languages as C# and Java provide much limited mechanisms of generic programming based on F-bounded polymorphism. Pitfalls of C# generics are analysed in this paper in detail (Sec. 2): we discuss some known drawbacks and state the problems of subtle semantics of recursive constraints (Sec. 2.2) and constraints-compatibility (Sec. 2.3). To manage the pitfalls considered, extending of C#

Term "concept" was initially introduced in a documentation of the Standard Template Library (STL) [4] to describe requirements on template parameters in informal way.

2

There were several designs of C++ concepts [3], [5], [6]; all of them share some general ideas.

with concepts is proposed: a design of concepts is briefly presented in Sec. 4. We also discuss a translation of such extension to standard C#.

C# language is used in this paper primarily for the sake of syntax demonstration. As for the pitfalls of C# generics, they hold for Java as well with slight differences. However, while the concepts design proposed in the paper could be easily adapted for Java (and also for any .NET-language with interface-based generics), the technique of language extension translation (which we consider in Sec. 4) cannot be applied for Java directly. Unlike Java Virtual Machine, .NET Framework preserves type information in its byte code, this property being crucial for the translation method.

2. Pitfalls of C# Generics

C# and Java interfaces originally developed to be an entity of object-oriented programming were later applied to generic programming as constraints on generic type parameters. There are several shortcomings of this approach.

2.1 Lack of Retroactive Interface Implementation

C# and Java interfaces originally developed to be an entity of object-oriented programming were later applied to generic programming as constraints on generic type parameters. There are several shortcomings of this approach. Interfaces cannot be implemented retroactively, i. e. it is impossible to add the relationship "type T implements interface I" if type T is already defined. Consider a generic algorithmfor sorting arrays Sort<T> with the following signature:

Sort<T>(T[]) where T : IComparable<T>;

If some type Foo provides an operation of comparison but does not implement the interface IComparable<Foo>, Sort<Foo> is not a valid instance of SortO. What one can do in this case? If type cannot be changed (it may be defined in external .dll, for instance), the only way to cope with sorting is to define an adapter class FooAdapter which implements Sort<FooAdapter> interface, pack all Foo objects into FooAdapter ones, sort them and unpack back to an array of Foo objects. Apparently, there must be a better approach. Fortunately, in the .NET Framework standard library the Array. Sort<T> method [8] is provided with two "branches" of overloads:

1. For any type T which implements IComparable<T> interface (( s -1) example, Fig. 1).

2. For any type T with an external comparer of type IComparer<T> provided (( s-2 ) example, Fig. 1).

Hence, if some type is already defined, values of this type can be compared, but this type does not implement IComparableO interface (as in the Foo example above), SortO with IComparerO (branch 2) is to be used. Thus one can 30

simulate retroactive modeling property (in Scala the similar approach is referred to as a programming with the "concept pattern" [9]). Consequently, if retroactive modeling is required, a programmer has to write a generic code twice — in "interface-oriented" and in "concept pattern" styles. The amount of necessary overloads grows exponentially: if one needs two retroactively modeled constraints on generic type, corresponding generic code would consist of four "twins", if three — eight "twins" and so on.

(ICmp-1) interface IComparable<T> {int CompareTo(T other);}

(ICmp-2) interface Icomparer<T> {int Compare(T x, T y);}

(s-1) Sort<T>(T ]) where T : IComparable<T>;

(s-2) Sort<T>(T ], IComparer<T>);

Fig. 1. IComparable<T>/IComparer<T> interfaces and its applications

(1) interface IComparableTo<S> { int CompareTo(S other); }

(2) interface IComparable<T> where T : IComparable<T> { int CompareTo(T other); }

Fig. 2. IComparable<T> vs IComparableTo<S> example

interface IDataVertexCVertex, DataType> where Vertex : IDataVertexCVertex, DataType>

IEnumerator<Vertex> OutVertices { get; } // (*)

} interface IDataGraphCVertex, DataType> where Vertex : IDataVertexCVertex, DataType> { • • • 1 // (#)

