Changeset 72dc82a


Ignore:
Timestamp:
Mar 31, 2017, 12:21:52 PM (5 years ago)
Author:
Thierry Delisle <tdelisle@…>
Branches:
aaron-thesis, arm-eh, cleanup-dtors, deferred_resn, demangler, jacob/cs343-translation, jenkins-sandbox, master, new-ast, new-ast-unique-expr, new-env, no_list, persistent-indexer, resolv-new, with_gc
Children:
78d3dd5
Parents:
690f13c (diff), 936a287 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge branch 'master' of plg.uwaterloo.ca:software/cfa/cfa-cc

Files:
17 edited

Legend:

Unmodified
Added
Removed
  • doc/LaTeXmacros/common.tex

    r690f13c r72dc82a  
    4242\newcommand{\CCfourteen}{\rm C\kern-.1em\hbox{+\kern-.25em+}14\xspace} % C++14 symbolic name
    4343\newcommand{\CCseventeen}{\rm C\kern-.1em\hbox{+\kern-.25em+}17\xspace} % C++17 symbolic name
     44\newcommand{\CCtwenty}{\rm C\kern-.1em\hbox{+\kern-.25em+}20} % C++20 symbolic name
    4445\newcommand{\Celeven}{C11\xspace}               % C11 symbolic name
    4546\newcommand{\Csharp}{C\raisebox{0.4ex}{\#}\xspace}      % C# symbolic name
     
    200201\newcommand{\opt}{$_{opt}$\ }
    201202
     203\usepackage{varioref}                 % extended references
    202204% adjust varioref package with default "section" and "page" titles, and optional title with faraway page numbers
    203205% \VRef{label} => Section 2.7, \VPageref{label} => page 17
     
    251253                _Bool,catch,catchResume,choose,_Complex,__complex,__complex__,__const,__const__,disable,dtype,enable,__extension__,
    252254                fallthrough,fallthru,finally,forall,ftype,_Generic,_Imaginary,inline,__label__,lvalue,_Noreturn,one_t,otype,restrict,_Static_assert,
    253                 _Thread_local,throw,throwResume,trait,try,typeof,__typeof,__typeof__,zero_t},
     255                _Thread_local,throw,throwResume,trait,try,ttype,typeof,__typeof,__typeof__,zero_t},
    254256}%
    255257
  • doc/generic_types/generic_types.bib

    r690f13c r72dc82a  
    3434}
    3535
     36@techreport{C++Concepts,
     37    type = {International Standard},
     38    keywords    = {ISO/IEC TS 19217:2015},
     39    contributer = {a3moss@uwaterloo.ca},
     40    key         = {{ISO/IEC} {TS} 19217},
     41    title       = {Information technology -- Programming languages -- {C}{\kern-.1em\hbox{\large\texttt{+\kern-.25em+}}} Extensions for concepts},
     42    institution = {International Standard Organization},
     43    address     = {http://www.iso.org},
     44    year        = 2015
     45}
     46
    3647@phdthesis{Ditchfield92,
    3748    keywords    = {C, parametric polymorphism, overloading},
     
    4354    address     = {Waterloo, Ontario, Canada, N2L 3G1},
    4455    note        = {\href{http://plg.uwaterloo.ca/theses/DitchfieldThesis.pdf}{http://\-plg.uwaterloo.ca/\-theses/\-DitchfieldThesis.pdf}}
     56}
     57
     58@article{Gro06,
     59 author = {Grossman, Dan},
     60 title = {Quantified Types in an Imperative Language},
     61 journal = {ACM Trans. Program. Lang. Syst.},
     62 issue_date = {May 2006},
     63 volume = {28},
     64 number = {3},
     65 month = may,
     66 year = {2006},
     67 issn = {0164-0925},
     68 pages = {429--475},
     69 numpages = {47},
     70 url = {http://doi.acm.org.proxy.lib.uwaterloo.ca/10.1145/1133651.1133653},
     71 doi = {10.1145/1133651.1133653},
     72 acmid = {1133653},
     73 publisher = {ACM},
     74 address = {New York, NY, USA},
    4575}
    4676
  • doc/generic_types/generic_types.tex

    r690f13c r72dc82a  
    1 % take of review (for line numbers) and anonymous (for anonymization) on submission
    2 \documentclass[format=acmlarge, anonymous, review]{acmart}
     1% take off review (for line numbers) and anonymous (for anonymization) on submission
     2% \documentclass[format=acmlarge, anonymous, review]{acmart}
     3\documentclass[format=acmlarge, review]{acmart}
    34
    45\usepackage{listings}   % For code listings
     
    1011\newcommand{\CCfourteen}{\rm C\kern-.1em\hbox{+\kern-.25em+}14} % C++14 symbolic name
    1112\newcommand{\CCseventeen}{\rm C\kern-.1em\hbox{+\kern-.25em+}17} % C++17 symbolic name
     13\newcommand{\CCtwenty}{\rm C\kern-.1em\hbox{+\kern-.25em+}20} % C++20 symbolic name
    1214
    1315\newcommand{\TODO}{\textbf{TODO}}
     
    1921\lstdefinelanguage{CFA}[ANSI]{C}{
    2022        morekeywords={_Alignas,_Alignof,__alignof,__alignof__,asm,__asm,__asm__,_At,_Atomic,__attribute,__attribute__,auto,
    21                 _Bool,catch,catchResume,choose,_Complex,__complex,__complex__,__const,__const__,disable,dtype,enable,__extension__,
     23                _Bool,bool,catch,catchResume,choose,_Complex,__complex,__complex__,__const,__const__,disable,dtype,enable,__extension__,
    2224                fallthrough,fallthru,finally,forall,ftype,_Generic,_Imaginary,inline,__label__,lvalue,_Noreturn,one_t,otype,restrict,size_t,sized,_Static_assert,
    23                 _Thread_local,throw,throwResume,trait,try,typeof,__typeof,__typeof__,zero_t},
     25                _Thread_local,throw,throwResume,trait,try,ttype,typeof,__typeof,__typeof__,zero_t},
    2426}%
    2527
     
    123125
    124126\begin{abstract}
    125 \TODO{} Write abstract.
     127The C programming language is a foundational technology for modern computing, with millions of lines of code implementing everything from commercial operating systems to hobby projects. This installed base of code and the programmers who produced it represent a massive software engineering investment spanning decades. Nonetheless, C, first standardized over thirty years ago, lacks many features that make programming in more modern languages safer and more productive. The goal of the \CFA{} project is to create an extension of C that provides modern safety and productivity features while still ensuring strong backwards compatibility with C. Particularly, \CFA{} is designed to have an orthogonal feature set based closely on the C programming paradigm, so that \CFA{} features can be added incrementally to existing C code-bases, and C programmers can learn \CFA{} extensions on an as-needed basis, preserving investment in existing engineers and code. This paper describes how generic and tuple types are implemented in \CFA{} in accordance with these principles.
    126128\end{abstract}
    127129
     
    132134\section{Introduction \& Background}
    133135
    134 \CFA{}\footnote{Pronounced ``C-for-all'', and written \CFA{} or Cforall.} is an evolutionary extension of the C programming language which aims to add modern language features to C while maintaining both source compatibility with C and a familiar mental model for programmers. Four key design goals were set out in the original design of \CFA{} \citep{Bilson03}:
     136\CFA{}\footnote{Pronounced ``C-for-all'', and written \CFA{} or Cforall.} is an evolutionary extension of the C programming language that aims to add modern language features to C while maintaining both source compatibility with C and a familiar mental model for programmers. Four key design goals were set out in the original design of \CFA{} \citep{Bilson03}:
    135137\begin{enumerate}
    136138\item The behaviour of standard C code must remain the same when translated by a \CFA{} compiler as when translated by a C compiler.
     
    139141\item Extensions introduced by \CFA{} must be translated in the most efficient way possible.
    140142\end{enumerate}
    141 The purpose of these goals is to ensure that existing C codebases can be converted to \CFA{} incrementally and with minimal effort, and that programmers who already know C can productively produce \CFA{} code without extensive training beyond the extension features they wish to employ. In its current implementation, \CFA{} is compiled by translating it to GCC-dialect C, allowing it to leverage the portability and code optimizations provided by GCC, meeting goals (1)-(3).
     143The purpose of these goals is to ensure that existing C code-bases can be converted to \CFA{} incrementally and with minimal effort, and that programmers who already know C can productively produce \CFA{} code without training in \CFA{} beyond the extension features they wish to employ. In its current implementation, \CFA{} is compiled by translating it to GCC-dialect C, allowing it to leverage the portability and code optimizations provided by GCC, meeting goals (1)-(3).
    142144
    143145\CFA{} has been previously extended with polymorphic functions and name overloading (including operator overloading) \citep{Bilson03}, and deterministically-executed constructors and destructors \citep{Schluntz17}. This paper describes how generic and tuple types are designed and implemented in \CFA{} in accordance with both the backward compatibility goals and existing features described above.
     
    146148\label{sec:poly-fns}
    147149
    148 \CFA{}'s polymorphism was originally formalized by \citet{Ditchfield92}, and first implemented by \citet{Bilson03}. The signature feature of \CFA{} is parametric-polymorphic functions; such functions are written using a @forall@ clause (which gives the language its name): 
     150\CFA{}'s polymorphism was originally formalized by \citet{Ditchfield92}, and first implemented by \citet{Bilson03}. The signature feature of \CFA{} is parametric-polymorphic functions; such functions are written using a @forall@ clause (which gives the language its name):
    149151\begin{lstlisting}
    150152forall(otype T)
    151 T identity(T x) {
    152     return x;
    153 }
     153T identity(T x) { return x; }
    154154
    155155int forty_two = identity(42); // T is bound to int, forty_two == 42
    156156\end{lstlisting}
    157 The @identity@ function above can be applied to any complete object type (or ``@otype@''). The type variable @T@ is transformed into a set of additional implicit parameters to @identity@, which encode sufficient information about @T@ to create and return a variable of that type. 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. If this extra information is not needed, the type parameter can be declared as @dtype T@, where @dtype@ is short for ``data type''.
     157The @identity@ function above can be applied to any complete object type (or ``@otype@''). The type variable @T@ is transformed into a set of additional implicit parameters to @identity@, that encode sufficient information about @T@ to create and return a variable of that type. 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. If this extra information is not needed, the type parameter can be declared as @dtype T@, where @dtype@ is short for ``data type''.
    158158
    159159Here, the runtime cost of polymorphism is spread over each polymorphic call, due to passing more arguments to polymorphic functions; preliminary experiments have shown this overhead to be similar to \CC{} virtual function calls. An advantage of this design is that, unlike \CC{} template functions, \CFA{} @forall@ functions are compatible with separate compilation.
     
