Wednesday, 25 June 2008

The future of C++

In my recent blog entry* I complained about not exactly knowing where C++ is heading, what features will C++0x contain when it finally appears, and if we'll need to switch to hex as in C++0a ;-). Then I read some interviews with Bjarne Stroustrup** and the things became clearer.

1. The process

The first ambiguity I addressed, was the problem of the very loooong time which C++ needs when acquiring new features, and hinted at the lack of corporate backing. Bjarne on that**:
BS: The progress on standard libraries has not been what I hoped for. ... We will not get ... I had hoped for much more, but the committee has so few resources and absolutely no funding for library development.
BS: There is no shortage of good ideas in the committee or of good libraries in the wider C++ community. There are, however, severe limits to what a group of volunteers working without funding can do. What I expect to miss most will be thread pools and the file system library. However, please note that the work will proceed beyond '09 and that many libraries are already available; for example see what has to offer.
So that's pretty clear, the industry isn't backing C++ anymore, and the ISO beaurocracy isn't helping here. Java's JSP is definitely more lightweight. Python hasn't a commitee. IBM, Sun (and Google?) are massively backing Java. Previously Google was a stronghold of C++ (MapReduce, BigTable, BigFile), but lately Java seems to take over, in the real "weed language" manner.

2. The features

The second of my questions was the extent of new features which will make it into new standard, beacuse this was a constant source of confusion: thousands of proposals, each in a different state of progress, constantly wandering between approved, considered, considered strongly, considered not so strongly, not considered, demised, etc ;-). Now the new feature scope seems to stabilize at last. Bjarne again**:
BS: I do — based on existing work and votes — expect to get:

- Threads
- Regular expressions
- Hash tables
- Smart pointers
- Many improvements for containers
- Quite a bit support for new libraries

- A memory model supporting modern machine architectures
- Thread local storage
- Atomic types
- Rvalue references
- Static assertions
- Template aliases
- Variadic templates
- Strongly typed enums
- constexpr: Generalized constant expressions
- Control of alignment
- Delegating constructors
- Inheriting constructors
- auto: Deducing variable types from initializers
- Control of defaults
- nullptr: A name for the null pointer
- initializer lists and uniform initialization syntax and semantics
- concepts (a type system for template arguments)
- a range-based for loop
- raw string literals
- UTF8 literals
- Lambda functions
The most important feature (IMHO) is**:
BS: The new memory model and a task library was voted into C++0x in Kona. That provides a firm basis for share-memory multiprocessing as is essential for multicores.
and, of course, the auto keyword and lambdas!

Maybe more important is what won't be there**:
BS: The progress on standard libraries has not been what I hoped for. .... We will not get the networking library, the date and time library, or the file system library. These will wait until a second library TR. I had hoped for much more, ...
BS: ... What I expect to miss most will be thread pools and the file system library. However, please note that the work will proceed beyond '09 ...

But an important change of working style will take place:**
... Fortunately, the committee has decided to try for more and smaller increments. For example, C++0x (whether that'll be C++09 or C++10) will have only the preparations for programmer-controlled garbage collection and lightweight concurrency, whereas we hope for the full-blown facilities in C++12 (or C++13).
and we may expect a host of new extensions in the future!

On the other hand, at least when the multithreading is concerned, there are independent libraries available, and they offer some rather high level concepts! Take for example the latest Trolltech's Qt 4.5 framework***, which implements futures, automatic scaling for multicore, has a MapReduce implementation plus concurrent mapping and filtering algorithms. It's just like Java 7's fork-join framework* and the ParallelArray class. Bravo! Other library with high level threading support are of course the Intel's Thread Building Blocks, it's not bad either! At this point we don't need a standard document, as it seems.

3. The prospects

At last, let's pose a more general question: what kind of language wants C++ to be? In the past Bjarne Stroustrup maintained that C++ should be a "general purpose programming language". Contrast this with the statements from the last interviews**:
JB: You are looking at making C++ better for systems programming in C++0x as I understand it, is that correct? ...

BS: Correct. The most direct answer involves features that directly support systems programming, such as thread local storage and atomic types.

JB: C++ is often used in embedded systems, including those where safety and security are top priorities. What are your favorite examples and why do you think C++ is an ideal language for embedded systems especially where safety is a concern, aside from easy low-level machine access?

BS: Yes, and I find many of those applications quite exciting.