Fig. 3. IDataGraphC, > and IDataVertexC, > interfaces

2.2 Drawbacks of Recursive Constraints

Example 1. The following reason about the Sort<T> method for ICompa-rable<T> may be not obvious. The notation of Sort<T> in ( s-1) example (Fig. 1) looks a little bit redundant; such a recursive constraint on type T might look even frightening, but it is well formed. Furthermore, the word "comparable" in this context is very likely associated with the ability to compare values of type T with each other. But the interface IComparable<T> ((ICmp-1) , Fig. 1) does not correspond this semantics: it designates the ability of some type (which implements this interface) to be comparable with type T. The same problem with Comparable<X> interface in Java is explored in [10]. The particular role of recursive constraints in generic programming is explored in [11]. It would be better to split the single IComparableO interface into two different interfaces (Fig. 2):

1. IComparableTo<S> which requires some type (which implements this interface) to be comparable with S.

2. IComparable<T> which requires values of type T to be comparable with each other.

Note that the definition of the latter interface needs the constraint (q.v. Fig. 2):

where T: IComparable<T> Example 2. As an another example consider a generic definition of graph with peculiar structure: graph stores some data in vertices; every vertex contains information about its predecessors and successors thereby defining arcs. A graph itself consists of set of vertices instead of set of edges. Such kind of graph is suitable for a task of data flow analysis in the area of optimizing compilers [12] because "movement along arcs up and down" is intensively used action in an analysis of a control flow graph.

Fig. 3 illustrates parts of the corresponding definitions: IData-Graph<Vertex, DataType> describes interface of a data graph; IDataVertex<Vertex, DataType> describes interface of a vertex in such graph. While the graph interface really depends on type parameters Vertex and D a t a T yp e, we have to include Vertex as a type parameter into the vertex interface IDataVertex<, > as well. Similarly to ICompa-rableO example the constraints (*) and (#) in Fig. 3 are not superfluous. Suppose we have the following types:

class VI : IDataVertexCVl, int> { ... } class V2 : IDataVertexCVl, int> { ... }

Thanks to the constraints (*) and (#) the instantiation of graph IData-Graph<V2 , int> is not allowed, since type V2 does not implement interface IDataVertex<V2 , int>. Without these constraints we might accept some inconsistent graph with vertices of type V2 which refer to vertices of type

VI.

Vertex and graph interface definitions are unclear and nonobvious. If programmers might be used to use interface IC omp a r ab 1 e < >, it is more difficult to manage such things as IDataGraphK, > example. In some cases one may prefer to abandon writing generic code because of this awkwardness.

2.3 Ambiguous Semantics of Generic Types

When using flexible Sort<T> method with an external parameter (Fig. 1), a programmer has clear understanding of how elements are sorted, since such a comparer is a parameter of an algorithm. But when one uses generic types, this information is implicit. For instance, SortedSet<T> class takes Icomparer<T> object as a constructor parameter, HashSet<T> class taking IEquality-

Comparer<T>. Therefore, given two sets of the same generic type one cannot check at compile time whether these sets are constraints-compatible (in case of HashSet<T> "constraints-compatibility" means that the given sets use the same equality comparer). And it seems that a programmer usually does not suppose that objects of the same type can have different comparers (or addition operators, coercions, etc). But they can, and it leads to subtle errors.

Suppose we have a simple function Ge tUnion<T> (q.v. Fig. 4) which returns a union of the two given sets. If some arguments a and b provide different equality comparers (e.g., case-sensitive and case-insensitive comparers for type string), the result of GetUnion(a, b) would differ from the result of GetUn-i on (b, a) . Note that Haskell type classes do not suffer from such an ambiguity because every type provides only one instance of a type class.

static HashSet<T> GetUnion<T>(HashSet<T> si, HashSet<T> s2) {

var us = new HashSet<T>(si, si.Comparer); us.UnionWith(s2); return us;