    162162\begin{lstlisting}
    163163forall(otype T | { T twice(T); })
    164 T four_times(T x) {
    165     return twice( twice(x) );
    166 }
     164T four_times(T x) { return twice( twice(x) ); }
    167165
    168166double twice(double d) { return d * 2.0; } // (1)
     
    176174forall(otype S | { S ?+?(S, S); })
    177175S twice(S x) { return x + x; }  // (2)
    178 \end{lstlisting} 
    179 This version of @twice@ works for any type @S@ that has an addition operator defined for it, and it could have been used to satisfy the type assertion on @four_times@. 
    180 The translator accomplishes this by creating a wrapper function calling @twice // (2)@ with @S@ bound to @double@, then providing this wrapper function to @four_times@\footnote{\lstinline@twice // (2)@ could also have had a type parameter named \lstinline@T@; \CFA{} specifies renaming of the type parameters, which would avoid the name conflict with the type variable \lstinline@T@ of \lstinline@four_times@.}.
     176\end{lstlisting}
     177This version of @twice@ works for any type @S@ that has an addition operator defined for it, and it could have been used to satisfy the type assertion on @four_times@.
     178The translator accomplishes this polymorphism by creating a wrapper function calling @twice // (2)@ with @S@ bound to @double@, then providing this wrapper function to @four_times@\footnote{\lstinline@twice // (2)@ could also have had a type parameter named \lstinline@T@; \CFA{} specifies renaming of the type parameters, which would avoid the name conflict with the type variable \lstinline@T@ of \lstinline@four_times@.}.
    181179
    182180\subsection{Traits}
     
    198196forall(otype M | has_magnitude(M))
    199197M max_magnitude( M a, M b ) {
    200     return abs(a) < abs(b) ? b : a; 
     198    return abs(a) < abs(b) ? b : a;
    201199}
    202200\end{lstlisting}
     
    213211};
    214212\end{lstlisting}
    215 Given this information, variables of polymorphic type can be treated as if they were a complete struct type -- they can be stack-allocated using the @alloca@ compiler builtin, default or copy-initialized, assigned, and deleted. As an example, the @abs@ function above would produce generated code something like the following (simplified for clarity and brevity):
    216 \begin{lstlisting}
    217 void abs( size_t _sizeof_M, size_t _alignof_M, 
    218                 void (*_ctor_M)(void*), void (*_copy_M)(void*, void*), 
    219                 void (*_assign_M)(void*, void*), void (*_dtor_M)(void*), 
    220                 bool (*_lt_M)(void*, void*), void (*_neg_M)(void*, void*), 
    221         void (*_ctor_M_zero)(void*, int), 
     213Given the information provided for an @otype@, variables of polymorphic type can be treated as if they were a complete struct type -- they can be stack-allocated using the @alloca@ compiler builtin, default or copy-initialized, assigned, and deleted. As an example, the @abs@ function above produces generated code something like the following (simplified for clarity and brevity):
     214\begin{lstlisting}
     215void abs( size_t _sizeof_M, size_t _alignof_M,
     216                void (*_ctor_M)(void*), void (*_copy_M)(void*, void*),
     217                void (*_assign_M)(void*, void*), void (*_dtor_M)(void*),
     218                bool (*_lt_M)(void*, void*), void (*_neg_M)(void*, void*),
     219        void (*_ctor_M_zero)(void*, int),
    222220                void* m, void* _rtn ) {  // polymorphic parameter and return passed as void*
    223221        // M zero = { 0 };
    224         void* zero = alloca(_sizeof_M);  // stack allocate 0 temporary
     222        void* zero = alloca(_sizeof_M);  // stack allocate zero temporary
    225223        _ctor_M_zero(zero, 0);  // initialize using zero_t constructor
    226224        // return m < zero ? -m : m;
    227         void *_tmp = alloca(_sizeof_M)
     225        void *_tmp = alloca(_sizeof_M);
    228226        _copy_M( _rtn,  // copy-initialize return value
    229227                _lt_M( m, zero ) ?  // check condition
     
    241239
    242240int is_nominal;  // int now satisfies the nominal trait
    243 {
    244     char is_nominal; // char satisfies the nominal trait
    245 }
    246 // char no longer satisfies the nominal trait here 
    247 \end{lstlisting}
    248 
    249 Traits, however, are significantly more powerful than nominal-inheritance interfaces; firstly, due to the scoping rules of the declarations that satisfy a trait's type assertions, a type may not satisfy a trait everywhere that the type is declared, as with @char@ and the @nominal@ trait above. Secondly, traits may be used to declare a relationship among multiple types, a property that may be difficult or impossible to represent in nominal-inheritance type systems:
     241\end{lstlisting}
     242
     243Traits, however, are significantly more powerful than nominal-inheritance interfaces; most notably, traits may be used to declare a relationship among multiple types, a property that may be difficult or impossible to represent in nominal-inheritance type systems:
    250244\begin{lstlisting}
    251245trait pointer_like(otype Ptr, otype El) {
     
    260254typedef list *list_iterator;
    261255
    262 lvalue int *?( list_iterator it ) {
    263     return it->value;
    264 }
    265 \end{lstlisting}
    266 
    267 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@).
     256lvalue int *?( list_iterator it ) { return it->value; }
     257\end{lstlisting}
     258
     259In 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@).
    268260While 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.
    269261
    270262\section{Generic Types}
    271263
    272 One of the known shortcomings of standard C is that it does not provide reusable type-safe abstractions for generic data structures and algorithms. Broadly speaking, there are three approaches to create data structures in C. One approach is to write bespoke data structures for each context in which they are needed. While this approach is flexible and supports integration with the C type-checker and tooling, it is also tedious and error-prone, especially for data structures more complicated than a singly-linked list. A second approach is to use @void*@-based polymorphism. This approach is taken by the C standard library functions @qsort@ and @bsearch@, and does allow the use of common code for common functionality. However, basing all polymorphism on @void*@ eliminates the type-checker's ability to ensure that argument types are properly matched, as well as adding pointer indirection and dynamic allocation to algorithms and data structures which would not otherwise require them. A third approach to generic code is to use pre-processor macros to generate it -- this approach does allow the generated code to be both generic and type-checked, though any errors produced may be difficult to read. Furthermore, writing and invoking C code as preprocessor macros is unnatural and somewhat inflexible.
    273 
    274 Other C-like languages such as \CC{} and Java use \emph{generic types} to produce type-safe abstract data types. The \CFA{} team has chosen to implement generic types as well, with the constraints that the generic types design for \CFA{} must integrate efficiently and naturally with the existing polymorphic functions in \CFA{}, while retaining backwards compatibility with C; maintaining separate compilation is a particularly important constraint on the design. However, where the concrete parameters of the generic type are known, there should not be extra overhead for the use of a generic type.
     264One of the known shortcomings of standard C is that it does not provide reusable type-safe abstractions for generic data structures and algorithms. Broadly speaking, there are three approaches to create data structures in C. One approach is to write bespoke data structures for each context in which they are needed. 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. A second approach is to use @void*@-based polymorphism. This approach is taken by the C standard library functions @qsort@ and @bsearch@, and does allow the use of common code for common functionality. However, basing all polymorphism on @void*@ eliminates the type-checker's ability to ensure that argument types are properly matched, often requires a number of extra function parameters, and also adds pointer indirection and dynamic allocation to algorithms and data structures that would not otherwise require them. A third approach to generic code is to use pre-processor macros to generate it -- this approach does allow the generated code to be both generic and type-checked, though any errors produced may be difficult to interpret. Furthermore, writing and invoking C code as preprocessor macros is unnatural and somewhat inflexible.
     265
     266Other C-like languages such as \CC{} and Java use \emph{generic types} to produce type-safe abstract data types. The authors have chosen to implement generic types as well, with some care taken that the generic types design for \CFA{} integrates efficiently and naturally with the existing polymorphic functions in \CFA{} while retaining backwards compatibility with C; maintaining separate compilation is a particularly important constraint on the design. However, where the concrete parameters of the generic type are known, there is not extra overhead for the use of a generic type.
    275267
    276268A 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:
     
    297289\end{lstlisting}
    298290
    299 \CFA{} classifies generic types as either \emph{concrete} or \emph{dynamic}. Dynamic generic types vary in their in-memory layout depending on their type parameters, while concrete generic types have a fixed memory layout regardless of type parameters. A type may have polymorphic parameters but still be concrete; \CFA{} refers to such types as \emph{dtype-static}. Polymorphic pointers are an example of dtype-static types -- @forall(dtype T) T*@ is a polymorphic type, but for any @T@ chosen, @T*@ will have exactly the same in-memory representation as a @void*@, and can therefore be represented by a @void*@ in code generation.
     291\CFA{} classifies generic types as either \emph{concrete} or \emph{dynamic}. Dynamic generic types vary in their in-memory layout depending on their type parameters, while concrete generic types have a fixed memory layout regardless of type parameters. A type may have polymorphic parameters but still be concrete; in \CFA{} such types are called \emph{dtype-static}. Polymorphic pointers are an example of dtype-static types -- @forall(dtype T) T*@ is a polymorphic type, but for any @T@ chosen, @T*@ has exactly the same in-memory representation as a @void*@, and can therefore be represented by a @void*@ in code generation.
     292
     293\CFA{} generic types may also specify constraints on their argument type to be checked by the compiler. For example, consider the following declaration of a sorted set type, which ensures that the set key supports comparison and tests for equality:
     294\begin{lstlisting}
     295forall(otype Key | { bool ?==?(Key, Key); bool ?<?(Key, Key); })
     296struct sorted_set;
     297\end{lstlisting}
    300298
    301299\subsection{Concrete Generic Types}
    302300
    303 The \CFA{} translator instantiates concrete generic types by template-expanding them to fresh struct types; concrete generic types can therefore be used with zero runtime overhead. To enable interoperation between equivalent instantiations of a generic type, the translator saves the set of instantiations currently in scope and re-uses the generated struct declarations where appropriate. As an example, the concrete instantiation for @pair(const char*, int)@ would look something like this:
     301The \CFA{} translator instantiates concrete generic types by template-expanding them to fresh struct types; concrete generic types can therefore be used with zero runtime overhead. To enable inter-operation among equivalent instantiations of a generic type, the translator saves the set of instantiations currently in scope and reuses the generated struct declarations where appropriate. For example, a function declaration that accepts or returns a concrete generic type produces a declaration for the instantiated struct in the same scope, which all callers that can see that declaration may reuse. As an example of the expansion, the concrete instantiation for @pair(const char*, int)@ looks like this:
    304302\begin{lstlisting}
    305303struct _pair_conc1 {
     
    309307\end{lstlisting}
    310308
    311 A concrete generic type with dtype-static parameters is also expanded to a struct type, but this struct type is used for all matching instantiations. In the example above, the @pair(F*, T*)@ parameter to @value_p@ is such a type; its expansion would look something like this, and be used as the type of the variables @q@ and @r@ as well, with casts for member access where appropriate:
     309A concrete generic type with dtype-static parameters is also expanded to a struct type, but this struct type is used for all matching instantiations. In the example above, the @pair(F*, T*)@ parameter to @value_p@ is such a type; its expansion looks something like this, and is used as the type of the variables @q@ and @r@ as well, with casts for member access where appropriate:
    312310\begin{lstlisting}
    313311struct _pair_conc0 {
     
