Changeset 18a7dcf1 for doc/theses/fangren_yu_MMath/intro.tex
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doc/theses/fangren_yu_MMath/intro.tex
rfbb5bdd r18a7dcf1 291 291 \section{Polymorphism} 292 292 293 \CFA provides polymorphic functions and types, where the polymorphic function can be the constraints types using assertions based on traits. 294 295 \subsection{\texorpdfstring{\protect\lstinline{forall} functions}{forall functions}} 296 \label{sec:poly-fns} 297 298 The signature feature of \CFA is parametric-polymorphic functions~\cite{forceone:impl,Cormack90,Duggan96} with functions generalized using a @forall@ clause (giving the language its name). 299 \begin{cfa} 300 @forall( T )@ T identity( T val ) { return val; } 301 int forty_two = identity( 42 ); $\C{// T is bound to int, forty\_two == 42}$ 302 \end{cfa} 303 This @identity@ function can be applied to any complete \newterm{object type} (or @otype@). 304 The type variable @T@ is transformed into a set of additional implicit parameters encoding sufficient information about @T@ to create and return a variable of that type. 305 The \CFA implementation passes the size and alignment of the type represented by an @otype@ parameter, as well as an assignment operator, constructor, copy constructor, and destructor. 306 If this extra information is not needed, for instance, for a pointer, the type parameter can be declared as a \newterm{data type} (or @dtype@). 307 308 In \CFA, the polymorphic runtime cost is spread over each polymorphic call, because more arguments are passed to polymorphic functions; 309 the experiments in Section~\ref{sec:eval} show this overhead is similar to \CC virtual function calls. 310 A design advantage is that, unlike \CC template functions, \CFA polymorphic functions are compatible with C \emph{separate compilation}, preventing compilation and code bloat. 311 312 Since bare polymorphic types provide a restricted set of available operations, \CFA provides a \newterm{type assertion}~\cite[pp.~37-44]{Alphard} mechanism to provide further type information, where type assertions may be variable or function declarations that depend on a polymorphic type variable. 313 For example, the function @twice@ can be defined using the \CFA syntax for operator overloading. 314 \begin{cfa} 315 forall( T @| { T ?+?(T, T); }@ ) T twice( T x ) { return x @+@ x; } $\C{// ? denotes operands}$ 316 int val = twice( twice( 3.7 ) ); $\C{// val == 14}$ 317 \end{cfa} 318 This works for any type @T@ with a matching addition operator. 319 The polymorphism is achieved by creating a wrapper function for calling @+@ with the @T@ bound to @double@ and then passing this function to the first call of @twice@. 320 There is now the option of using the same @twice@ and converting the result into @int@ on assignment or creating another @twice@ with the type parameter @T@ bound to @int@ because \CFA uses the return type~\cite{Cormack81,Baker82,Ada} in its type analysis. 321 The first approach has a late conversion from @double@ to @int@ on the final assignment, whereas the second has an early conversion to @int@. 322 \CFA minimizes the number of conversions and their potential to lose information; 323 hence, it selects the first approach, which corresponds with C programmer intuition. 324 325 Crucial to the design of a new programming language are the libraries to access thousands of external software features. 326 Like \CC, \CFA inherits a massive compatible library base, where other programming languages must rewrite or provide fragile interlanguage communication with C. 327 A simple example is leveraging the existing type-unsafe (@void *@) C @bsearch@ to binary search a sorted float array. 328 \begin{cfa} 329 void * bsearch( const void * key, const void * base, size_t nmemb, size_t size, 330 int (* compar)( const void *, const void * )); 331 int comp( const void * t1, const void * t2 ) { 332 return *(double *)t1 < *(double *)t2 ? -1 : *(double *)t2 < *(double *)t1 ? 1 : 0; 333 } 334 double key = 5.0, vals[10] = { /* 10 sorted float values */ }; 335 double * val = (double *)bsearch( &key, vals, 10, sizeof(vals[0]), comp ); $\C{// search sorted array}$ 336 \end{cfa} 337 This can be augmented simply with generalized, type-safe, \CFA-overloaded wrappers. 