For my taste, Bjarne thinks clearly that C++ is an system and embedded programming language: e.g. he expressed his fondness for robotics systems before. That's bad news, because I don't really like embedded programming and automotive :-(((. On the other hand, system programming is quite exciting for me, provided I haven't to fiddle about low level data structures too much.

Allow me a question in this context: for me OO programming is about hiding low level details, seeing the bigger picture. If the strengths of the language lie in the hardware access then maybe it's not so useful for OO programming? We can use C for low level programming (like Wireshark's code does, and it's not a toy system) and do OO in Java or Python? So where's the place for C++ then?

But maybe the future will be totally diffrent? Maybe we won't be programming C++ anymore but rather the Qt platform, which only happens to be written in C++? This would be akin to the Java platform: because C++ doesn't provide a standard ABI, many comapnies are using Qt as to assure the portability of their code between operating systems (among others my current client). Interestingly, not only in GUI applications, abut also in general purpose programming! But what about the (maybe only preconceived) imcompatibility with the standard library, which I bemoaned in one of my previous entries? If I can give faith to Danny Kalev's words****:
And in other news, Nokia completed its acquisition of Trolltech last week.
Qt is currently used in Skype, Google Earth, and Adobe Photoshop Elements.
After Nokia's acquisition, it seems that Qt will be modified to support Symbian and other mobile environments, or at least POSIX libraries and better support for mainstream C++.
then it seems that not only yours truly is having that impression, and that there will be a remedy soon!

* Language trends and waiting blues:
** An Interview with Bjarne Stroustrup: (but
also , although I don't quote it here)
**** C++ Reference Guide: (Notes on 25th of June)

Sunday, 8 June 2008

C++ pocket lambda library, part III

As I first wrote my C++ lambda code about a year and a half ago, I didn't know that I'm hitting such a hot topic. I wanted just to reduce the amount of code I had to write, and didn't have any high-church functional programming thingy in mind. But now lamdbads and closures are all the rage: look at all those Groovy articles on developerWorks for example. Even Java 7 will have closures (or won't it?). Definitely, Ruby has made programming languages an interesting topic again!

BTW, do you know how currying and lambdas looks like in Haskell, a popular functional (dynamically and strongly typed) language? If you don't know what it is, we've discussed currying in a previous posting of this mini-series*. In Haskell it is very natural syntactically, you can just write (well, almost, I skipped the T=>T=>T type definition):

    product = a b = a*b
    double = product 2    <-- curried!
    double 2
This is basic, but look at that:

    doubleEach = map (2 *)
i.e. we define a partially evaluated function (as map needs 2 arguments, a function and a list) waiting for application. It's like you'd be using the bind() template of our last posting* in C++. And look at the cute lambda function shortcut: (2 *) is a function (unsurprisingly, as in Haskell everything is a function, contrary to Ruby or Groovy where everything is an object, even the functions ;-)). I like it.

1. Getting exxpresive

Admittedly the code in the 2nd part of this mini series was rather bland*: some hyper technical stuff but not really very entertaining like the 1st part (which was really fun for me to code). I wrote it only for completness' sake, as it is part of my code. I hope this installment will be more fun again.

So let us tackle the last topic we need to implement as to have an usable lambda mini-library: the expression templates. The what? Wy do we need it exacltly? I'm certainly not going to write code like: __expr template <class Expressible> express_anger(Expressible& e); - not in my life!!! Ok, ok, let's introduce the concept gently.

Do you know for example the Boost (e)Xpressive library? It expresses (expressively) regular expressions (Boost Spirit library does in much greater style for grammars) by C++ code constructs. I.e. instead of:

    sregex rex = sregex::compile( "(\\w+) (\\w+)!" );
you can write

    sregex rex = (s1= +_w) >> ' ' >> (s2= +_w) >> '!';
using the domain specific language (buzzword alarm!!!) instead. The string: "\\w+" is replaced by an (Xpressive) expression +_w. You recognize perhaps the usage of placeholders, like our _$1 or _$2, operator overloading and assignment of partial matches to external variables (external to the closure, you'd say in Perl or Groovy). But in this case we don't have a single operation which should create a functor, neither a combination of two different operations. Here we have one operation applied again and again (>> concatenator), and we have to encapsulate it in a single lambda functor!

The same problem emerges in the context of out mini-library.

    for_each(vec.begin(), vec.end(), cout << "-->" << _$1 << "\n");
we have to collect all the items which have to be sent to cout, which can be infinite in number!