    319317\subsection{Dynamic Generic Types}
    320318
    321 Though \CFA{} implements concrete generic types efficiently, it also has a fully-general system for computing with dynamic generic types. 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. Dynamic generic structs also come with an \emph{offset array} which contains the offsets of each member of the struct\footnote{Dynamic generic unions need no such offset array, as all members are at offset 0.}. Access to members\footnote{The \lstinline@offsetof@ macro is implmented similarly.} of a dynamic generic struct is provided by adding the corresponding member of the offset array to the struct pointer at runtime, essentially moving a compile-time offset calculation to runtime where neccessary.
    322 
    323 These offset arrays are staticly generated where possible. 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 (that is, has a known layout) at any call-site, and the offset array is passed from the caller; if the generic type is concrete at the call site this offset array can even be statically generated using the C @offsetof@ macro. As an example, @p.second@ in the @value@ function above is implemented as @*(p + _offsetof_pair[1])@, where @p@ is a @void*@, and @_offsetof_pair@ is the offset array passed in to @value@ for @pair(const char*, T)@. The offset array @_offsetof_pair@ is generated at the call site as @size_t _offsetof_pair[] = { offsetof(_pair_conc1, first), offsetof(_pair_conc1, second) };@.
    324 
    325 In some cases the offset arrays cannot be staticly generated. For instance, modularity is generally produced in C by including an opaque forward-declaration of a struct and associated accessor and mutator routines in a header file, with the actual implementations in a separately-compiled \texttt{.c} file. \CFA{} supports this pattern for generic types, and in tis instance the caller does not know the actual layout or size of the dynamic generic type, and only holds it by pointer. The \CFA{} translator automatically generates \emph{layout functions} for cases where the size, alignment, and offset array of a generic struct cannot be passed in to a function from that function's caller. 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 struct (un-@sized@ parameters are forbidden from the language from being used in a context which affects layout). 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@.
     319Though \CFA{} implements concrete generic types efficiently, it also has a fully general system for computing with dynamic generic types. 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. Dynamic generic structs have the same size and alignment parameter, and also an \emph{offset array} which contains the offsets of each member of the struct\footnote{Dynamic generic unions need no such offset array, as all members are at offset 0; the size and alignment parameters are still provided for dynamic unions, however.}. Access to members\footnote{The \lstinline@offsetof@ macro is implemented similarly.} of a dynamic generic struct is provided by adding the corresponding member of the offset array to the struct pointer at runtime, essentially moving a compile-time offset calculation to runtime where necessary.
     320
     321These offset arrays are statically generated where possible. 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 (that is, has a known layout) at any call-site, and the offset array is passed from the caller; 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. As an example, @p.second@ in the @value@ function above is implemented as @*(p + _offsetof_pair[1])@, where @p@ is a @void*@, and @_offsetof_pair@ is the offset array passed in to @value@ for @pair(const char*, T)@. The offset array @_offsetof_pair@ is generated at the call site as @size_t _offsetof_pair[] = { offsetof(_pair_conc1, first), offsetof(_pair_conc1, second) };@.
     322
     323In some cases the offset arrays cannot be statically generated. For instance, modularity is generally provided in C by including an opaque forward-declaration of a struct and associated accessor and mutator routines in a header file, with the actual implementations in a separately-compiled \texttt{.c} file. \CFA{} supports this pattern for generic types, and in this instance the caller does not know the actual layout or size of the dynamic generic type, and only holds it by pointer. The \CFA{} translator automatically generates \emph{layout functions} for cases where the size, alignment, and offset array of a generic struct cannot be passed in to a function from that function's caller. 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 struct (un-@sized@ parameters are forbidden from the language from being used in a context that affects layout). 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@.
    326324% \begin{lstlisting}
    327 % static inline void _layoutof_pair(size_t* _szeof_pair, size_t* _alignof_pair, size_t* _offsetof_pair, 
     325% static inline void _layoutof_pair(size_t* _szeof_pair, size_t* _alignof_pair, size_t* _offsetof_pair,
    328326%               size_t _szeof_R, size_t _alignof_R, size_t _szeof_S, size_t _alignof_S) {
    329327%     *_szeof_pair = 0; // default values
     
    334332%     *_szeof_pair += _szeof_R;
    335333%     if ( *_alignof_pair < _alignof_R ) *_alignof_pair = _alignof_R;
    336        
     334
    337335%       // padding, offset, size, and alignment of second field
    338336%     if ( *_szeof_pair & (_alignof_S - 1) )
     
    348346% \end{lstlisting}
    349347
    350 Layout functions also allow generic types to be used in a function definition without reflecting them in the function signature. For instance, a function that strips duplicate values from an unsorted @vector(T)@ would likely have a pointer to the vector as its only explicit parameter, but internally may use some sort of @set(T)@ to test for duplicate values. This function could acquire the layout for @set(T)@ by calling its layout function with the layout of @T@ implicitly passed into the function.
    351 
    352 Whether a type is concrete, dtype-static, or dynamic is decided based solely on the type parameters and @forall@ clause on the struct declaration. This allows opaque forward declarations of generic types like @forall(otype T) struct Box;@ -- like in C, all uses of @Box(T)@ can be in a separately compiled translation unit, and callers from other translation units will know the proper calling conventions to use. If the definition of a struct type was included in the determination of dynamic or concrete, some further types may be recognized as dtype-static (\eg, @forall(otype 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}.), but preserving separate compilation (and the associated C compatibility) in this way is judged to be an appropriate trade-off.
     348Layout functions also allow generic types to be used in a function definition without reflecting them in the function signature. For instance, a function that strips duplicate values from an unsorted @vector(T)@ would likely have a pointer to the vector as its only explicit parameter, but use some sort of @set(T)@ internally to test for duplicate values. This function could acquire the layout for @set(T)@ by calling its layout function with the layout of @T@ implicitly passed into the function.
     349
     350Whether a type is concrete, dtype-static, or dynamic is decided based solely on the type parameters and @forall@ clause on the struct declaration. This design allows opaque forward declarations of generic types like @forall(otype T) struct Box;@ -- like in C, all uses of @Box(T)@ can be in a separately compiled translation unit, and callers from other translation units know the proper calling conventions to use. If the definition of a struct type was included in the decision of whether a generic type is dynamic or concrete, some further types may be recognized as dtype-static (\eg{} @forall(otype 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}.), but preserving separate compilation (and the associated C compatibility) in the existing design is judged to be an appropriate trade-off.
    353351
    354352\subsection{Applications}
    355 
    356 The re-use of dtype-static struct instantiations enables some useful programming patterns at zero runtime cost. The most important such pattern is using @forall(dtype T) T*@ as a type-checked replacement for @void*@, as in this example, which takes a @qsort@ or @bsearch@-compatible comparison routine and creates a similar lexicographic comparison for pairs of pointers:
     353\label{sec:generic-apps}
     354
     355The reuse of dtype-static struct instantiations enables some useful programming patterns at zero runtime cost. The most important such pattern is using @forall(dtype T) T*@ as a type-checked replacement for @void*@, as in this example, which takes a @qsort@ or @bsearch@-compatible comparison routine and creates a similar lexicographic comparison for pairs of pointers:
    357356\begin{lstlisting}
    358357forall(dtype T)
     
    363362}
    364363\end{lstlisting}
    365 Since @pair(T*, T*)@ is a concrete type, there are no added implicit parameters to @lexcmp@, so the code generated by \CFA{} will be effectively identical to a version of this written in standard C using @void*@, yet the \CFA{} version will be type-checked to ensure that the fields of both pairs and the arguments to the comparison function match in type.
    366 
    367 Another useful pattern enabled by re-used dtype-static type instantiations is zero-cost ``tag'' structs. Sometimes a particular bit of information is only useful for type-checking, and can be omitted at runtime. Tag structs can be used to provide this information to the compiler without further runtime overhead, as in the following example:
     364Since @pair(T*, T*)@ is a concrete type, there are no added implicit parameters to @lexcmp@, so the code generated by \CFA{} is effectively identical to a version of this function written in standard C using @void*@, yet the \CFA{} version is type-checked to ensure that the fields of both pairs and the arguments to the comparison function match in type.
     365
     366Another useful pattern enabled by reused dtype-static type instantiations is zero-cost ``tag'' structs. Sometimes a particular bit of information is only useful for type-checking, and can be omitted at runtime. Tag structs can be used to provide this information to the compiler without further runtime overhead, as in the following example:
    368367\begin{lstlisting}
    369368forall(dtype Unit) struct scalar { unsigned long value; };
     
