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For example, a vector would have a random-access iterator, but a list only a bidirectional iterator. Iterators are the major feature that allow the generality of the STL. For example, an algorithm to reverse a sequence can be implemented using bidirectional iterators, and then the same implementation can be used on lists, vectors and deques.
Until the standardization of the C++ language in 1998, they were part of the Standard Template Library (STL), published by SGI. Alexander Stepanov , the primary designer of the STL, bemoans the choice of the name vector , saying that it comes from the older programming languages Scheme and Lisp but is inconsistent with the mathematical meaning ...
The C++ Standard Library is based upon conventions introduced by the Standard Template Library (STL), and has been influenced by research in generic programming and developers of the STL such as Alexander Stepanov and Meng Lee. [4] [5] Although the C++ Standard Library and the STL share many features, neither is a strict superset of the other.
In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
For example, a container defined as std::vector<Shape*> does not work because Shape is not a class, but a template needing specialization. A container defined as std::vector<Shape<Circle>*> can only store Circles, not Squares. This is because each of the classes derived from the CRTP base class Shape is a unique type.
Due to their usefulness, they were later included in several other implementations of the C++ Standard Library (e.g., the GNU Compiler Collection's (GCC) libstdc++ [2] and the Visual C++ (MSVC) standard library). The hash_* class templates were proposed into C++ Technical Report 1 (C++ TR1) and were accepted under names unordered_*. [3]
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.
Example implementation of expression templates : An example implementation of expression templates looks like the following. A base class VecExpression represents any vector-valued expression. It is templated on the actual expression type E to be implemented, per the curiously recurring template pattern.