}

Fig. 4. Union of HashSet<T> objects

interface IObserverCO , S> where 0 IObserverCO, S>

where s ISubj ectCO, S>

{ void update(S subj ) ; }

interface ISubjectCO, s> where 0 IObserverCO, S>

where s ISubj ectCO, S>

i List<0> getObservers( );

void register(0 obs ) ;

void notify(); }

Fig. 5. Observer pattern in C#

2.4 The Problem of Multi-Type Constraints

The well-known problem of multi-type constraints holds for C# interfaces. Requirements concerning on several types cannot be naturally expressed within interfaces. The paper [10] deals with the example of Observer pattern in Java. The Observer pattern connects two types: Observer and Sub j ect. Both types has methods which take the another type of this pair as an argument: the Observer provides update (Sub j ect), the Subject— register (Observer) . Fig. 5 shows the interface definitions 10bserver<0, S> for Observer and ISubj ect<0, S> for Subject in standard C#. We need two different interfaces and have to duplicate the constraints on 0 and S in both definitions to estab-

lish consistent connection between type parameters 0 and S . And again we face with recursive constraints on types 0 (which represents the Observer) and S (which represents the Subject). This example looks even worse than the case of vertex and graph interfaces presented in Fig. 3. But it is the only way to define a type family [13] of Observer pattern correctly.

2.5 Constraints Duplication and Verbose Type Parameters

All constraints required by a definition of generic type are to be repeatedly specified in every generic component which uses this type. Consider the generic algorithm GetSubgraph<, , > depending on type parameter G which implements IDataGraphK, > interface (q.v. Fig. 3).

G GetSubgraph<G, Vertex, DataType>( G g, Predicate<DataType> p)

where G : IDataGraphCVertex, DataType>, new()

where Vertex : IDataVertexCVertex, DataType> { ... }

GetSubgraph<G, Vertex, DataType> method is not correct without explicit specification of constraint on type parameter Vertex . This constraint is induced by the definition of IDataGraph<Vertex, DataType> interface and should be repeated every time one uses Idata-Graph<, >.

Another property of GetSubgraph< . . . > definition is a plenty of generic parameters. Clearly, vertex and data types are fully determined by the type of specific graph. At the level of GetSubgraph< . . . > signature vertex type even does not matter at all. Such types are often referred to as associated types. Some programming languages allow to declare associated types explicitly (SML, C++ via traits, Scala via abstract types and some other), but in C# and Java they can only be represented by extra type parameters. It makes generic definitions verbose and breaks encapsulation of constraints on associated types. Issues of repeated constraints specification and lack of associated types are considered in [14], [1] in more detail.

3. Related Work

We consider two studies concerning modification of generic interfaces in this section:

1. [14] proposes the extension of C# generics with associated types and constraint propagation.

2. [10] generalizes Java 1.5 interfaces enabling retroactive interface implementation, multi-headed interfaces (expressing multi-type constraints) and some other features.

Both studies revise interfaces to improve interface-based mechanism of generic programming and to approach to C++ concepts and Haskell type classes, which are

considered being rather similar [7]. Some features of Scala language in respect to problems considered in Sec. 2 will also be mentioned.

interface ObserverPattern[0, S] {

receiver 0 { void update S subj); }

receiver S {

List<0> getObservers ) ;

void register(0 obs) { getObservers().add(obs); }

void notify!) { ••• }

} class MultiheadedTest {

<S,0> void genericUpdate s subject, 0 observer)

where [S,0] iirplements ObserverPattern {

observer.update(subj ect } } ) ;

Fig. 6. Observer pattern in JavaGI

3.1 C# with Associated Types and Constraint Propagation

Member types in interfaces and classes are introduced in [14] to provide direct support of associated types. A mechanism of constraint propagation is also proposed to lower verbosity of generic components and get rid of constraints duplication as was mentioned in Sec. 2-5. The example of Incidence Graph concept from the Boost Graph Library (BGL) [15] is considered. It is shown that features proposed can significantly improve a support of generic programming not only in C# language but in any object-oriented language with F-bounded polymorphism. But the problems of multi-type constraints and recursive constraints cannot be solved with this extension. Thus, the code of Observer pattern (Fig. 5) cannot be improved at all because of recursive constraints; the same holds for I Comparable^ > interface. The issue of retroactive implementation is also not touched upon in [14]: extended interfaces are still interfaces which cannot be implemented retroactively.