    384383marathon + swimming_pool; // ERROR -- caught by compiler
    385384\end{lstlisting}
    386 @scalar@ is a dtype-static type, so all uses of it will use a single struct definition, containing only a single @unsigned long@, and can share the same implementations of common routines like @?+?@ -- these implementations may even be separately compiled, unlike \CC{} template functions. However, the \CFA{} type-checker will ensure that matching types are used by all calls to @?+?@, preventing nonsensical computations like adding the length of a marathon to the volume of an olympic pool.
     385@scalar@ is a dtype-static type, so all uses of it use a single struct definition, containing only a single @unsigned long@, and can share the same implementations of common routines like @?+?@ -- these implementations may even be separately compiled, unlike \CC{} template functions. However, the \CFA{} type-checker ensures that matching types are used by all calls to @?+?@, preventing nonsensical computations like adding the length of a marathon to the volume of an olympic pool.
    387386
    388387\section{Tuples}
    389 
    390 The @pair(R, S)@ generic type used as an example in the previous section can be considered a special case of a more general \emph{tuple} data structure. The authors have implemented tuples in \CFA{} as an extension to C. The \CFA{} tuple design is particularly motivated by two use cases: \emph{multiple-return-value functions} and \emph{variadic functions}.
    391 
    392 In standard C, functions can return at most one value. This restriction results in code which emulates functions with multiple return values by \emph{aggregation} or by \emph{aliasing}. In the former situation, the function designer creates a record type that combines all of the return values into a single type. Of note, the designer must come up with a name for the return type and for each of its fields. Unnecessary naming is a common programming language issue, introducing verbosity and a complication of the user's mental model. As such, this technique is effective when used sparingly, but can quickly get out of hand if many functions need to return different combinations of types. In the latter approach, the designer simulates multiple return values by passing the additional return values as pointer parameters. The pointer parameters are assigned inside of the routine body to emulate a return. Notably, using this approach, the caller is directly responsible for allocating storage for the additional temporary return values. This complicates the call site with a sequence of variable declarations leading up to the call. Also, while a disciplined use of @const@ can give clues about whether a pointer parameter is going to be used as an out parameter, it is not immediately obvious from only the routine signature whether the callee expects such a parameter to be initialized before the call. Furthermore, while many C routines that accept pointers are designed so that it is safe to pass @NULL@ as a parameter, there are many C routines that are not null-safe. On a related note, C does not provide a standard mechanism to state that a parameter is going to be used as an additional return value, which makes the job of ensuring that a value is returned more difficult for the compiler.
    393 
    394 C does provide a mechanism for variadic functions through manipulation of @va_list@ objects, but it is notoriously not type-safe. A variadic function is one which contains at least one parameter, followed by @...@ as the last token in the parameter list. In particular, some form of \emph{argument descriptor} is needed to inform the function of the number of arguments and their types, commonly a format string or counter parameter. It is important to note that both of these mechanisms are inherently redundant, because they require the user to specify information that the compiler knows explicitly. This required repetition is error prone, because it is easy for the user to add or remove arguments without updating the argument descriptor. In addition, C requires the programmer to hard code all of the possible expected types. As a result, it is cumbersome to write a variadic function that is open to extension. For example, consider a simple function which sums $N$ @int@s:
     388\label{sec:tuples}
     389
     390The @pair(R, S)@ generic type used as an example in the previous section can be considered a special case of a more general \emph{tuple} data structure. The authors have implemented tuples in \CFA{}, with a design particularly motivated by two use cases: \emph{multiple-return-value functions} and \emph{variadic functions}.
     391
     392In standard C, functions can return at most one value. This restriction results in code that emulates functions with multiple return values by \emph{aggregation} or by \emph{aliasing}. In the former situation, the function designer creates a record type that combines all of the return values into a single type. Unfortunately, the designer must come up with a name for the return type and for each of its fields. Unnecessary naming is a common programming language issue, introducing verbosity and a complication of the user's mental model. As such, this technique is effective when used sparingly, but can quickly get out of hand if many functions need to return different combinations of types. In the latter approach, the designer simulates multiple return values by passing the additional return values as pointer parameters. The pointer parameters are assigned inside of the routine body to emulate a return. Using this approach, the caller is directly responsible for allocating storage for the additional temporary return values. This responsibility complicates the call site with a sequence of variable declarations leading up to the call. Also, while a disciplined use of @const@ can give clues about whether a pointer parameter is going to be used as an out parameter, it is not immediately obvious from only the routine signature whether the callee expects such a parameter to be initialized before the call. Furthermore, while many C routines that accept pointers are designed so that it is safe to pass @NULL@ as a parameter, there are many C routines that are not null-safe. On a related note, C does not provide a standard mechanism to state that a parameter is going to be used as an additional return value, which makes the job of ensuring that a value is returned more difficult for the compiler.
     393
     394C does provide a mechanism for variadic functions through manipulation of @va_list@ objects, but it is notoriously type-unsafe. A variadic function is one that contains at least one parameter, followed by @...@ as the last token in the parameter list. In particular, some form of \emph{argument descriptor} is needed to inform the function of the number of arguments and their types, commonly a format string or counter parameter. It is important to note that both of these mechanisms are inherently redundant, because they require the user to specify information that the compiler knows explicitly. This required repetition is error prone, because it is easy for the user to add or remove arguments without updating the argument descriptor. In addition, C requires the programmer to hard code all of the possible expected types. As a result, it is cumbersome to write a variadic function that is open to extension. For example, consider a simple function that sums $N$ @int@s:
    395395\begin{lstlisting}
    396396int sum(int N, ...) {
     
    405405  return ret;
    406406}
     407
    407408sum(3, 10, 20, 30);  // must keep initial counter argument in sync
    408409\end{lstlisting}
    409410
    410 The @va_list@ type is a special C data type that abstracts variadic argument manipulation. The @va_start@ macro initializes a @va_list@, given the last named parameter. Each use of the @va_arg@ macro allows access to the next variadic argument, given a type. Since the function signature does not provide any information on what types can be passed to a variadic function, the compiler does not perform any error checks on a variadic call. As such, it is possible to pass any value to the @sum@ function, including pointers, floating-point numbers, and structures. In the case where the provided type is not compatible with the argument's actual type after default argument promotions, or if too many arguments are accessed, the behaviour is undefined \citep{C11}. Furthermore, there is no way to perform the necessary error checks in the @sum@ function at run-time, since type information is not carried into the function body. Since they rely on programmer convention rather than compile-time checks, variadic functions are generally unsafe.
    411 
    412 In practice, compilers can provide warnings to help mitigate some of the problems. For example, GCC provides the @format@ attribute to specify that a function uses a format string, which allows the compiler to perform some checks related to the standard format specifiers. Unfortunately, this does not permit extensions to the format string syntax, so a programmer cannot extend the attribute to warn for mismatches with custom types.
     411The @va_list@ type is a special C data type that abstracts variadic argument manipulation. The @va_start@ macro initializes a @va_list@, given the last named parameter. Each use of the @va_arg@ macro allows access to the next variadic argument, given a type. Since the function signature does not provide any information on what types can be passed to a variadic function, the compiler does not perform any error checks on a variadic call. As such, it is possible to pass any value to the @sum@ function, including pointers, floating-point numbers, and structures. In the case where the provided type is not compatible with the argument's actual type after default argument promotions, or if too many arguments are accessed, the behaviour is undefined \citep{C11}. Furthermore, there is no way to perform the necessary error checks in the @sum@ function at run-time, since type information is not carried into the function body. Since they rely on programmer convention rather than compile-time checks, variadic functions are inherently unsafe.
     412
     413In practice, compilers can provide warnings to help mitigate some of the problems. For example, GCC provides the @format@ attribute to specify that a function uses a format string, which allows the compiler to perform some checks related to the standard format specifiers. Unfortunately, this attribute does not permit extensions to the format string syntax, so a programmer cannot extend it to warn for mismatches with custom types.
    413414
    414415\subsection{Tuple Expressions}
     
    432433[double, int] adi[10];
    433434\end{lstlisting}
    434 This examples declares a variable of type @[double, int]@, a variable of type pointer to @[double, int]@, and an array of ten @[double, int]@.
     435This example declares a variable of type @[double, int]@, a variable of type pointer to @[double, int]@, and an array of ten @[double, int]@.
    435436
    436437\subsection{Flattening and Restructuring}
     
    450451In \CFA{}, each of these calls is valid. In the call to @f@, @x@ is implicitly flattened so that the components of @x@ are passed as the two arguments to @f@. For the call to @g@, the values @y@ and @10@ are structured into a single argument of type @[int, int]@ to match the type of the parameter of @g@. Finally, in the call to @h@, @y@ is flattened to yield an argument list of length 3, of which the first component of @x@ is passed as the first parameter of @h@, and the second component of @x@ and @y@ are structured into the second argument of type @[int, int]@. The flexible structure of tuples permits a simple and expressive function call syntax to work seamlessly with both single- and multiple-return-value functions, and with any number of arguments of arbitrarily complex structure.
    451452
    452 In {K-W C} \citep{Buhr94a,Till89} there were 4 tuple coercions: opening, closing, flattening, and structuring. Opening coerces a tuple value into a tuple of values, while closing converts a tuple of values into a single tuple value. Flattening coerces a nested tuple into a flat tuple, i.e. it takes a tuple with tuple components and expands it into a tuple with only non-tuple components. Structuring moves in the opposite direction, i.e. it takes a flat tuple value and provides structure by introducing nested tuple components.
     453In {K-W C} \citep{Buhr94a,Till89}, a precursor to \CFA{}, there were 4 tuple coercions: opening, closing, flattening, and structuring. Opening coerces a tuple value into a tuple of values, while closing converts a tuple of values into a single tuple value. Flattening coerces a nested tuple into a flat tuple, \ie{} it takes a tuple with tuple components and expands it into a tuple with only non-tuple components. Structuring moves in the opposite direction, \ie{} it takes a flat tuple value and provides structure by introducing nested tuple components.
    453454
    454455In \CFA{}, the design has been simplified to require only the two conversions previously described, which trigger only in function call and return situations. Specifically, the expression resolution algorithm examines all of the possible alternatives for an expression to determine the best match. In resolving a function call expression, each combination of function value and list of argument alternatives is examined. Given a particular argument list and function value, the list of argument alternatives is flattened to produce a list of non-tuple valued expressions. Then the flattened list of expressions is compared with each value in the function's parameter list. If the parameter's type is not a tuple type, then the current argument value is unified with the parameter type, and on success the next argument and parameter are examined. If the parameter's type is a tuple type, then the structuring conversion takes effect, recursively applying the parameter matching algorithm using the tuple's component types as the parameter list types. Assuming a successful unification, eventually the algorithm gets to the end of the tuple type, which causes all of the matching expressions to be consumed and structured into a tuple expression. For example, in
     
    474475double z = [x, f()].0.1;  // access second component of first component of tuple expression
    475476\end{lstlisting}
    476 As seen above, tuple-index expressions can occur on any tuple-typed expression, including tuple-returning functions, square-bracketed tuple expressions, and other tuple-index expressions, provided the retrieved component is also a tuple. This feature was proposed for {K-W C}, a precursor of \CFA{}, but never implemented \citep[p.~45]{Till89}.
     477As seen above, tuple-index expressions can occur on any tuple-typed expression, including tuple-returning functions, square-bracketed tuple expressions, and other tuple-index expressions, provided the retrieved component is also a tuple. This feature was proposed for {K-W C}, but never implemented \citep[p.~45]{Till89}.
    477478
    478479It is possible to access multiple fields from a single expression using a \emph{member-access tuple expression}. The result is a single tuple expression whose type is the tuple of the types of the members. For example,
     
    481482s.[x, y, z];
    482483\end{lstlisting}
    483 Here, the type of @s.[x, y, z]@ is @[int, double, char *]@. A member tuple expression has the form @a.[x, y, z];@ where @a@ is an expression with type @T@, where @T@ supports member access expressions, and @x, y, z@ are all members of @T@ with types @T$_x$@, @T$_y$@, and @T$_z$@ respectively. Then the type of @a.[x, y, z]@ is @[T_x, T_y, T_z]@.
    484 
    485 Since tuple index expressions are a form of member-access expression, it is possible to use tuple-index expressions in conjunction with member tuple expressions to manually restructure a tuple (e.g. rearrange components, drop components, duplicate components, etc.):
     484Here, the type of @s.[x, y, z]@ is @[int, double, char *]@. A member tuple expression has the form @a.[x, y, z];@ where @a@ is an expression with type @T@, where @T@ supports member access expressions, and @x, y, z@ are all members of @T@ with types @T$_x$@, @T$_y$@, and @T$_z$@ respectively. Then the type of @a.[x, y, z]@ is @[T$_x$, T$_y$, T$_z$]@.
     485
     486Since tuple index expressions are a form of member-access expression, it is possible to use tuple-index expressions in conjunction with member tuple expressions to manually restructure a tuple (\eg{} rearrange components, drop components, duplicate components, etc.):
    486487\begin{lstlisting}
    487488[int, int, long, double] x;
     
    514515z = [x, y];     // multiple assignment
    515516\end{lstlisting}
    516 Let $L_i$ for $i$ in $[0, n)$ represent each component of the flattened left side, $R_i$ represent each component of the flattened right side of a multiple assignment, and $R$ represent the right side of a mass assignment.
     517Let $L_i$ for $i$ in $[0, n)$ represent each component of the flattened left-hand side, $R_i$ represent each component of the flattened right-hand side of a multiple assignment, and $R$ represent the right-hand side of a mass assignment.
    517518
    518519For a multiple assignment to be valid, both tuples must have the same number of elements when flattened. Multiple assignment assigns $R_i$ to $L_i$ for each $i$.
    519520That is, @?=?(&$L_i$, $R_i$)@ must be a well-typed expression. In the previous example, @[x, y] = z@, @z@ is flattened into @z.0, z.1@, and the assignments @x = z.0@ and @y = z.1@ are executed.
    520521
    521 A mass assignment assigns the value $R$ to each $L_i$. For a mass assignment to be valid, @?=?(&$L_i$, $R$)@ must be a well-typed expression. This differs from C cascading assignment (e.g. @a=b=c@) in that conversions are applied to $R$ in each individual assignment, which prevents data loss from the chain of conversions that can happen during a cascading assignment. For example, @[y, x] = 3.14@ performs the assignments @y = 3.14@ and @x = 3.14@, which results in the value @3.14@ in @y@ and the value @3@ in @x@. On the other hand, the C cascading assignment @y = x = 3.14@ performs the assignments @x = 3.14@ and @y = x@, which results in the value @3@ in @x@, and as a result the value @3@ in @y@ as well.
     522A mass assignment assigns the value $R$ to each $L_i$. For a mass assignment to be valid, @?=?(&$L_i$, $R$)@ must be a well-typed expression. This rule differs from C cascading assignment (\eg{} @a=b=c@) in that conversions are applied to $R$ in each individual assignment, which prevents data loss from the chain of conversions that can happen during a cascading assignment. For example, @[y, x] = 3.14@ performs the assignments @y = 3.14@ and @x = 3.14@, which results in the value @3.14@ in @y@ and the value @3@ in @x@. On the other hand, the C cascading assignment @y = x = 3.14@ performs the assignments @x = 3.14@ and @y = x@, which results in the value @3@ in @x@, and as a result the value @3@ in @y@ as well.
    522523
    523524Both kinds of tuple assignment have parallel semantics, such that each value on the left side and right side is evaluated \emph{before} any assignments occur. As a result, it is possible to swap the values in two variables without explicitly creating any temporary variables or calling a function:
     
    528529After executing this code, @x@ has the value @20@ and @y@ has the value @10@.
    529530
    530 In \CFA{}, tuple assignment is an expression where the result type is the type of the left-hand side of the assignment, as in normal assignment. That is, a tuple assignment produces the value of the left-hand side after assignment. These semantics allow cascading tuple assignment to work out naturally in any context where a tuple is permitted. These semantics are a change from the original tuple design in {K-W C} \citep{Till89}, wherein tuple assignment was a statement that allows cascading assignments as a special case. This decision wa made in an attempt to fix what was seen as a problem with assignment, wherein it can be used in many different locations, such as in function-call argument position. While permitting assignment as an expression does introduce the potential for subtle complexities, it is impossible to remove assignment expressions from \CFA{} without affecting backwards compatibility with C. Furthermore, there are situations where permitting assignment as an expression improves readability by keeping code succinct and reducing repetition, and complicating the definition of tuple assignment puts a greater cognitive burden on the user. In another language, tuple assignment as a statement could be reasonable, but it would be inconsistent for tuple assignment to be the only kind of assignment in \CFA{} that is not an expression.
     531Tuple assignment is an expression where the result type is the type of the left-hand side of the assignment, just like all other assignment expressions in C. This definition allows cascading tuple assignment and use of tuple assignment in other expression contexts, an occasionally useful idiom to keep code succinct and reduce repetition.
     532% In \CFA{}, tuple assignment is an expression where the result type is the type of the left-hand side of the assignment, as in normal assignment. That is, a tuple assignment produces the value of the left-hand side after assignment. These semantics allow cascading tuple assignment to work out naturally in any context where a tuple is permitted. These semantics are a change from the original tuple design in {K-W C} \citep{Till89}, wherein tuple assignment was a statement that allows cascading assignments as a special case. This decision was made in an attempt to fix what was seen as a problem with assignment, wherein it can be used in many different locations, such as in function-call argument position. While permitting assignment as an expression does introduce the potential for subtle complexities, it is impossible to remove assignment expressions from \CFA{} without affecting backwards compatibility with C. Furthermore, there are situations where permitting assignment as an expression improves readability by keeping code succinct and reducing repetition, and complicating the definition of tuple assignment puts a greater cognitive burden on the user. In another language, tuple assignment as a statement could be reasonable, but it would be inconsistent for tuple assignment to be the only kind of assignment in \CFA{} that is not an expression.
    531533
    532534\subsection{Casting}
     
    548550(void)f();  // (1)
    549551(int)g();  // (2)
    550 
    551 struct A { int x; };
    552 (struct A)f();  // (3)
    553 \end{lstlisting}
    554 In C, (1) is a valid cast, which calls @f@ and discards its result. On the other hand, (2) is invalid, because @g@ does not produce a result, so requesting an @int@ to materialize from nothing is nonsensical. Finally, (3) is also invalid, because in C casts only provide conversion between scalar types \cite{C11}. For consistency, this implies that any case wherein the number of components increases as a result of the cast is invalid, while casts which have the same or fewer number of components may be valid.
    555 
    556 Formally, a cast to tuple type is valid when $T_n \leq S_m$, where $T_n$ is the number of components in the target type and $S_m$ is the number of components in the source type, and for each $i$ in $[0, n)$, $S_i$ can be cast to $T_i$. Excess elements ($S_j$ for all $j$ in $[n, m)$) are evaluated, but their values are discarded so that they are not included in the result expression. This discarding naturally follows the way that a cast to @void@ works in C.
     552\end{lstlisting}
     553In C, (1) is a valid cast, which calls @f@ and discards its result. On the other hand, (2) is invalid, because @g@ does not produce a result, so requesting an @int@ to materialize from nothing is nonsensical. Generalizing these principles, any cast wherein the number of components increases as a result of the cast is invalid, while casts that have the same or fewer number of components may be valid.
     554
     555Formally, a cast to tuple type is valid when $T_n \leq S_m$, where $T_n$ is the number of components in the target type and $S_m$ is the number of components in the source type, and for each $i$ in $[0, n)$, $S_i$ can be cast to $T_i$. Excess elements ($S_j$ for all $j$ in $[n, m)$) are evaluated, but their values are discarded so that they are not included in the result expression. This approach follows naturally from the way that a cast to @void@ works in C.
    557556
    558557For example, in
     
    568567\end{lstlisting}
    569568
    570 (1) discards the last element of the return value and converts the second element to @double@. Since @int@ is effectively a 1-element tuple, (2) discards the second component of the second element of the return value of @g@. If @g@ is free of side effects, this is equivalent to @[(int)(g().0), (int)(g().1.0), (int)(g().2)]@.
     569(1) discards the last element of the return value and converts the second element to @double@. Since @int@ is effectively a 1-element tuple, (2) discards the second component of the second element of the return value of @g@. If @g@ is free of side effects, this expression is equivalent to @[(int)(g().0), (int)(g().1.0), (int)(g().2)]@.
    571570Since @void@ is effectively a 0-element tuple, (3) discards the first and third return values, which is effectively equivalent to @[(int)(g().1.0), (int)(g().1.1)]@).
    572571
     
    582581f([5, "hello"]);
    583582\end{lstlisting}
    584 In this example, @[5, "hello"]@ is flattened, so that the argument list appears as @5, "hello"@. The argument matching algorithm binds @T@ to @int@ and @U@ to @const char@, and calls the function as normal.
    585 
    586 Tuples, however, can contain polymorphic components. For example, a plus operator can be written to add two triples of a type together.
     583In this example, @[5, "hello"]@ is flattened, so that the argument list appears as @5, "hello"@. The argument matching algorithm binds @T@ to @int@ and @U@ to @const char*@, and calls the function as normal.
     584
     585Tuples, however, may contain polymorphic components. For example, a plus operator can be written to add two triples of a type together.
    587586\begin{lstlisting}
    588587forall(otype T | { T ?+?(T, T); })
     
    595594\end{lstlisting}
    596595
    597 Flattening and restructuring conversions are also applied to tuple types in polymorphic type assertions. Previously in \CFA{}, it has been assumed that assertion arguments must match the parameter type exactly, modulo polymorphic specialization (\ie{}, no implicit conversions are applied to assertion arguments). In the example below:
     596Flattening and restructuring conversions are also applied to tuple types in polymorphic type assertions. Previously in \CFA{}, it has been assumed that assertion arguments must match the parameter type exactly, modulo polymorphic specialization (\ie{} no implicit conversions are applied to assertion arguments). In the example below:
    598597\begin{lstlisting}
    599598int f([int, double], double);
     
    604603If assertion arguments must match exactly, then the call to @g@ cannot be resolved, since the expected type of @f@ is flat, while the only @f@ in scope requires a tuple type. Since tuples are fluid, this requirement reduces the usability of tuples in polymorphic code. To ease this pain point, function parameter and return lists are flattened for the purposes of type unification, which allows the previous example to pass expression resolution.
    605604
    606 This relaxation is made possible by extending the existing thunk generation scheme, as described by Bilson \citet{Bilson03}. Now, whenever a candidate's parameter structure does not exactly match the formal parameter's structure, a thunk is generated to specialize calls to the actual function:
     605This relaxation is made possible by extending the existing thunk generation scheme, as described by \citet{Bilson03}. Now, whenever a candidate's parameter structure does not exactly match the formal parameter's structure, a thunk is generated to specialize calls to the actual function:
    607606\begin{lstlisting}
    608607int _thunk(int _p0, double _p1, double _p2) {
     
    610609}
    611610\end{lstlisting}
    612 Essentially, this provides flattening and structuring conversions to inferred functions, improving the compatibility of tuples and polymorphism.
     611Essentially, this thunk provides flattening and structuring conversions to inferred functions, improving the compatibility of tuples and polymorphism. These thunks take advantage of GCC C nested functions to produce closures that have the usual function pointer signature.
    613612
    614613\subsection{Variadic Tuples}
    615614
    616 To define variadic functions, \CFA{} adds a new kind of type parameter, @ttype@. Matching against a @ttype@ parameter consumes all remaining argument components and packages them into a tuple, binding to the resulting tuple of types. In a given parameter list, there should be at most one @ttype@ parameter that must occur last, otherwise the call can never resolve, given the previous rule. This idea essentially matches normal variadic semantics, with a strong feeling of similarity to \CCeleven{} variadic templates. As such, @ttype@ variables will also be referred to as \emph{argument packs}.
     615To define variadic functions, \CFA{} adds a new kind of type parameter, @ttype@. Matching against a @ttype@ (``tuple type'') parameter consumes all remaining argument components and packages them into a tuple, binding to the resulting tuple of types. In a given parameter list, there should be at most one @ttype@ parameter that must occur last, otherwise the call can never resolve, given the previous rule. This idea essentially matches normal variadic semantics, with a strong feeling of similarity to \CCeleven{} variadic templates. As such, @ttype@ variables are also referred to as \emph{argument} or \emph{parameter packs} in this paper.
    617616
    618617Like variadic templates, the main way to manipulate @ttype@ polymorphic functions is through recursion. Since nothing is known about a parameter pack by default, assertion parameters are key to doing anything meaningful. Unlike variadic templates, @ttype@ polymorphic functions can be separately compiled.
    619618
    620 For example, the C @sum@ function at the beginning of this section could be written using @ttype@ as:
     619For example, the C @sum@ function at the beginning of Section~\ref{sec:tuples} could be written using @ttype@ as:
    621620\begin{lstlisting}
    622621int sum(){ return 0; }        // (0)
     