Here expression templates come to the rescue. First described by Todd Veldhuizen**, they let us to define recursive templates with operator overloading. And recursion can go infinitely deep down, so we can accomodate our long shift operator sequences with our usual aplomb! What we need is following tree structure:

                   op >>
                 /    \
               op >>   \
             /   \      \
           op >>  \      \
         /        \      \
      s1=+_w  ' ' s2=+w_  '!'
True to the "Modern C++ design" book's ubiquitous typelists usage, we can express this runtime structure in compile time with a following monstrous type:

    Op<Op<Op<Char, Expr>, Expr>, Char> rex;
Here, all the structural information has been recorded: just read the type from left to right and compare it with the picture of the parse tree. Now we have to supply the arguments to the constructor of an object of this type and then call a method of the rex object. But we don't do it in classical sense, the construction and the type definition will be done recursively while compiler is parsing the expression. Hence the name of the expression templates #B-D.

2. First real exxpressive code

To convince the compiler to to some sensible work for us we first define the following recursive template:

    // Shift represents a node in the parse tree
    // ---
    template<typename Left, typename Op, typename Right>
        struct Shift  : public lambda_expr
        Left leftNode;
        Right rightNode;
        std::ostream& out;

        Shift(Left t1, Right t2, std::ostream& os)
            : leftNode(t1), rightNode(t2), out(os) { }

        template <class T>
            void operator() (T& t) { Op::print(leftNode, rightNode, t); }
You can see, the structure of the tree node is different form the monstrous type given as example above, well, it's even more complicated. Using this approach we would express the above example tree as:

    Node<Node<Node<Char, Op, Expr>, Op, Expr>, Op, Char> rex;
Ok, why not. If it's supposed to help, I couldn't care less... ;-)

But what has this all with our lambda library? The answer is, we can apply the same concept to the problem of priniting data to cout: supposed we have a following lambda function: cout lt;< "element:" << _$1, we'll can build a type tree like:

                  << op
                 /    \
             << op     \
             /   \      \
            /     \      \
         cout "element:" _$1
One interesting thing to note is the ()-operator, which prints the actual node of the parse tree using a mysterious T& t argument: it is the actual parametr of the lambda function, i.e. the uderlying iterator itself!

So if we have the top level tree node (i.e. the expr in the diagram above), we'll just call its ()-operator an the whole tree is printed out, hopefully! Two problem pose themselves here:

1. how to descend to the subnodes of the tree while printing, and
2. how do we get the whole tree structure constructed in the first place?

3. Recursive printing

To answer the first question we need the representation of the recursive printing operation in code:

    struct shiftOp // Represents << operation
        template <class Left, class Right, class T>
            static void print(Left& left, Right& right, T& t)
              print(left.leftNode, left.rightNode, t); // walk down
              left.out << right(t);  // if right needs t? : << _$1*2 ???
template <class Right, class T> static void print(std::ostream& left, Right& right, T& t) { left << right(t); // at the beginning }
template <class Left, class T> static void print(Left& left, placeholder<1>& right, T& t) { print(left.leftNode, left.rightNode, t); left.out << t; // special case placeholder } };
First we walk down the tree in the depth first, left to right mode (the first print() function). When we arrive at the lowest left node of the tree we do the first print, then go back and print the corresponding right node. Note that we don't walk a physical tree here, we walk a type expression which is organized like a tree! The print() functions will "match" a part of the type-tree, print the matched part, and match the subtype in a recursive manner. So we are treating types in compile time as we'd treat data in the runtime! That's why this is called template META-programming.

Then we need only 2 specialisations: one for the first invocation of the shift operator, where the left operand is the output stream itself, and the second one to deal with our lambda mini-library's placeholder types. The placeholder will be printed directly to the stream. Our tree expression for the simple example above will be then as follows:

    Shift<Shift<cout, shiftOp, "element"-Expr>, shiftOp, _$1> lambda;
Now just imagine how the print() function will work on it.

4. Growing the tree

To answer the second question we need 2 simple ;-) operator overloading definitions:

    // The overloaded operator which does parsing for expressions of the
    //  form "a<<b<<c<<d" => Shift<Shift<Shift<A, op, B>, op, C>, op, D>()
// for ostream: cannot be taken by value!
template<class Left, class Right> Shift<Left&, shiftOp, Right> operator<< (Left& left, Right right) { return Shift<Left&, shiftOp, Right>(left, right, left); // left IS an ostream! }
// for lambda_expr: must be taken by value! template<class Left1, class Left2, class Right> Shift<Shift<Left1, shiftOp, Left2>, shiftOp, Right> operator<< (Shift<Left1, shiftOp, Left2> left, Right right) { return Shift<Shift<Left1, shiftOp, Left2>, shiftOp, Right>(left, right, left.out); }
The first one starts the recursive template definition at the "cout <<"-expression, an the second one goes one nesting level deeper and one <<-operator application to the right. It's an elaborate syntax, but conceptually it's not a rocket science! Note how the stream (cout) parameter is handed down the expression tree.

