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Lists

Lists are sequence containers that allow constant time insert and erase operations anywhere within the sequence, and iteration in both directions.

List containers are implemented as doubly-linked lists; Doubly linked lists can store each of the elements they contain in different and unrelated storage locations. The ordering is kept internally by the association to each element of a link to the element preceding it and a link to the element following it.

They are very similar to forward_list: The main difference being that forward_list objects are single-linked lists, and thus they can only be iterated forwards, in exchange for being somewhat smaller and more efficient.

Compared to other base standard sequence containers (array, vector and deque), lists perform generally better in inserting, extracting and moving elements in any position within the container for which an iterator has already been obtained, and therefore also in algorithms that make intensive use of these, like sorting algorithms.

The main drawback of lists and forward_lists compared to these other sequence containers is that they lack direct access to the elements by their position; For example, to access the sixth element in a list, one has to iterate from a known position (like the beginning or the end) to that position, which takes linear time in the distance between these. They also consume some extra memory to keep the linking information associated to each element (which may be an important factor for large lists of small-sized elements).

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pair

This class couples together a pair of values, which may be of different types (T1 and T2). The individual values can be accessed through its public members first and second.

Pairs are a particular case of tuple.

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Forward lists

Forward lists are sequence containers that allow constant time insert and erase operations anywhere within the sequence.

Forward lists are implemented as singly-linked lists; Singly linked lists can store each of the elements they contain in different and unrelated storage locations. The ordering is kept by the association to each element of a link to the next element in the sequence.

The main design difference between a forward_list container and a list container is that the first keeps internally only a link to the next element, while the latter keeps two links per element: one pointing to the next element and one to the preceding one, allowing efficient iteration in both directions, but consuming additional storage per element and with a slight higher time overhead inserting and removing elements. forward_list objects are thus more efficient than list objects, although they can only be iterated forwards.

Compared to other base standard sequence containers (array, vector and deque), forward_list perform generally better in inserting, extracting and moving elements in any position within the container, and therefore also in algorithms that make intensive use of these, like sorting algorithms.

The main drawback of forward_lists and lists compared to these other sequence containers is that they lack direct access to the elements by their position; For example, to access the sixth element in a forward_list one has to iterate from the beginning to that position, which takes linear time in the distance between these. They also consume some extra memory to keep the linking information associated to each element (which may be an important factor for large lists of small-sized elements).

The forward_list class template has been designed with efficiency in mind: By design, it is as efficient as a simple handwritten C-style singly-linked list, and in fact is the only standard container to deliberately lack a size member function for efficiency considerations: due to its nature as a linked list, having a size member that takes constant time would require it to keep an internal counter for its size (as list does). This would consume some extra storage and make insertion and removal operations slightly less efficient. To obtain the size of a forward_list object, you can use the distance algorithm with its begin and end, which is an operation that takes linear time.

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Unordered Map

Unordered maps are associative containers that store elements formed by the combination of a key value and a mapped value, and which allows for fast retrieval of individual elements based on their keys.

In an unordered_map, the key value is generally used to uniquely identify the element, while the mapped value is an object with the content associated to this key. Types of key and mapped value may differ.

Internally, the elements in the unordered_map are not sorted in any particular order with respect to either their key or mapped values, but organized into buckets depending on their hash values to allow for fast access to individual elements directly by their key values (with a constant average time complexity on average).

unordered_map containers are faster than map containers to access individual elements by their key, although they are generally less efficient for range iteration through a subset of their elements.

Unordered maps implement the direct access operator (operator[]) which allows for direct access of the mapped value using its key value as argument.

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LIFO stack

Stacks are a type of container adaptor, specifically designed to operate in a LIFO context (last-in first-out), where elements are inserted and extracted only from one end of the container.

stacks are implemented as containers adaptors, which are classes that use an encapsulated object of a specific container class as its underlying container, providing a specific set of member functions to access its elements. Elements are pushed/popped from the "back" of the specific container, which is known as the top of the stack.

The underlying container may be any of the standard container class templates or some other specifically designed container class. The container shall support the following operations: empty size back push_back pop_back

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Vector

Vectors are sequence containers representing arrays that can change in size.

Just like arrays, vectors use contiguous storage locations for their elements, which means that their elements can also be accessed using offsets on regular pointers to its elements, and just as efficiently as in arrays. But unlike arrays, their size can change dynamically, with their storage being handled automatically by the container.

Internally, vectors use a dynamically allocated array to store their elements. This array may need to be reallocated in order to grow in size when new elements are inserted, which implies allocating a new array and moving all elements to it. This is a relatively expensive task in terms of processing time, and thus, vectors do not reallocate each time an element is added to the container.

Instead, vector containers may allocate some extra storage to accommodate for possible growth, and thus the container may have an actual capacity greater than the storage strictly needed to contain its elements (i.e., its size). Libraries can implement different strategies for growth to balance between memory usage and reallocations, but in any case, reallocations should only happen at logarithmically growing intervals of size so that the insertion of individual elements at the end of the vector can be provided with amortized constant time complexity (see push_back).

Therefore, compared to arrays, vectors consume more memory in exchange for the ability to manage storage and grow dynamically in an efficient way.