3.2 JavaGI: Java with Generalized Interfaces

In contrast to [14], the study [10] is mainly concentrated on the problems of retroactive implementation, multi-type constraints (solved with multi-headed interfaces) and recursive interface definitions3. For instance, Observer pattern is expressed in JavaGI with generalized interfaces as shown in Fig. 6 [10]. Methods of a whole interface are grouped by a receiver type with keyword receiver. A syntax of an interface looks a little bit verbose but it is essentially better than two interfaces with duplicated constraints shown in Fig. 5. Moreover, JavaGI interfaces allow default implementation of methods (as register and notify). Retroactive imple-

This problem is usually connected with so-called binary methods problem.

mentation of interfaces is also allowed, but it is possible to define only one implementation of an interface for the given set of types in a namespace. It turns out that interfaces become some restricted version of C++ concepts [5], [16] (in particular, they do not support associated types) and, moreover, they lose a semantics of object- oriented interfaces4. JavaGI interfaces only act as constraints on generic type parameters, but they cannot act as types, so one cannot use JavaGI interfaces as in Java.

(s-s) def Sort[T : Ordering](elems: Array[T]) { ... }

(s-u) def Sort[T](elems: Array [T] ) (iirplicit ord: Ordering [T]) {...}

trait ObserverPattern[S, 0] {

def update(obs: 0, subj: S);

def getObservers(sub" : S): Seg[0];

def setObservers(sub" : S, observers : Seg[0] );

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def register(subj: S, obs: 0)

{ setObservers(subj, getObservers(subj) :+ obs); }

def notify(subj: S) ) i ... }

; object MultiheadedTest {

def genericUpdate[S, 0](subject: S, observer: 0)

(iirplicit obsPat: Observer Pattern [ S, 0] ) {

obs Pat.update(observer, subj ect); } }

Fig. 7. Sort [T] and observerPattern [ s, o] examples in Scala

3.3 "Concept Pattern" and Context Bounds in Scala

The idea of programming with "concept pattern" has been reflected in Scala language [9]. Due to the combination of generic traits (something like interfaces with abstract types and implementation), implicits (objects used by default as function arguments or class fields) and context bounds (like T : Ordering in Fig. 7) Scala provides much more powerful mechanism of generic programming than C# or Java. Fig. 7 illustrates the examples of sorting and observer pattern. Context bounds provide simple syntax for single-parameter constraints: the sugared (s-s) version of Sort[T] algorithm is translated into (s-u) one by desugaring. Retroactive modeling is supported since one can define new Ordering [ ] object and use it for sorting. And one does not need to provide two versions of the sort algorithm as for C# language (q.v. Fig. 1): Sort [ ] with one argument would use default ordering due to implicit keyword. Ob-serverPattern [S, 0] looks rather similar to corresponding JavaGI in-

The way to preserve compatibility with Java code is considered in [10], but "real interfaces" no longer exist in JavaGI.

terface (Fig. 6). There is no syntactic sugar for multi-parameters traits, so the nota-tionof genericUpdate [ S, 0] cannot be shortened. In respect to the constraints-compatibility problem discussed in Sec. 2-3 Scala's "concept pattern" reveals the same drawback as C#. Generic types take "concept objects" as constructor parameters. In such a way TreeSet [A] [17] implicitly takes Ordering [A] object, therefore, for instance, the result of intersection operation would depend on an order of arguments if they use different ordering.

4. Design of Concepts for C# Language

4.1 Interfaces and Concepts

It seems that a new language construct for generic programming should be introduced into such object-oriented languages as C# or Java. If we extend interfaces preserving their object- oriented essence [14], a generic programming mechanism becomes better but still not good enough, since such problems as retroactive modeling or constraints-compatibility remain. If we make interfaces considerably better for generic programming purposes [10], they lose their object-oriented essence and can no longer be used as types.

We advocate the assertion that both features have to be provided in an object-oriented language:

1. Object-oriented interfaces which are used as types.

2. Some new construct which is used to constrain generic type parameters. C++ like concepts are proposed to serve this goal.

Construct of extended language Construct of base language

Concept Abstract class

Concept parameter Type parameter

Associated type Type parameter

Concept refinement Subtyping

Associated value Property (only read)

Nested concept requirement Type parameter

Concept requirement in generic code Type parameter

Model Class

Fig. 8. Translation of C# extension with concepts

4.2 C#with Concepts: Design and Translation

In this section we present a sketch of C# concepts design. Concept mechanism introduces the following constructs into the programming language: 1. Concept. Concepts describe a named set of requirements (or constraints) on one or more types called concept parameters.