338 \begin{cfa} 339 forall( T | { int ?<?( T, T ); } ) T * bsearch( T key, const T * arr, size_t size ) { 340 int comp( const void * t1, const void * t2 ) { /* as above with double changed to T */ } 341 return (T *)bsearch( &key, arr, size, sizeof(T), comp ); 342 } 343 forall( T | { int ?<?( T, T ); } ) unsigned int bsearch( T key, const T * arr, size_t size ) { 344 T * result = bsearch( key, arr, size ); $\C{// call first version}$ 345 return result ? result - arr : size; $\C{// pointer subtraction includes sizeof(T)}$ 346 } 347 double * val = bsearch( 5.0, vals, 10 ); $\C{// selection based on return type}$ 348 int posn = bsearch( 5.0, vals, 10 ); 349 \end{cfa} 350 The nested function @comp@ provides the hidden interface from typed \CFA to untyped (@void *@) C, plus the cast of the result. 351 % FIX 352 Providing a hidden @comp@ function in \CC is awkward as lambdas do not use C calling conventions and template declarations cannot appear in block scope. 353 In addition, an alternate kind of return is made available: position versus pointer to found element. 354 \CC's type system cannot disambiguate between the two versions of @bsearch@ because it does not use the return type in overload resolution, nor can \CC separately compile a template @bsearch@. 355 356 \CFA has replacement libraries condensing hundreds of existing C functions into tens of \CFA overloaded functions, all without rewriting the actual computations (see Section~\ref{sec:libraries}). 357 For example, it is possible to write a type-safe \CFA wrapper @malloc@ based on the C @malloc@, where the return type supplies the type/size of the allocation, which is impossible in most type systems. 358 \begin{cfa} 359 forall( T & | sized(T) ) T * malloc( void ) { return (T *)malloc( sizeof(T) ); } 360 // select type and size from left-hand side 361 int * ip = malloc(); double * dp = malloc(); struct S {...} * sp = malloc(); 362 \end{cfa} 363 364 Call site inferencing and nested functions provide a localized form of inheritance. 365 For example, the \CFA @qsort@ only sorts in ascending order using @<@. 366 However, it is trivial to locally change this behavior. 367 \begin{cfa} 368 forall( T | { int ?<?( T, T ); } ) void qsort( const T * arr, size_t size ) { /* use C qsort */ } 369 int main() { 370 int ?<?( double x, double y ) { return x @>@ y; } $\C{// locally override behavior}$ 371 qsort( vals, 10 ); $\C{// descending sort}$ 372 } 373 \end{cfa} 374 The local version of @?<?@ performs @?>?@ overriding the built-in @?<?@ so it is passed to @qsort@. 375 Therefore, programmers can easily form local environments, adding and modifying appropriate functions, to maximize the reuse of other existing functions and types. 376 377 To reduce duplication, it is possible to distribute a group of @forall@ (and storage-class qualifiers) over functions/types, such that each block declaration is prefixed by the group (see the example in Appendix~\ref{s:CforallStack}). 378 \begin{cfa} 379 forall( @T@ ) { $\C{// distribution block, add forall qualifier to declarations}$ 380 struct stack { stack_node(@T@) * head; }; $\C{// generic type}$ 381 inline { $\C{// nested distribution block, add forall/inline to declarations}$ 382 void push( stack(@T@) & s, @T@ value ) ... $\C{// generic operations}$ 383 } 384 } 385 \end{cfa} 386 387 388 \subsection{Traits} 389 390 \CFA provides \newterm{traits} to name a group of type assertions, where the trait name allows specifying the same set of assertions in multiple locations, preventing repetition mistakes at each function declaration. 391 \begin{cquote} 392 \lstDeleteShortInline@% 393 \begin{tabular}{@{}l@{\hspace{\parindentlnth}}|@{\hspace{\parindentlnth}}l@{}} 394 \begin{cfa} 395 trait @sumable@( T ) { 396 void @?{}@( T &, zero_t ); // 0 literal constructor 397 T ?+?( T, T ); // assortment of additions 398 T @?+=?@( T &, T ); 399 T ++?( T & ); 400 T ?++( T & ); 401 }; 402 \end{cfa} 403 & 404 \begin{cfa} 405 forall( T @| sumable( T )@ ) // use trait 406 T sum( T a[$\,$], size_t size ) { 407 @T@ total = { @0@ }; // initialize by 0 constructor 408 for ( size_t i = 0; i < size; i += 1 ) 409 total @+=@ a[i]; // select appropriate + 410 return total; 411 } 412 \end{cfa} 413 \end{tabular} 414 \lstMakeShortInline@% 415 \end{cquote} 416 417 Note that the @sumable@ trait does not include a copy constructor needed for the right side of @?