Yeeee-ha! We are done now! Let us try it out:

    for_each(vec.begin(), vec.end(), cout << _$1);  // OK
    for_each(vec.begin(), vec.end(), cout << _$1 << "\n" ); // compile error???
    for_each(vec.begin(), vec.end(), cout << i++ << ":" << _$1 << " " ); // again!!!
Did you see that? We still cannot use our lambda library. What is it this time? Well, we need a last building block, and for discussioon of that we need a separate paragraph.

5. External data in lambda functions

The problem is, that inside of an lambda expression we are working with functors, and not with native C++ data types. This means, we need a function call operator for each element of the lambda expression. What can be easier than that! We can make a trivial functor, which, when evaluated returns our literal value i.e. "\n" or ":"!

    // constant_ref
    //  ---
    template<class T> struct Const : public lambda_expr
        T& val;
        Const(T& t) : val(t) { }
        const T& operator()() const { return val; }
        const T& value() const { return val; }

        template <class S> // for different context: needed for Shift!!!
            const T& operator()(S& s) const { return val; } // ignore input
template<class T> Const<T> delay(T& t) { return Const<T>(t); }
This can be described as a delayed evaluation: the compiler first wraps the constant in a functor, and the constant's value is used in runtime instead of compile time. Now a lambda like: auto lambda = (cout << _$1 << "\n"); will work. BTW I wonder if that would compile...

Maybe you don't remebmer, but it the IIa part of this series*** I showed the following code snippet:

    // assign to a external counter
    int aaa;
    for_each(vecx.begin(), vecx.end(), aaa += _$1->*(&XXX::value));
only to say, that it wouldn't work yet. What's the problem? Basically the same one: we are using native C++ type instead of a functor. The solution is of course the delayed evaluation from above, but now must cater for the basic operations:

    // variable_ref
    //  ---
    template<class T> struct Var : public lambda_expr
        T& val;
        Var(T& t) : val(t) { }
        T& operator()() const { return val; }
        T& operator()(T& t) const { return val; } // ignore input
        T& value() const { return val; }

        AssgnTo<T> operator=(T t) { return AssgnTo<T>(val, t); }

        template <class S>  // assign from lambda_expr
            AssgnTo<T> operator=(S s) { return AssgnTo<T>(val, s); }
template<class T> Var<T> globvar(T& t) { return Var<T>(t); }
Here we enabled the assignment to the C++ data type. The addional operators could be implemented like this:

    // OPEN todo: be more modular!!!
    //  --- return lambda_operation<lambda_exp, oper_type>
    template<class T>
        AddAssg<T> operator+=(Var<T> v, const T& t) { return AddAssg<T>(v.value(), t); }
    template<class T>
        AddAssg<T> operator+=(Var<T> v, placeholder<1>) { return AddAssg<T>(v.value()); }
template<class T> Incr<T> operator++(Var<T> v, int) { return Incr<T>(v.value()); }
Now we can finally write:

    int xxx = 0;
    for_each(vecx.begin(), vecx.end(), globvar(xxx)++);
    for_each(vecx.begin(), vecx.end(), globvar(xxx) += 5);
    for_each(vecx.begin(), vecx.end(), globvar(xxx) += _$1->*(&XXX::value));
and, for example:

    for_each(vec.begin(), vec.end(), cout << _$1 << delay("\n") );
    for_each(vec.begin(), vec.end(), cout << globvar(i++) << delay(":") << _$1 );
But not, among others: globvar(aaa) = _$1->*(&XXX::value), as it's not a complete, orthogonal, and idustrial strength library. It was only a little pastime of mine...

6. The End?

Ehm, I thought this will be the last part of the description of my simple implementation, but no, I'll need another blog entry as not to bore you to death with this one. Meantime, the writing of this description has taken more time than the actual implementation itself!!! But I have some more points to make, and at the end of a long post, there are rater unlikely to be given much attention. So long then!

* Part II:
** Techniques for Scientific C++:
*** Part IIa: