Category Archives: Programming

Variadic macro to count number of arguments

The C-Preprocessor is a very powerful mechanism, which offers many different features. One of these features is called Variadic macros: macros that accept a varying number of arguments. It is interesting to note at this point, that such Variadic macros, despite being part of the C99 Standard, are not part of the C++ Standard at the moment. However, a big number of C++ compilers support it nevertheless.

While allowing the definition of Variadic macros, there is no built-in (preprocessor) way of obtaining the actual number of arguments that is passed to a specific Variadic macro. In this post we shall provide a possible macro implementation for such a query.

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Futures: asynchronous invocation

In the concurrent world, a Future object refers to an object whose actual value is to be computed in the future. You can think of it as a handle to an asynchronous invocation of a computation that yields a value.

Many so called concurrent programming languages support this idea as a native construct offered by the core language itself. Unfortunately, C++ does not. Well, at least not in the current standard; C++0x (or shall I say C++1x ?) is going to support std::future as part of the massive new C++0x thread library, which is based on boost::thread. In this post we will implement a simple, yet very powerful, such future object.

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Catching uncaught exceptions within terminate

The handler std::terminate() is called whenever the exception handling mechanism cannot find a suitable catch clause for a thrown exception (and in some other cases. For example, when an exception is thrown during the handling of another exception – see this GotW post about std::uncaught_exception). It is possible to define a custom handler by using std::set_terminate.

In this post we would like to create a terminate handler which will be able to catch the exception that led to its invocation, when there is one.

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Escaping overloaded operators

The possibility of overloading just about any C++ operator and having it do something entirely different from what it was designed for, can sometimes make life pretty hard.

Here are a couple of examples: What if you wanted to take the address of an object, which had implemented an entirely different semantic for the ampersand (&) operator? Or what if somebody decided to overload the comma operator in some strange manner?

As you could have guessed, there are solutions for such scenarios.

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Metalists for fun and profit

The following post has been written by a guest blogger.
My name is Nadav Rotem and I am a guest blogger on this blog. I am here to write about metalists. Not metalists like Metallica or Iron Maiden, but meta-lists. Lists which are “template maiden”.

The First thing I am going to show you is how to create a data structure which is similar to a linked list. Next we are going to define the Push, Pop and Concat operations. After we have those, we will implement the Walsh transform (similar to FFT on integers) on our list. After that, we will use template templates to define generators to create lists. Finally we are going to implement the Map and Reduce operations on our lists. Let’s start.

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Compile time primality test

The powerful template mechanism of C++ allows us to write pretty complex Meta Functions, which are executed by the compiler during compilation. There are two basic types of meta-functions: one whose result is a type (mainly dealt with by Boost.MPL), and the other is a compile-time computation (which can result in any compile time constant). In this post we will review an example of the latter.

We would like to achieve a compile time boolean constant of the form is_prime::res. The problem with such meta programming task, in my opinion, is that it requires a functional programming mindset. Something that we, as C++ programmers, aren’t necessarily used to. But I am sure we will be able to tackle it anyway.

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One of the containers introduced within TR1 (which is already widely available – both in gcc and Visual Studio) is a Tuple type, which is adopted from The Boost Tuple Library. Tuple types are very convenient at times; For example, it is possible to return multiple values from a function through a tuple, or write more intuitive and expressive code by utilizing tuples.

In this post we will examine the functionality offered by the new Tuple container, and have a go at profiling its performance. Actually, the results of said profiling were a small (pleasant) surprise to me.

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Memoization is essentially a fancy name for caching results for future use. A generalization of dynamic programming, if you will.

While I am certain most of us use it one way or another, in many occasions, it is usually through an Ad hoc implementation.. One that is only suitable for the specific, current, use case. Why don’t we generalize it further, and supply a generic, reusable, solution for Memoization?

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