C++ for Scientists - Technische Universität Dresden

204 CHAPTER 7. EFFECTIVE PROGRAMMING: THE POLYMORPHIC WAY
copy(InputIterator first, InputIterator last, OutputIterator result)
{
while (first != last)
∗result++ = ∗first++;
return result;
}
With this code the same functionality of the memcpy() from the C library is achieved.
All kinds of data structure which offer an begin() and end() iterator can be used.
• Container: An abstraction to all kinds of data structures which can store other data
types.
• Iterator: This is the glue between the containers and the algorithms. First, it separates
the usage of data structures and algorithms. Second, it provides a concept hierarchy for
all kinds of traversal within data structures.
This type of genericity is called parametric polymorphism (see Section 7.5.2). Section 4.9
introduced the Standard Template Library (STL). The STL solves many standard data structure
and algorithmic problems. The STL is (or should be) the first choice in all code development
steps.
• Algorithm/Data-Structure Interoperability: First, each algorithm is written in a datastructure
neutral way, allowing a single template function to operate on many different
classes of containers. The concept of an iterator is the key ingredient in this decoupling of
algorithms and data-structures. The impact of this technique is a reduction of the STL’s
code size from O(M*N) to O(M+N), where M is the number of algorithms and N is the
number of containers. Considering a situation of 20 algorithms and 5 data-structures,
this makes the difference between writing 100 functions versus only 25 functions! And the
differences grows faster as the number of algorithms and data-structures increase.
• Extension through Function Objects: The second way that the STL is generic is that its
algorithms and containers are extensible. The user can adapt and customize the STL
through the use of function objects. This flexibility is what makes STL such a great
tool for solving real-world problems. Each programming problem brings its own set of
entities and interactions that must be modeled. Function objects provide a mechanism
for extending the STL to handle the specifics of each problem domain.
• Element Type Parametrization: The third way that STL is generic is that its containers
are parametrized on the element type.
Most people think, that element type parametrization is the feature that makes the successful.
This is perhaps the least interesting way in which STL is generic. The interoperability with
iterators and the extensibility by function objects are more important parts of the STL. But
the essence is the programming with concepts. The programmer can write the data structures
and algorithms, or in other words the concept of these, as it should be. Next to these facts, the
STL has proven that with the generic programming paradigm, high performance computing
can be accomplished as well on several different computer architectures.
The advantages of this paradigm are:
• Programming with concepts
• Great number of available libraries