2. Model. Models determine the manner in which specific types satisfy concept. Models are external for types; they can be defined later than types. It means that a type can retroactively model a concept if it semantically conforms to this concept. Types may have several models for the same concept. In some cases a default model can be implicitly generated by a compiler.

3. Constraints are used in generic code to describe requirements on generic type parameters.

Concepts support the following kinds of constraints:

• associated types and associated values;

• function signatures (may have default implementation);

• nested concept requirements (for concept parameters and associated types);

• same-type constraints;

• subtype and supertype constraints;

• aliases for types and nested concept requirements.

The main distinction of C# concepts proposed in comparison with other concepts designs (C++ , G [16]) is the support of subtype constraints and anonymous models (like anonymous classes). Concept-based mechanism of constraining generic type parameters surpasses the abilities of interface-based one. At the same time interfaces can be used as usual without any restrictions.

Concepts can be implemented in existing compilers via the translation to standard C#. Fig. 8 presents correspondence between main constructs of extended and standard C# languages. To preserve maximum information about the source code semantics, some additional metainformation has to be included into translated code. In particular, one needs to distinguish generic type parameters in the resultant code as far as they may represent concept parameters, associated types or nested concept requirements. To resolve such ambiguities we propose using attributes. The method of translation suggested is strongly determined by the properties of .NET Framework. Due to preserving type information and attributes in a .NET byte code, translated code can be unambiguously recognized as a result of code- with-concepts translation. Moreover, it can be restored into its source form, what means that modularity could be provided: having the binary module with definitions in extended language one can add it to the project (in extended language either) and use in an ordinary way.

Fig. 9 illustrates several concept definitions (in the left column) and their translation to standard C# (in the right column). Basic syntax of concepts is shown: concept declarations (start with keyword concept), signature constraints, signature constraints with default implementation (NotEqual in CEquatible [T] ) , refinement (concept CComparable [ T ] refines CEquatible [ T ], i.e. it includes all requirements of refined concept and adds some new ones), associated types (Data in CTransf erFunction [TF]), multi-type concept COb-

server Pat tern [0, S], nested concept requirements (CSemi lattice [Data] in Ctransf erFun-ction [TF]).

concept CEquatible[T] [Concept] abstract class

{ // function signature (FS) CEquatible<[IsConceptParam]T>

bool Equal(T x, T y); {

// FS with default implementation public abstract bool Equal(T x, T y);

bool NotEqual(T x, T y) public virtual bool NotEqual(T x, T y)

{ return !Equal(x, y); } i { return !this.Equal(x, y); } i

i // refining concept i [Concept] abstract class CComparable<

concept CComparable[T] [IsConceptParam]T> : CEquatible<T>

refines CEquatible[T] {

{ public abstract int Compare(T x, T y);

int Compare(T x, T y); public override bool Equal(T x, T y)

// overrides Equal from refined { . . . }

// concept CEquatible[T] }

override bool Equal(T x, T y) [Concept] abstract class

{ . . . } CTransferFunction<

} [IsConceptParam]TF, [IsAssocType]Data,

concept CTransferFunction[TF] [IsNestedConceptReq]CSemilattice Data>

{ where CSemilattice Data

type Data; // associated type : CSemilattice<Data>, new()

// nested concept requirement {

require CSemilattice[Data]; public abstract Data Apply(

Data Apply(TF trFun, Data d); TF trFun, Data d);

TF Compose(TF trFunl, TF trFun2); public abstract TF Compose(

} TF trFunl, TF trFun2);

concept CObserverPattern[0, S] } [Concept] abstract class CObserverPattern<

{ [IsConceptParam]0, [IsConceptParam]S>

void UpdateSubject( {

0 obs, S subj); public abstract void UpdateSubject(

ICollection<0> GetObservers( 0 obs, S subj);

S subj); public abstract ICollection<0>

void RegisterObserver( GetObservers(S subj);