    629628Since (0) does not accept any arguments, it is not a valid candidate function for the call @sum(10, 20, 30)@.
    630629In order to call (1), @10@ is matched with @x@, and the argument resolution moves on to the argument pack @rest@, which consumes the remainder of the argument list and @Params@ is bound to @[20, 30]@.
    631 In order to finish the resolution of @sum@, an assertion parameter which matches @int sum(int, int)@ is required.
    632 Like in the previous iteration, (0) is not a valid candiate, so (1) is examined with @Params@ bound to @[int]@, requiring the assertion @int sum(int)@.
     630In order to finish the resolution of @sum@, an assertion parameter that matches @int sum(int, int)@ is required.
     631Like in the previous iteration, (0) is not a valid candidate, so (1) is examined with @Params@ bound to @[int]@, requiring the assertion @int sum(int)@.
    633632Next, (0) fails, and to satisfy (1) @Params@ is bound to @[]@, requiring an assertion @int sum()@.
    634633Finally, (0) matches and (1) fails, which terminates the recursion.
    635 Effectively, this traces as @sum(10, 20, 30)@ $\rightarrow$ @10+sum(20, 30)@ $\rightarrow$ @10+(20+sum(30))@ $\rightarrow$ @10+(20+(30+sum()))@ $\rightarrow$ @10+(20+(30+0))@.
    636 
    637 A point of note is that this version does not require any form of argument descriptor, since the \CFA{} type system keeps track of all of these details. It might be reasonable to take the @sum@ function a step further to enforce a minimum number of arguments, which could be done simply:
     634Effectively, this algorithm traces as @sum(10, 20, 30)@ $\rightarrow$ @10+sum(20, 30)@ $\rightarrow$ @10+(20+sum(30))@ $\rightarrow$ @10+(20+(30+sum()))@ $\rightarrow$ @10+(20+(30+0))@.
     635
     636As a point of note, this version does not require any form of argument descriptor, since the \CFA{} type system keeps track of all of these details. It might be reasonable to take the @sum@ function a step further to enforce a minimum number of arguments:
    638637\begin{lstlisting}
    639638int sum(int x, int y){
     
    644643  return sum(x+y, rest);
    645644}
    646 sum(10, 20, 30);
    647645\end{lstlisting}
    648646
     
    662660  return sum(x+y, rest);
    663661}
    664 sum(3, 10, 20, 30);
    665 \end{lstlisting}
    666 Unlike C, it is not necessary to hard code the expected type. This is naturally open to extension, in that any user-defined type with a @?+?@ operator is automatically able to be used with the @sum@ function. That is to say, the programmer who writes @sum@ does not need full program knowledge of every possible data type, unlike what is necessary to write an equivalent function using the standard C mechanisms. Summing arbitrary heterogeneous lists is possible with similar code by adding the appropriate type variables and addition operators.
    667 
    668 It is possible to write a type-safe variadic print routine, which can replace @printf@
     662\end{lstlisting}
     663Unlike C, it is not necessary to hard code the expected type. This code is naturally open to extension, in that any user-defined type with a @?+?@ operator is automatically able to be used with the @sum@ function. That is to say, the programmer who writes @sum@ does not need full program knowledge of every possible data type, unlike what is necessary to write an equivalent function using the standard C mechanisms. Summing arbitrary heterogeneous lists is possible with similar code by adding the appropriate type variables and addition operators.
     664
     665It is also possible to write a type-safe variadic print routine which can replace @printf@:
    669666\begin{lstlisting}
    670667struct S { int x, y; };
     
    678675void print(int x) { printf("%d", x);  }
    679676void print(S s) { print("{ ", s.x, ",", s.y, " }"); }
     677
    680678print("s = ", (S){ 1, 2 }, "\n");
    681679\end{lstlisting}
     
    692690  return ((T*)malloc( sizeof(T) )){ p }; // construct into result of malloc
    693691}
     692
    694693Pair(int, char) * x = new(42, '!');
    695694\end{lstlisting}
    696 The @new@ function provides the combination of type-safe @malloc@ with a constructor call, so that it becomes impossible to forget to construct dynamically allocated objects. This provides the type-safety of @new@ in \CC{}, without the need to specify the allocated type, thanks to return-type inference.
    697 
    698 In the call to @new@, @Pair(double, char)@ is selected to match @T@, and @Params@ is expanded to match @[double, char]@. To satisfy the assertion, a constructor with an interface compatible with @void ?{}(Pair(int, char) *, int, char)@ must exist in the current scope, which (1) may be specialized to match.
     695The @new@ function provides the combination of type-safe @malloc@ with a constructor call, so that it becomes impossible to forget to construct dynamically allocated objects. This function provides the type-safety of @new@ in \CC{}, without the need to specify the allocated type again, thanks to return-type inference.
     696
     697In the call to @new@, @Pair(double, char)@ is selected to match @T@, and @Params@ is expanded to match @[double, char]@. The constructor (1) may be specialized to  satisfy the assertion for a constructor with an interface compatible with @void ?{}(Pair(int, char) *, int, char)@.
    699698
    700699\TODO{} Check if we actually can use ttype parameters on generic types (if they set the complete flag, it should work, or nearly so).
     
    716715  T1 field_1;
    717716};
    718 _tuple2_(int, int) f() {
    719   _tuple2_(double, double) x;
     717_tuple2(int, int) f() {
     718  _tuple2(double, double) x;
    720719  forall(dtype T0, dtype T1, dtype T2 | sized(T0) | sized(T1) | sized(T2))
    721720  struct _tuple3 {  // generated before the first 3-tuple
     
    734733Becomes:
    735734\begin{lstlisting}
    736 (_tuple3_(int, char, double)){ 5, 'x', 1.24 };
     735(_tuple3(int, char, double)){ 5, 'x', 1.24 };
    737736\end{lstlisting}
    738737
     
    748747Is transformed into:
    749748\begin{lstlisting}
    750 void f(int, _tuple2_(double, char));
    751 _tuple2_(int, double) x;
     749void f(int, _tuple2(double, char));
     750_tuple2(int, double) x;
    752751
    753752x.field_0+x.field_1;
     
    755754f(x.field_0, (_tuple2){ x.field_1, 'z' });
    756755\end{lstlisting}
    757 Note that due to flattening, @x@ used in the argument position is converted into the list of its fields. In the call to @f@, a the second and third argument components are structured into a tuple argument. Similarly, tuple member expressions are recursively expanded into a list of member access expressions.
    758 
    759 Expressions which may contain side effects are made into \emph{unique expressions} before being expanded by the flattening conversion. Each unique expression is assigned an identifier and is guaranteed to be executed exactly once:
     756Note that due to flattening, @x@ used in the argument position is converted into the list of its fields. In the call to @f@, the second and third argument components are structured into a tuple argument. Similarly, tuple member expressions are recursively expanded into a list of member access expressions.
     757
     758Expressions that may contain side effects are made into \emph{unique expressions} before being expanded by the flattening conversion. Each unique expression is assigned an identifier and is guaranteed to be executed exactly once:
    760759\begin{lstlisting}
    761760void g(int, double);
     
    763762g(h());
    764763\end{lstlisting}
    765 Interally, this is converted to two variables and an expression:
     764Internally, this expression is converted to two variables and an expression:
    766765\begin{lstlisting}
    767766void g(int, double);
     