+=?@ and return; 418 it is provided by @otype@, which is syntactic sugar for the following trait. 419 \begin{cfa} 420 trait otype( T & | sized(T) ) { // sized is a pseudo-trait for types with known size and alignment 421 void ?{}( T & ); $\C{// default constructor}$ 422 void ?{}( T &, T ); $\C{// copy constructor}$ 423 void ?=?( T &, T ); $\C{// assignment operator}$ 424 void ^?{}( T & ); $\C{// destructor}$ 425 }; 426 \end{cfa} 427 Given the information provided for an @otype@, variables of polymorphic type can be treated as if they were a complete type: stack allocatable, default or copy initialized, assigned, and deleted. 428 429 In summation, the \CFA type system uses \newterm{nominal typing} for concrete types, matching with the C type system, and \newterm{structural typing} for polymorphic types. 430 Hence, trait names play no part in type equivalence; 431 the names are simply macros for a list of polymorphic assertions, which are expanded at usage sites. 432 Nevertheless, trait names form a logical subtype hierarchy with @dtype@ at the top, where traits often contain overlapping assertions, \eg operator @+@. 433 Traits are used like interfaces in Java or abstract base classes in \CC, but without the nominal inheritance relationships. 434 Instead, each polymorphic function (or generic type) defines the structural type needed for its execution (polymorphic type key), and this key is fulfilled at each call site from the lexical environment, which is similar to the Go~\cite{Go} interfaces. 435 Hence, new lexical scopes and nested functions are used extensively to create local subtypes, as in the @qsort@ example, without having to manage a nominal inheritance hierarchy. 436 % (Nominal inheritance can be approximated with traits using marker variables or functions, as is done in Go.) 437 438 % Nominal inheritance can be simulated with traits using marker variables or functions: 439 % \begin{cfa} 440 % trait nominal(T) { 441 % T is_nominal; 442 % }; 443 % int is_nominal; $\C{// int now satisfies the nominal trait}$ 444 % \end{cfa} 445 % 446 % Traits, however, are significantly more powerful than nominal-inheritance interfaces; most notably, traits may be used to declare a relationship \emph{among} multiple types, a property that may be difficult or impossible to represent in nominal-inheritance type systems: 447 % \begin{cfa} 448 % trait pointer_like(Ptr, El) { 449 % lvalue El *?(Ptr); $\C{// Ptr can be dereferenced into a modifiable value of type El}$ 450 % } 451 % struct list { 452 % int value; 453 % list * next; $\C{// may omit "struct" on type names as in \CC}$ 454 % }; 455 % typedef list * list_iterator; 456 % 457 % lvalue int *?( list_iterator it ) { return it->value; } 458 % \end{cfa} 459 % In the example above, @(list_iterator, int)@ satisfies @pointer_like@ by the user-defined dereference function, and @(list_iterator, list)@ also satisfies @pointer_like@ by the built-in dereference operator for pointers. Given a declaration @list_iterator it@, @*it@ can be either an @int@ or a @list@, with the meaning disambiguated by context (\eg @int x = *it;@ interprets @*it@ as an @int@, while @(*it).value = 42;@ interprets @*it@ as a @list@). 460 % While a nominal-inheritance system with associated types could model one of those two relationships by making @El@ an associated type of @Ptr@ in the @pointer_like@ implementation, few such systems could model both relationships simultaneously. 461 462 463 \subsection{Generic Types} 464 465 A significant shortcoming of standard C is the lack of reusable type-safe abstractions for generic data structures and algorithms. 466 Broadly speaking, there are three approaches to implement abstract data structures in C. 467 One approach is to write bespoke data structures for each context in which they are needed. 468 While this approach is flexible and supports integration with the C type checker and tooling, it is also tedious and error prone, especially for more complex data structures. 469 A second approach is to use @void *@-based polymorphism, \eg the C standard library functions @bsearch@ and @qsort@, which allow for the reuse of code with common functionality. 