S subj, 0 obs) public virtual void RegisterObserver(

{ GetObservers(subj).Add(obs); } S subj, 0 obs)

void NotifyObservers(S subj) { GetObservers(subj).Add(obs); }

{ . . . } public virtual void NotifyObservers(

} S subj) { ... }

Fig. 9. Concept examples and their translation to basic C#

Concepts are translated to generic classes. Function signatures are translated to abstract or virtual (if implementation is provided) class methods. Concept parameters and associated types are represented by type parameters (marked with attributes) of a generic abstract class as well as nested concept requirements. For instance, CSemilattice_Data type parameter of CTransf erFunctionO denotes Csemilattice [Data] concept requirement because this parameter is attributed with [ IsNestedConceptReq], corresponding subtype constraint being in a where-clause.

static void Sort<T>(T[] values) where CComparable[T]

[GenericFun] static void Sort< [IsGenericParam]T,

[IsRequireConceptParam]CComparable_T> (T[] values) where CComparable_T

class BinarySearchTree<T> // concept requirement with alias where CComparable[T] using cCmp { private BinTreeNode<T> root; private bool AddAux( T x, ref BinTreeNode<T> root) { // refer, to concept by alias if (cCmp.Equal(x, root.data)) return false; } : CComparable<T>, new() { ... } [GenericClass] [ConceptAlias("CComparable T", "cCmp")] class BinarySearchTree<[IsGenericParam]T, [IsRequireConceptParam]CComparable T> where CComparable T : CComparable<T>, new () { private BinTreeNode<T> root; private bool AddAux( T x, ref BinTreeNode<T> root) { ... CComparable T cCmp = ConceptSingleton CCComparable T>.Instance; if (cCmp.Equal(x, root.data)) return false; }

Fig. 10. Generic code and its translation to basic C#

// class for rational number // with properties // Num for numenator and Denom // for denominator class Rational { ... } model CComparable[Rational] { bool Equal( Rational x, Rational y) { return (x.Num == y.Num) && (x.Denom == y.Denom); } int Compare(Rational x, Rational y) { ... } } BST<Rational> rations // * = new BST<Rational>(); class Rational { ... } [ExplicitModel] class Ccomparable Rational Def : CComparable <Rational> { public override bool Equal( Rational x, Rational y) { return (x.Num == y.Num) && (x.Denom == y.Denom); } public override int Compare( Rational x, Rational y){ ... } } BSKRational, CComparable Rational Def> rations // * = new BSKRational, CComparable Rational Def>();

* "BST" is used instead of "BinarySearchTree" for short.

Fig. 11. Model ccomparable [Rational ] and its translation to basic C#

Some examples of generic code with concept constraints are presented in the left column of Fig. 10. Concept requirements can be used with alias (as CCompa-rable [ T ] in the class of binary search tree). Note that a singular definition of generic component is sufficient. Translated generic code (in the right column) demonstrates significant property of translation: concept requirements are translated into extra type parameters instead of extra method and constructor parameters (as it is in Scala and G [16]). Therefore, constraints-compatibility can be checked at compile time, methods and objects being saved from unnecessary arguments and fields. Fig. 11 presents the model of concept CComparable [ ] for class Rational of rational number. It is translated to derived class CCompa-rable_Rational_Def of Ccomparable<Rational> and then

used as the second type argument of generic instance BST<, >. Fig. 12 demonstrates using of anonymous model to find a number with a numerator equal to 5.

static bool Contains<T>(T x, IEnumerable<T> values)

where CEquatible[T] { .. • }

static void TestContains

1 Rational[] nums = ...;

var hasNumer5 = Contains [model CEquatible[Rational] {

bool Equal(Rational x, Rational y) { return x.Num == y.Num; }

}](new Rational(5), nums } );

Fig. 12. Anonymous model example

5. Conclusion and Future Work

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Many problems of C # and Java generics seem to be well understood now. Investigating generics and several approaches to revising 00 interfaces, we faced with some pitfalls of these solutions which were not considered yet.

1. Recursive constraints used to solve the binary method problem appear to be rather complex and often do not correspond a semantics assumed by a programmer.

2. The "concept pattern" breaks constraints-compatibility.

3. Using interfaces both as types and constraints on generic type parameters leads to awkward programs with low understandability.

To solve problems considered we proposed to extend C# language with the new language construct — concepts. Keeping interfaces untouched, concept mechanism provides much better support of the features crucial for generic programming [1]. The support of these features in C# with concepts extension and its comparison with some other generic mechanisms are presented in Fig. 13. The design of C# concepts is rather similar to C++ concepts designs, but it supports subtype and supertype constraints.