    775774);
    776775\end{lstlisting}
    777 Since argument evaluation order is not specified by the C programming language, this scheme is built to work regardless of evaluation order. The first time a unique expression is executed, the actual expression is evaluated and the accompanying boolean is true to true. Every subsequent evaluation of the unique expression then results in an access to the stored result of the actual expression. Tuple member expressions also take advantage of unique expressions in the case of possible impurity.
    778 
    779 Currently, the \CFA{} translator has a very broad, imprecise definition of impurity, where any function call is assumed to be impure. This notion could be made more precise for certain intrinsic, autogenerated, and builtin functions, and could analyze function bodies when they are available to recursively detect impurity, to eliminate some unique expressions.
    780 
    781 The various kinds of tuple assignment, constructors, and destructors generate GNU C statement expressions. A variable is generated to store the value produced by a statement expression, since its fields may need to be constructed with a non-trivial constructor and it may need to be referred to multiple time, \eg{} in a unique expression. The use of statement expressions allows the translator to arbitrarily generate additional temporary variables as needed, but binds the implementation to a non-standard extension of the C language. However, there are other places where the \CFA{} translator makes use of GNU C extensions, such as its use of nested functions, so this is not a new restriction.
    782 
    783 Type assertions in \CFA{} generally require exact matching of parameter and return types, with no implicit conversions allowed. Tuple flattening and restructuring is an exception to this, however, allowing functions to match assertions without regard to the presence of tuples; this is particularly useful for structuring trailing arguments to match a @ttype@ parameter or flattening assertions based on @ttype@ type variables to match programmer-defined functions. This relaxation is made possible by extending the existing thunk generation scheme, as described by Bilson \citet{Bilson03}. Whenever a candidate's parameter structure does not exactly match the formal parameter's structure, a thunk is generated to specialize calls to the actual function, as in this conversion from a function @f@ with signature @int (*)(int, char, char)@ to another with signature @int (*)([int, char], char)@:
    784 \begin{lstlisting}
    785 int _thunk(int _p0, char _p1, char _p2) {
    786   return f([_p0, _p1], _p2);
    787 }
    788 \end{lstlisting}
    789 These thunks take advantage of GCC C nested functions to produce closures that have the usual function pointer signature.
     776Since argument evaluation order is not specified by the C programming language, this scheme is built to work regardless of evaluation order. The first time a unique expression is executed, the actual expression is evaluated and the accompanying boolean is set to true. Every subsequent evaluation of the unique expression then results in an access to the stored result of the actual expression. Tuple member expressions also take advantage of unique expressions in the case of possible impurity.
     777
     778Currently, the \CFA{} translator has a very broad, imprecise definition of impurity, where any function call is assumed to be impure. This notion could be made more precise for certain intrinsic, auto-generated, and builtin functions, and could analyze function bodies when they are available to recursively detect impurity, to eliminate some unique expressions.
     779
     780The various kinds of tuple assignment, constructors, and destructors generate GNU C statement expressions. A variable is generated to store the value produced by a statement expression, since its fields may need to be constructed with a non-trivial constructor and it may need to be referred to multiple time, \eg{} in a unique expression. The use of statement expressions allows the translator to arbitrarily generate additional temporary variables as needed, but binds the implementation to a non-standard extension of the C language. However, there are other places where the \CFA{} translator makes use of GNU C extensions, such as its use of nested functions, so this restriction is not new.
    790781
    791782\section{Related Work}
    792783
    793 \TODO{} Talk about \CC{}, Cyclone, maybe D, Rust, \etc{}
    794 
    795 A major difference between the approaches of \CC{} and \CFA{} to polymorphism is that the set of assumed properties for a type is \emph{explicit} in \CFA{}. One of the major limiting factors of \CC{}'s approach is that templates cannot be separately compiled. In contrast, the explicit nature of assertions allows \CFA{}'s polymorphic functions to be separately compiled.
     784\CC{} is the existing language it is most natural to compare \CFA{} to, as they are both more modern extensions to C with backwards source compatibility. The most fundamental difference in approach between \CC{} and \CFA{} is their approach to this C compatibility. \CC{} does provide fairly strong source backwards compatibility with C, but is a dramatically more complex language than C, and imposes a steep learning curve to use many of its extension features. For instance, in a break from general C practice, template code is typically written in header files, with a variety of subtle restrictions implied on its use by this choice, while the other polymorphism mechanism made available by \CC{}, class inheritance, requires programmers to learn an entirely new object-oriented programming paradigm; the interaction between templates and inheritance is also quite complex. \CFA{}, by contrast, has a single facility for polymorphic code, one which supports separate compilation and the existing procedural paradigm of C code. A major difference between the approaches of \CC{} and \CFA{} to polymorphism is that the set of assumed properties for a type is \emph{explicit} in \CFA{}. One of the major limiting factors of \CC{}'s approach is that templates cannot be separately compiled, and, until concepts \citep{C++Concepts} are standardized (currently anticipated for \CCtwenty{}), \CC{} provides no way to specify the requirements of a generic function in code beyond compilation errors for template expansion failures. By contrast, the explicit nature of assertions in \CFA{} allows polymorphic functions to be separately compiled, and for their requirements to be checked by the compiler; similarly, \CFA{} generic types may be opaque, unlike \CC{} template classes.
     785
     786Cyclone also provides capabilities for polymorphic functions and existential types \citep{Gro06}, similar in concept to \CFA{}'s @forall@ functions and generic types. Cyclone existential types can include function pointers in a construct similar to a virtual function table, but these pointers must be explicitly initialized at some point in the code, a tedious and potentially error-prone process. Furthermore, Cyclone's polymorphic functions and types are restricted in that they may only abstract over types with the same layout and calling convention as @void*@, in practice only pointer types and @int@ - in \CFA{} terms, all Cyclone polymorphism must be dtype-static. This design provides the efficiency benefits discussed in Section~\ref{sec:generic-apps} for dtype-static polymorphism, but is more restrictive than \CFA{}'s more general model.
     787
     788Go and Rust are both modern, compiled languages with abstraction features similar to \CFA{} traits, \emph{interfaces} in Go and \emph{traits} in Rust. However, both languages represent dramatic departures from C in terms of language model, and neither has the same level of compatibility with C as \CFA{}. Go is a garbage-collected language, imposing the associated runtime overhead, and complicating foreign-function calls with the necessity of accounting for data transfer between the managed Go runtime and the unmanaged C runtime. Furthermore, while generic types and functions are available in Go, they are limited to a small fixed set provided by the compiler, with no language facility to define more. Rust is not garbage-collected, and thus has a lighter-weight runtime that is more easily interoperable with C. It also possesses much more powerful abstraction capabilities for writing generic code than Go. On the other hand, Rust's borrow-checker, while it does provide strong safety guarantees, is complex and difficult to learn, and imposes a distinctly idiomatic programming style on Rust. \CFA{}, with its more modest safety features, is significantly easier to port C code to, while maintaining the idiomatic style of the original source.
    796789
    797790\section{Conclusion \& Future Work}
    798791
    799 In conclusion, the authors' design for generic types and tuples imposes minimal runtime overhead while still supporting a full range of C features, including separately-compiled modules. There is ongoing work on a wide range of \CFA{} feature extensions, including reference types, exceptions, and concurent programming primitives. In addition to this work, there are some interesting future directions the polymorphism design could take. Notably, \CC{} template functions trade compile time and code bloat for optimal runtime of individual instantiations of polymorphic functions. \CFA{} polymorphic functions, by contrast, use an approach which is essentially dynamic virtual dispatch. The runtime overhead of this approach is low, but not as low as \CC{} template functions, and it may be beneficial to provide a mechanism for particularly performance-sensitive code to close this gap. Further research is needed, but two promising approaches are to allow an annotation on polymorphic function call sites that tells the translator to create a template-specialization of the function (provided the code is visible in the current translation unit) or placing an annotation on polymorphic function definitions that instantiates a version of the polymorphic function specialized to some set of types. These approaches are not mutually exclusive, and would allow these performance optimizations to be applied only where most useful to increase performance, without suffering the code bloat or loss of generality of a template expansion approach where it is unneccessary.
     792In conclusion, the authors' design for generic types and tuples imposes minimal runtime overhead while still supporting a full range of C features, including separately-compiled modules. There is ongoing work on a wide range of \CFA{} feature extensions, including reference types, exceptions, and concurrent programming primitives. In addition to this work, there are some interesting future directions the polymorphism design could take. Notably, \CC{} template functions trade compile time and code bloat for optimal runtime of individual instantiations of polymorphic functions. \CFA{} polymorphic functions, by contrast, use an approach that is essentially dynamic virtual dispatch. The runtime overhead of this approach is low, but not as low as \CC{} template functions, and it may be beneficial to provide a mechanism for particularly performance-sensitive code to close this gap. Further research is needed, but two promising approaches are to allow an annotation on polymorphic function call sites that tells the translator to create a template-specialization of the function (provided the code is visible in the current translation unit) or placing an annotation on polymorphic function definitions that instantiates a version of the polymorphic function specialized to some set of types. These approaches are not mutually exclusive, and would allow these performance optimizations to be applied only where most useful to increase performance, without suffering the code bloat or loss of generality of a template expansion approach where it is unnecessary.
     793
     794\begin{acks}
     795This work is supported in part by a corporate partnership with \grantsponsor{Huawei}{Huawei Ltd.}{http://www.huawei.com}\ and the first author's \grantsponsor{NSERC-PGS}{NSERC PGS D}{http://www.nserc-crsng.gc.ca/Students-Etudiants/PG-CS/BellandPostgrad-BelletSuperieures_eng.asp} scholarship.
     796\end{acks}
    800797
    801798\bibliographystyle{ACM-Reference-Format}
  • doc/rob_thesis/ctordtor.tex

    r690f13c r72dc82a  
    135135%   at the global scope (which is likely the most common case)
    136136% * [9]
    137 
    138 % Move semantics
    139 % * <ongoing discussion about this. this will be filled in
    140 %    once we come to a consensus>
    141137
    142138% Changes to polymorphic type classes
  • doc/rob_thesis/tuples.tex

    r690f13c r72dc82a  
    615615\end{cfacode}
    616616Note that due to flattening, @x@ used in the argument position is converted into the list of its fields.
    617 In the call to @f@, a the second and third argument components are structured into a tuple argument.
     617In the call to @f@, the second and third argument components are structured into a tuple argument.
    618618
    619619Expressions which may contain side effects are made into \emph{unique expressions} before being expanded by the flattening conversion.
     
    643643\end{cfacode}
    644644Since argument evaluation order is not specified by the C programming language, this scheme is built to work regardless of evaluation order.
    645 The first time a unique expression is executed, the actual expression is evaluated and the accompanying boolean is true to true.
     645The first time a unique expression is executed, the actual expression is evaluated and the accompanying boolean is set to true.
    646646Every subsequent evaluation of the unique expression then results in an access to the stored result of the actual expression.
    647647
     
    12991299Thunks 0 through 3 provide wrappers for the @otype@ parameters for @const char *@, while @_thunk4@ translates a call to @print([int, const char *])@ into a call to @print_variadic(int, [const char *])@.
    13001300This all builds to a call to @print_variadic@, with the appropriate copy construction of the tuple argument.
     1301
     1302\section{Future Work}
  • src/CodeGen/CodeGenerator.cc

    r690f13c r72dc82a  
    1010// Created On       : Mon May 18 07:44:20 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Fri Mar 17 09:06:01 2017
    13 // Update Count     : 481
     12// Last Modified On : Thu Mar 30 16:38:01 2017
     13// Update Count     : 482
    1414//
    1515
     
    674674
    675675        void CodeGenerator::visit( CompoundLiteralExpr *compLitExpr ) {
    676                 assert( compLitExpr->get_type() && dynamic_cast< ListInit * > ( compLitExpr->get_initializer() ) );
    677                 output << "(" << genType( compLitExpr->get_type(), "", pretty ) << ")";
     676                assert( compLitExpr->get_result() && dynamic_cast< ListInit * > ( compLitExpr->get_initializer() ) );
     677                output << "(" << genType( compLitExpr->get_result(), "", pretty ) << ")";
    678678                compLitExpr->get_initializer()->accept( *this );
    679679        }
  • src/InitTweak/FixInit.cc

    r690f13c r72dc82a  
    738738                                                stmtsToAddAfter.push_back( ifStmt );
    739739
    740                                                 if ( ctorInit->get_dtor() ) {
     740                                                Statement * dtor = ctorInit->get_dtor();
     741                                                objDecl->set_init( NULL );
     742                                                ctorInit->set_ctor( NULL );
     743                                                ctorInit->set_dtor( nullptr );
     744                                                if ( dtor ) {
    741745                                                        // if the object has a non-trivial destructor, have to
    742746                                                        // hoist it and the object into the global space and
    743747                                                        // call the destructor function with atexit.
    744748
    745                                                         Statement * dtorStmt = ctorInit->get_dtor()->clone();
     749                                                        Statement * dtorStmt = dtor->clone();
    746750
    747751                                                        // void __objName_dtor_atexitN(...) {...}
     