470 However, basing all polymorphism on @void *@ eliminates the type checker's ability to ensure that argument types are properly matched, often requiring a number of extra function parameters, pointer indirection, and dynamic allocation that is otherwise not needed. 471 A third approach to generic code is to use preprocessor macros, which does allow the generated code to be both generic and type checked, but errors may be difficult to interpret. 472 Furthermore, writing and using preprocessor macros is unnatural and inflexible. 473 474 \CC, Java, and other languages use \newterm{generic types} to produce type-safe abstract data types. 475 \CFA generic types integrate efficiently and naturally with the existing polymorphic functions, while retaining backward compatibility with C and providing separate compilation. 476 However, for known concrete parameters, the generic-type definition can be inlined, like \CC templates. 477 478 A generic type can be declared by placing a @forall@ specifier on a @struct@ or @union@ declaration and instantiated using a parenthesized list of types after the type name. 479 \begin{cquote} 480 \lstDeleteShortInline@% 481 \begin{tabular}{@{}l|@{\hspace{\parindentlnth}}l@{}} 482 \begin{cfa} 483 @forall( R, S )@ struct pair { 484 R first; S second; 485 }; 486 @forall( T )@ // dynamic 487 T value( pair(const char *, T) p ) { return p.second; } 488 @forall( dtype F, T )@ // dtype-static (concrete) 489 T value( pair(F *, T * ) p) { return *p.second; } 490 \end{cfa} 491 & 492 \begin{cfa} 493 pair(const char *, int) p = {"magic", 42}; // concrete 494 int i = value( p ); 495 pair(void *, int *) q = { 0, &p.second }; // concrete 496 i = value( q ); 497 double d = 1.0; 498 pair(double *, double *) r = { &d, &d }; // concrete 499 d = value( r ); 500 \end{cfa} 501 \end{tabular} 502 \lstMakeShortInline@% 503 \end{cquote} 504 505 \CFA classifies generic types as either \newterm{concrete} or \newterm{dynamic}. 506 Concrete types have a fixed memory layout regardless of type parameters, whereas dynamic types vary in memory layout depending on their type parameters. 507 A \newterm{dtype-static} type has polymorphic parameters but is still concrete. 508 Polymorphic pointers are an example of dtype-static types; 509 given some type variable @T@, @T@ is a polymorphic type, as is @T *@, but @T *@ has a fixed size and can, therefore, be represented by @void *@ in code generation. 510 511 \CFA generic types also allow checked argument constraints. 512 For example, the following declaration of a sorted set type ensures the set key supports equality and relational comparison. 513 \begin{cfa} 514 forall( Key | { _Bool ?==?(Key, Key); _Bool ?<?(Key, Key); } ) struct sorted_set; 515 \end{cfa} 516 517 518 \subsection{Concrete generic types} 519 520 The \CFA translator template expands concrete generic types into new structure types, affording maximal inlining. 521 To enable interoperation among equivalent instantiations of a generic type, the translator saves the set of instantiations currently in scope and reuses the generated structure declarations where appropriate. 522 A function declaration that accepts or returns a concrete generic type produces a declaration for the instantiated structure in the same scope, which all callers may reuse. 523 For example, the concrete instantiation for @pair( const char *, int )@ is 524 \begin{cfa} 525 struct _pair_conc0 { 526 const char * first; int second; 527 }; 528 \end{cfa} 529 530 A concrete generic type with dtype-static parameters is also expanded to a structure type, but this type is used for all matching instantiations. 531 In the above example, the @pair( F *, T * )@ parameter to @value@ is such a type; its expansion is below, and it is used as the type of the variables @q@ and @r@ as well, with casts for member access where appropriate. 532 \begin{cfa} 533 struct _pair_conc1 { 534 void * first, * second; 535 }; 536 \end{cfa} 537 538 539 \subsection{Dynamic generic types} 540 541 Though \CFA implements concrete generic types efficiently, it also has a fully general system for dynamic generic types. 542 As mentioned in Section~\ref{sec:poly-fns}, @otype@ function parameters (in fact, all @sized@ polymorphic parameters) come with implicit size and alignment parameters provided by the caller. 