Jeremy siek phd thesis language generic programming

ML signatures can contain type members that 2. Concepts define requirements on type parameters, models specify how concrete types meet those requirements. The third major lan- 2. Each model is a declaration that states that the spec- the arguments to a template meet the requirements of that template ified types model a particular concept, providing bindings for the and that the template itself does not rely on any template-dependent associated types and operations required by that concept.

Mod- constructs not explicitly stated as requirements. Requirements in els themselves are syntactically similar to concepts. Model requirements are written using the same form as models, e. Figure 2. A simplified implementation of the STL find algorithm Section 4. In fact, type Same-type requirements Same-type requirements indicate that checking of templates is divided into two phases. The first phase two types are equivalent within the template.

As an example of the use of same- called non-dependent. The second phase of type checking occurs at type constraints, consider the STL merge algorithm, which has template instantiation time, when the template parameters are sub- two template type parameters that model the InputIterator concept. These requirements are OutIter merge OutIter result ; introduced into the scope of the template. For example, the two concept requirements in the where clause of Figure 2 introduce the associated type name value type into the scope of find along with 2.

The constraints of the third overload thus bool operator! The advance function overloaded on several concepts.

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However, support for specialization implies that during the The basic model of resolving a call to an overloaded function second phase of type checking, at instantiation time, the compiler is as follows: 1 select the set of candidate functions, that is, all will select more specialized functions and data types.

The following functions for which the argument types match the parameter types section describes the effect of specialization on the type system. Type checking specialized generic components where clauses for determining the best matching function. Specializations of a class template do not necessarily a single non-specialized definition of a generic algorithm may in- define member functions as specializations of those of the primary voke other generic algorithms that are specialized. For example, the template, and may even omit member functions. Concept-based overloading was later cialized to obtain higher performance on data structures supporting proposed as a language feature by Stroustrup [44].

For ex- class template specializations and ambiguous specializations. This specialized, but the definitions of these specializations can be arbi- adaptor has minimal performance overhead, as its functions contain trary. Similarly, the instantiation model can enable function foo that uses vector. This optimization tional programming languages. First, since ever, the binary operation passed to transform is supplied both as there is no longer an array of bool values, a data member func- a template argument and as a value, and thus its code can be in- tion that returns a pointer to bool cannot be implemented.

Second, lined into the body of an instance of transform.

Jeremy Siek. “Toward a Mechanized Encyclopedia of Gradual Typing” – IMFD

Note that inlining and more subtly, the type returned from the subscripting operator [] calls to generic functions does not strictly require an instantiation is no longer an actual reference to a bool value in memory; instead, model, and in fact has been done in Haskell, which usually imple- it is proxy class that one can use to read and write values of type ments generic functions using dictionary passing [20]. Finally, the combination of instantiation model, lack of template The generic function foo in Figure 4 proves challenging for parameter constraints, and specialization allow a form of metapro- type checking.

When the template is initially type checked, the gramming with templates. For example, version 2 of the Matrix primary most general definition of vector will be used for type Template Library MTL [38] includes a set of metaprograms to checking, and the type check succeeds.

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These metaprograms are writ- and both statements in foo fail to type check at instantiation time. Due to the instantiation model, each use of the way in which specializations can be defined i. Tag dispatching is based on tag types that correspond to unusable for template metaprogramming. Specialized generic algorithms are then implemented checking. Even though all specializations are known to be correct as functions that detect the tag and then dispatch to a specialization, to use, an error occurs if no single specialization can be determined which is defined as a separate function.

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A more refined dispatching to be the best. Consider the overloads in Figure 5. We assume three mechanism is presented in [25]. Ambiguous multimethod definitions. Three sort overloads. We assume here that the concepts possible solutions. The definitions to establish these assumptions 4.

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Design space of concept-based overloading are not shown. Note that a sequence type modeling SortedSequence The notion of multimethods arose from the limitations of single implies that its value type models LessThanComparable. With multimethods, dispatching is early, SortedSequence additionally guarantees that the sequence is based on the types of all of the arguments of a method. Multimeth- sorted, and RandomAccessSequence enables constant time access us- ods were pioneered in CLOS and its predecessors [2, 3], followed ing an index but does not guarantee sortedness.

The Sequence con- by a host of research and implementations in other languages, such cept captures the minimal requirements for sorting, assuming the as Cecil and Java extensions [6, 8, 29, 30]. The expressive power element types can be compared, enabling the implementation in the gained over single-dispatch came with a price, however, compro- first overload. For type. The call m b, b cannot be sort pq ; resolved to either of the last two definitions of method m. Overload hierarchies like this one detects ambiguities at instantiation time of generic components.

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See [29] resolution performed at instantiation time. To see this, assume that for an analysis of the design space of such restrictions. More recent the sort functions in Figure 5 are internal to a module that pub- work has focused on frameworks that can tolerate potential ambi- lishes the following function in its interface: guities, and only deal with them if they actually appear [30]. Type checking select n first type checks the call to sort with the 4.

Then, all overloads in the current lexical function overloading has a common core: an overloaded function scope that are token-wise equivalent to the selected function, except describes a set of constraints on its arguments. For example, the for stronger constraints, are considered specializations of the se- constraint set of the first advance function in Figure 3 could be lected function. Here, the second and third overloads are specializa- loosely described as: tions of the first one.

No ambiguity is detected at this point. Moreover, the performance of which the example does not demonstrate. Non-generic functions, on the of argument types. Note that a constraint set can include constraints other hand, will still use overloading to select the most special- involving more than one argument type, making it impossible to ized versions of the functions they call.

This approach provides define the specialization ordering by looking at each argument po- fully modular type checking. All constraints in ming [36, 40] follows this model. The approach is also used for the constraint set are considered equal in weight; there is no pref- overloaded methods in object-oriented languages without multi- erence ordering between them. Jones [21] studied extensively the properties of constraint sets One can design around the lack of specialization by making with specialization ordering based on implication, and their use as each function that has specializations into a requirement of a con- bounds for type parameters of software components.

The special- cept. For example, the advance , distance , etc.

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Alternatively, sets is a preorder, a reflexive and transitive but not antisymmetric separate concepts, such as Advanceable, could be defined. This ei- relation on functions. Under this preorder, which we represent which captures a single function. For This design for specialization does remove the problem of am- overloading purposes, functions can be identified with their asso- biguities in internal overloads called by a generic function: all func- ciated constraint sets, and so we can think of A and B as sets of tion calls are resolved when the function is first seen, and the over- constraints.

Therefore, the only ambiguities possible from calling a specialized e. Moving internal ized as the other, as with overloads on distinct concrete types. A single minimal element means as static overloading. A1 would now be the most-specialized unambiguous overload resolution, there will be at least one which is minimal , match. A result is guaranteed to exist by the existence of the over- and two or more minimal elements indicates that several overloads load A that was necessary for type checking the body of f.

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Again, were equally good, and thus ambiguous. This approach provides a limited form of We can now describe the ambiguity in the sort overloads in specialization. The specializations of advance , distance , etc. Assume the three sort overloads the STL would be found, since their constraint sets form a chain.

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Further, that were rejected due to ambiguity, which would be the case in assume a public function f this corresponds to select n first in Figure 5. Silently ignoring the ambiguous definitions may thus not Section 3. Furthermore, we consider a call to f , from an external library, with types that satisfy some constraint set D, such that 4.