    772776                                                        objDecl->set_mangleName( SymTab::Mangler::mangle( objDecl ) );
    773777
    774                                                         objDecl->set_init( NULL );
    775                                                         ctorInit->set_ctor( NULL );
    776                                                         delete ctorInit;
    777 
    778778                                                        // xxx - temporary hack: need to return a declaration, but want to hoist the current object out of this scope
    779779                                                        // create a new object which is never used
    780780                                                        static UniqueName dummyNamer( "_dummy" );
    781781                                                        ObjectDecl * dummy = new ObjectDecl( dummyNamer.newName(), Type::StorageClasses( Type::Static ), LinkageSpec::Cforall, 0, new PointerType( Type::Qualifiers(), new VoidType( Type::Qualifiers() ) ), 0, std::list< Attribute * >{ new Attribute("unused") } );
     782                                                        delete ctorInit;
    782783                                                        return dummy;
    783784                                                }
  • src/InitTweak/GenInit.cc

    r690f13c r72dc82a  
    294294                handleDWT( objDecl );
    295295                // hands off if @=, extern, builtin, etc.
    296                 // if global but initializer is not constexpr, always try to construct, since this is not legal C
    297                 if ( ( tryConstruct( objDecl ) && isManaged( objDecl ) ) || (! inFunction && ! isConstExpr( objDecl->get_init() ) ) ) {
     296                // even if unmanaged, try to construct global or static if initializer is not constexpr, since this is not legal C
     297                if ( tryConstruct( objDecl ) && ( isManaged( objDecl ) || ((! inFunction || objDecl->get_storageClasses().is_static ) && ! isConstExpr( objDecl->get_init() ) ) ) ) {
    298298                        // constructed objects cannot be designated
    299                         if ( isDesignated( objDecl->get_init() ) ) throw SemanticError( "Cannot include designations in the initializer for a managed Object. If this is really what you want, then initialize with @=.", objDecl );
     299                        if ( isDesignated( objDecl->get_init() ) ) throw SemanticError( "Cannot include designations in the initializer for a managed Object. If this is really what you want, then initialize with @=.\n", objDecl );
    300300                        // constructed objects should not have initializers nested too deeply
    301301                        if ( ! checkInitDepth( objDecl ) ) throw SemanticError( "Managed object's initializer is too deep ", objDecl );
  • src/Parser/ExpressionNode.cc

    r690f13c r72dc82a  
    1010// Created On       : Sat May 16 13:17:07 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Sat Mar  4 06:58:47 2017
    13 // Update Count     : 509
     12// Last Modified On : Thu Mar 30 17:02:46 2017
     13// Update Count     : 515
    1414//
    1515
     
    356356        // these types do not have associated type information
    357357        } else if ( StructDecl * newDeclStructDecl = dynamic_cast< StructDecl * >( newDecl )  ) {
    358                 return new CompoundLiteralExpr( new StructInstType( Type::Qualifiers(), newDeclStructDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     358                if ( newDeclStructDecl->has_body() ) {
     359                        return new CompoundLiteralExpr( new StructInstType( Type::Qualifiers(), newDeclStructDecl ), maybeMoveBuild< Initializer >(kids) );
     360                } else {
     361                        return new CompoundLiteralExpr( new StructInstType( Type::Qualifiers(), newDeclStructDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     362                } // if
    359363        } else if ( UnionDecl * newDeclUnionDecl = dynamic_cast< UnionDecl * >( newDecl )  ) {
    360                 return new CompoundLiteralExpr( new UnionInstType( Type::Qualifiers(), newDeclUnionDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     364                if ( newDeclUnionDecl->has_body() ) {
     365                        return new CompoundLiteralExpr( new UnionInstType( Type::Qualifiers(), newDeclUnionDecl ), maybeMoveBuild< Initializer >(kids) );
     366                } else {
     367                        return new CompoundLiteralExpr( new UnionInstType( Type::Qualifiers(), newDeclUnionDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     368                } // if
    361369        } else if ( EnumDecl * newDeclEnumDecl = dynamic_cast< EnumDecl * >( newDecl )  ) {
    362                 return new CompoundLiteralExpr( new EnumInstType( Type::Qualifiers(), newDeclEnumDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     370                if ( newDeclEnumDecl->has_body() ) {
     371                        return new CompoundLiteralExpr( new EnumInstType( Type::Qualifiers(), newDeclEnumDecl ), maybeMoveBuild< Initializer >(kids) );
     372                } else {
     373                        return new CompoundLiteralExpr( new EnumInstType( Type::Qualifiers(), newDeclEnumDecl->get_name() ), maybeMoveBuild< Initializer >(kids) );
     374                } // if
    363375        } else {
    364376                assert( false );
  • src/Parser/parser.yy

    r690f13c r72dc82a  
    1010// Created On       : Sat Sep  1 20:22:55 2001
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Fri Mar 17 15:42:22 2017
    13 // Update Count     : 2317
     12// Last Modified On : Thu Mar 30 15:42:32 2017
     13// Update Count     : 2318
    1414//
    1515
     
    423423        | postfix_expression DECR
    424424                { $$ = new ExpressionNode( build_unary_ptr( OperKinds::DecrPost, $1 ) ); }
    425         | '(' type_name_no_function ')' '{' initializer_list comma_opt '}' // C99
     425        | '(' type_name_no_function ')' '{' initializer_list comma_opt '}' // C99, compound-literal
    426426                { $$ = new ExpressionNode( build_compoundLiteral( $2, new InitializerNode( $5, true ) ) ); }
    427427        | postfix_expression '{' argument_expression_list '}' // CFA
  • src/SymTab/Indexer.cc

    r690f13c r72dc82a  
    1010// Created On       : Sun May 17 21:37:33 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Tue Mar 14 08:07:34 2017
    13 // Update Count     : 17
     12// Last Modified On : Thu Mar 30 16:38:47 2017
     13// Update Count     : 19
    1414//
    1515
     
    483483        void Indexer::visit( CompoundLiteralExpr *compLitExpr ) {
    484484                acceptNewScope( compLitExpr->get_result(), *this );
    485                 maybeAccept( compLitExpr->get_type(), *this );
    486485                maybeAccept( compLitExpr->get_initializer(), *this );
    487486        }
  • src/SymTab/Validate.cc

    r690f13c r72dc82a  
    1010// Created On       : Sun May 17 21:50:04 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Thu Mar 16 16:39:15 2017
    13 // Update Count     : 353
     12// Last Modified On : Thu Mar 30 16:50:13 2017
     13// Update Count     : 357
    1414//
    1515
     
    222222                CompoundLiteral compoundliteral;
    223223
     224                HoistStruct::hoistStruct( translationUnit );
    224225                EliminateTypedef::eliminateTypedef( translationUnit );
    225                 HoistStruct::hoistStruct( translationUnit );
    226226                ReturnTypeFixer::fix( translationUnit ); // must happen before autogen
    227227                acceptAll( translationUnit, lrt ); // must happen before autogen, because sized flag needs to propagate to generated functions
     
    824824                static UniqueName indexName( "_compLit" );
    825825
    826                 ObjectDecl *tempvar = new ObjectDecl( indexName.newName(), storageClasses, LinkageSpec::C, 0, compLitExpr->get_type(), compLitExpr->get_initializer() );
    827                 compLitExpr->set_type( 0 );
     826                ObjectDecl *tempvar = new ObjectDecl( indexName.newName(), storageClasses, LinkageSpec::C, 0, compLitExpr->get_result(), compLitExpr->get_initializer() );
     827                compLitExpr->set_result( 0 );
    828828                compLitExpr->set_initializer( 0 );
    829829                delete compLitExpr;
  • src/SynTree/Expression.cc

    r690f13c r72dc82a  
    1010// Created On       : Mon May 18 07:44:20 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Fri Mar 17 09:42:04 2017
    13 // Update Count     : 51
     12// Last Modified On : Thu Mar 30 16:41:13 2017
     13// Update Count     : 52
    1414//
    1515
     
    571571
    572572
    573 CompoundLiteralExpr::CompoundLiteralExpr( Type * type, Initializer * initializer ) : type( type ), initializer( initializer ) {
     573CompoundLiteralExpr::CompoundLiteralExpr( Type * type, Initializer * initializer ) : initializer( initializer ) {
    574574        assert( type && initializer );
    575         set_result( type->clone() );
    576 }
    577 
    578 CompoundLiteralExpr::CompoundLiteralExpr( const CompoundLiteralExpr &other ) : Expression( other ), type( other.type->clone() ), initializer( other.initializer->clone() ) {}
     575        set_result( type );
     576}
     577
     578CompoundLiteralExpr::CompoundLiteralExpr( const CompoundLiteralExpr &other ) : Expression( other ), initializer( other.initializer->clone() ) {}
    579579
    580580CompoundLiteralExpr::~CompoundLiteralExpr() {
    581581        delete initializer;
    582         delete type;
    583582}
    584583
     
    586585        os << "Compound Literal Expression: " << std::endl;
    587586        os << std::string( indent+2, ' ' );
    588         type->print( os, indent + 2 );
     587        get_result()->print( os, indent + 2 );
    589588        os << std::string( indent+2, ' ' );
    590589        initializer->print( os, indent + 2 );
  • src/SynTree/Expression.h

    r690f13c r72dc82a  
    1010// Created On       : Mon May 18 07:44:20 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Sat Jan 14 14:37:54 2017
    13 // Update Count     : 37
     12// Last Modified On : Thu Mar 30 16:44:00 2017
     13// Update Count     : 41
    1414//
    1515
     
    3535
    3636        Type *& get_result() { return result; }
     37        const Type * get_result() const { return result; }
    3738        void set_result( Type * newValue ) { result = newValue; }
    3839        bool has_result() const { return result != nullptr; }
     
    586587        virtual ~CompoundLiteralExpr();
    587588
    588         Type * get_type() const { return type; }
    589         void set_type( Type * t ) { type = t; }
    590 
    591589        Initializer * get_initializer() const { return initializer; }
    592590        void set_initializer( Initializer * i ) { initializer = i; }
     
    597595        virtual void print( std::ostream & os, int indent = 0 ) const;
    598596  private:
    599         Type * type;
    600597        Initializer * initializer;
    601598};
  • src/SynTree/Mutator.cc

    r690f13c r72dc82a  
    1010// Created On       : Mon May 18 07:44:20 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Thu Feb 16 15:02:23 2017
    13 // Update Count     : 21
     12// Last Modified On : Thu Mar 30 16:45:19 2017
     13// Update Count     : 22
    1414//
    1515
     
    369369        compLitExpr->set_env( maybeMutate( compLitExpr->get_env(), *this ) );
    370370        compLitExpr->set_result( maybeMutate( compLitExpr->get_result(), *this ) );
    371         compLitExpr->set_type( maybeMutate( compLitExpr->get_type(), *this ) );
    372371        compLitExpr->set_initializer( maybeMutate( compLitExpr->get_initializer(), *this ) );
    373372        return compLitExpr;
  • src/SynTree/Visitor.cc

    r690f13c r72dc82a  
    1010// Created On       : Mon May 18 07:44:20 2015
    1111// Last Modified By : Peter A. Buhr
    12 // Last Modified On : Thu Feb 16 15:01:25 2017
    13 // Update Count     : 23
     12// Last Modified On : Thu Mar 30 16:45:25 2017
     13// Update Count     : 24
    1414//
    1515
     
    292292void Visitor::visit( CompoundLiteralExpr *compLitExpr ) {
    293293        maybeAccept( compLitExpr->get_result(), *this );
    294         maybeAccept( compLitExpr->get_type(), *this );
    295294        maybeAccept( compLitExpr->get_initializer(), *this );
    296295}
  • src/libcfa/iostream.c

    r690f13c r72dc82a  
    154154ostype * ?|?( ostype * os, const char * cp ) {
    155155        enum { Open = 1, Close, OpenClose };
    156         static const unsigned char mask[256] = {
     156        static const unsigned char mask[256] @= {
    157157                // opening delimiters, no space after
    158158                ['('] : Open, ['['] : Open, ['{'] : Open,
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