543 Dynamic generic types also have an \newterm{offset array} containing structure-member offsets. 544 A dynamic generic @union@ needs no such offset array, as all members are at offset 0, but size and alignment are still necessary. 545 Access to members of a dynamic structure is provided at runtime via base displacement addressing 546 % FIX 547 using the structure pointer and the member offset (similar to the @offsetof@ macro), moving a compile-time offset calculation to runtime. 548 549 The offset arrays are statically generated where possible. 550 If a dynamic generic type is declared to be passed or returned by value from a polymorphic function, the translator can safely assume that the generic type is complete (\ie has a known layout) at any call site, and the offset array is passed from the caller; 551 if the generic type is concrete at the call site, the elements of this offset array can even be statically generated using the C @offsetof@ macro. 552 As an example, the body of the second @value@ function is implemented as 553 \begin{cfa} 554 _assign_T( _retval, p + _offsetof_pair[1] ); $\C{// return *p.second}$ 555 \end{cfa} 556 \newpage 557 \noindent 558 Here, @_assign_T@ is passed in as an implicit parameter from @T@, and takes two @T *@ (@void *@ in the generated code), a destination and a source, and @_retval@ is the pointer to a caller-allocated buffer for the return value, the usual \CFA method to handle dynamically sized return types. 559 @_offsetof_pair@ is the offset array passed into @value@; 560 this array is generated at the call site as 561 \begin{cfa} 562 size_t _offsetof_pair[] = { offsetof( _pair_conc0, first ), offsetof( _pair_conc0, second ) } 563 \end{cfa} 564 565 In some cases, the offset arrays cannot be statically generated. 566 For instance, modularity is generally provided in C by including an opaque forward declaration of a structure and associated accessor and mutator functions in a header file, with the actual implementations in a separately compiled @.c@ file. 567 \CFA supports this pattern for generic types, but the caller does not know the actual layout or size of the dynamic generic type and only holds it by a pointer. 568 The \CFA translator automatically generates \newterm{layout functions} for cases where the size, alignment, and offset array of a generic struct cannot be passed into a function from that function's caller. 569 These layout functions take as arguments pointers to size and alignment variables and a caller-allocated array of member offsets, as well as the size and alignment of all @sized@ parameters to the generic structure (un@sized@ parameters are forbidden from being used in a context that affects layout). 570 Results of these layout functions are cached so that they are only computed once per type per function. %, as in the example below for @pair@. 571 Layout functions also allow generic types to be used in a function definition without reflecting them in the function signature. 572 For instance, a function that strips duplicate values from an unsorted @vector(T)@ likely has a pointer to the vector as its only explicit parameter, but uses some sort of @set(T)@ internally to test for duplicate values. 573 This function could acquire the layout for @set(T)@ by calling its layout function with the layout of @T@ implicitly passed into the function. 574 575 Whether a type is concrete, dtype-static, or dynamic is decided solely on the @forall@'s type parameters. 576 This design allows opaque forward declarations of generic types, \eg @forall(T)@ @struct Box@ -- like in C, all uses of @Box(T)@ can be separately compiled, and callers from other translation units know the proper calling conventions to use. 577 If the definition of a structure type is included in deciding whether a generic type is dynamic or concrete, some further types may be recognized as dtype-static (\eg @forall(T)@ @struct unique_ptr { T * p }@ does not depend on @T@ for its layout, but the existence of an @otype@ parameter means that it \emph{could}.); 578 however, preserving separate compilation (and the associated C compatibility) in the existing design is judged to be an appropriate trade-off. 293 579 294 580
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