We also suggested a novel way of concepts translation: in contrast to G concepts [16] and Scala "concept pattern" [9], C# concept requirements are translated to type parameters instead of object parameters; this lowers the run-time expenses on passing extra objects to methods and classes.

Much further investigation is to be fulfilled. First of all, type safety of C# concepts has to be formally proved. The design of concepts proposed seems to be rather expressive, but it needs an approbation. So the next step is developing of the tool for compiling a code in C# with concepts. Currently we are working on formalization of translation from extended language into standard C#.

Feature G C++ c#m JGI Scala ^ ^concept

multi-type constraints + + + +2 +

associated types + + + - + +

same-type constraints + + + - + +

subtype constraints - - + + + +

retroactive modeling + + + +3 +

multiple models + - - + +

anonymous models - - - - +3 +

concept-based overloading + + - - ±4 -

constraints-compatibility + + + - +

"C#ext" means C# with associated types [1 ] „^concept,, means r ■ with concepts.

1 partially supported via "concept pattern" ~ supported via "concept pattern"

3 supported via "concept pattern" and implicits 4 partially supported by prioritized overlapping implicits

Fig. 13. Comparison of "concepts" designs

6. Acknowledgement

The authors would like to thank the participants of the study group on the foundations of programming languages Vitaly Bragilevsky and Artem Pelenitsyn for discussions on topics of type theory and concepts.

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Проблемы обобщений С# и способы их решения с помощью концептов

Ю.В. Белякова <[email protected]>, С.С. Михалкович <[email protected]> Институт математики, механики и компьютерных наук им. И.И. Воровича, Южный федеральный университет, 344006, Россия, г. Ростов-на-Дону, ул. Б. Садовая, д. 105/42

Аннотация. По сравнению с классами типов Haskell и концептами С++ такие объект-но-ориентированные языки как С# и Java предоставляют значительно менее выразительные механизмы обобщённого программирования на основе F-ограниченного полиморфизма. В этой статье рассматриваются основные подводные камни обобщений С#. Для решения проблем обобщений предлагается расширение языка С# концептами, которые можно использовать одновременно с интерфейсами; очерчены дизайн и основные принципы трансляции концептов.

Ключевые слова: generic programming; (С++) concepts; generics; C# language; concept pattern; recursive constraints; generic interfaces.

Список литературы

[1]. R. Garcia, J. Jarvi, A. Lumsdaine, J. Siek, and J. Willcock, "An Extended Comparative Study of Language Support for Generic Programming", J. Funct. Program., vol. 17, no. 2, pp. 145-205, Mar. 2007.

[2]. B. Stroustrup and G. Dos Reis, "Concepts — Design Choices for Template Argument Checking", С++ Standards Committee Papers, Technical Report N1522=03-0105, ISO/IEC JTC1/SC22/WG21, October 2003.

[3]. G. Dos Reis and B. Stroustrup, "Specifying С++ Concepts", in Conference Record of the 33rd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, ser. POPL '06. New York, NY, USA: ACM, 2006, pp. 295-308.

[4]. M. H. Austern, Generic Programming and the STL: Using and Extending the С++ Standard Template Library. Boston, MA, USA: Addison- Wesley Longman Publishing Co., Inc., 1998.

[5]. D. Gregor, J. Jarvi, J. Siek, B. Stroustrup, G. Dos Reis, and A. Lumsdaine, "Concepts: Linguistic Support for Generic Programming in С++", in Proceedings of the 21st Annual ACM SIGPLAN Conference on Object-oriented Programming Systems, Languages, and Applications, ser. OOPSLA '06. New York, NY, USA: ACM, 2006, pp. 291-310.

[6]. B. Stroustrup and A. Sutton, "A Concept Design for the STL", С++ Standards Committee Papers, Technical Report N3351=12-0041, ISOAEC JTC1/SC22/WG21, January 2012.

[7]. J.-P. Bernardy, P. Jansson, M. Zalewski, S. Schupp, and A. Priesnitz, "A Comparison of C++ Concepts and Haskell Type Classes", in Proceedings of the ACM SIGPLAN Workshop on Generic Programming, ser. WGP '08. New York, NY, USA: ACM, 2008, pp. 37^18.