Compared to the other dynamic sequence containers (deques, lists and forward_lists), vectors are very efficient accessing its elements (just like arrays) and relatively efficient adding or removing elements from its end. For operations that involve inserting or removing elements at positions other than the end, they perform worse than the others, and have less consistent iterators and references than lists and forward_lists.

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Iterator definitions

An iterator is any object that, pointing to some element in a range of elements (such as an array or a container), has the ability to iterate through the elements of that range using a set of operators (with at least the increment (++) and dereference (*) operators).

The most obvious form of iterator is a pointer: A pointer can point to elements in an array, and can iterate through them using the increment operator (++). But other kinds of iterators are possible. For example, each container type (such as a list) has a specific iterator type designed to iterate through its elements.

Notice that while a pointer is a form of iterator, not all iterators have the same functionality of pointers; Depending on the properties supported by iterators, they are classified into five different categories:

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Unordered Set

Unordered sets are containers that store unique elements in no particular order, and which allow for fast retrieval of individual elements based on their value.

In an unordered_set, the value of an element is at the same time its key, that identifies it uniquely. Keys are immutable, therefore, the elements in an unordered_set cannot be modified once in the container - they can be inserted and removed, though.

Internally, the elements in the unordered_set are not sorted in any particular order, but organized into buckets depending on their hash values to allow for fast access to individual elements directly by their values (with a constant average time complexity on average).

unordered_set containers are faster than set containers to access individual elements by their key, although they are generally less efficient for range iteration through a subset of their elements.

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FIFO queue

queues are a type of container adaptor, specifically designed to operate in a FIFO context (first-in first-out), where elements are inserted into one end of the container and extracted from the other.

queues are implemented as containers adaptors, which are classes that use an encapsulated object of a specific container class as its underlying container, providing a specific set of member functions to access its elements. Elements are pushed into the "back" of the specific container and popped from its "front".

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Map

Maps are associative containers that store elements formed by a combination of a key value and a mapped value, following a specific order.

In a map, the key values are generally used to sort and uniquely identify the elements, while the mapped values store the content associated to this key. The types of key and mapped value may differ, and are grouped together in member type value_type, which is a pair type combining both:

Internally, the elements in a map are always sorted by its key following a specific strict weak ordering criterion indicated by its internal comparison object (of type Compare).

map containers are generally slower than unordered_map containers to access individual elements by their key, but they allow the direct iteration on subsets based on their order.

The mapped values in a map can be accessed directly by their corresponding key using the bracket operator ((operator[]).

Maps are typically implemented as binary search trees.

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Double ended queue

deque (usually pronounced like "deck") is an irregular acronym of double-ended queue. Double-ended queues are sequence containers with dynamic sizes that can be expanded or contracted on both ends (either its front or its back).

Specific libraries may implement deques in different ways, generally as some form of dynamic array. But in any case, they allow for the individual elements to be accessed directly through random access iterators, with storage handled automatically by expanding and contracting the container as needed.

Therefore, they provide a functionality similar to vectors, but with efficient insertion and deletion of elements also at the beginning of the sequence, and not only at its end. But, unlike vectors, deques are not guaranteed to store all its elements in contiguous storage locations: accessing elements in a deque by offsetting a pointer to another element causes undefined behavior.

Both vectors and deques provide a very similar interface and can be used for similar purposes, but internally both work in quite different ways: While vectors use a single array that needs to be occasionally reallocated for growth, the elements of a deque can be scattered in different chunks of storage, with the container keeping the necessary information internally to provide direct access to any of its elements in constant time and with a uniform sequential interface (through iterators). Therefore, deques are a little more complex internally than vectors, but this allows them to grow more efficiently under certain circumstances, especially with very long sequences, where reallocations become more expensive.

For operations that involve frequent insertion or removals of elements at positions other than the beginning or the end, deques perform worse and have less consistent iterators and references than lists and forward lists.

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Array class

Arrays are fixed-size sequence containers: they hold a specific number of elements ordered in a strict linear sequence.

Internally, an array does not keep any data other than the elements it contains (not even its size, which is a template parameter, fixed on compile time). It is as efficient in terms of storage size as an ordinary array declared with the language's bracket syntax ([]). This class merely adds a layer of member and global functions to it, so that arrays can be used as standard containers.

Unlike the other standard containers, arrays have a fixed size and do not manage the allocation of its elements through an allocator: they are an aggregate type encapsulating a fixed-size array of elements. Therefore, they cannot be expanded or contracted dynamically (see vector for a similar container that can be expanded).

Zero-sized arrays are valid, but they should not be dereferenced (members front, back, and data).

Unlike with the other containers in the Standard Library, swapping two array containers is a linear operation that involves swapping all the elements in the ranges individually, which generally is a considerably less efficient operation. On the other side, this allows the iterators to elements in both containers to keep their original container association.

Another unique feature of array containers is that they can be treated as tuple objects: The header overloads the get function to access the elements of the array as if it was a tuple, as well as specialized tuple_size and tuple_element types.

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Set

Sets are containers that store unique elements following a specific order.

In a set, the value of an element also identifies it (the value is itself the key, of type T), and each value must be unique. The value of the elements in a set cannot be modified once in the container (the elements are always const), but they can be inserted or removed from the container.

Internally, the elements in a set are always sorted following a specific strict weak ordering criterion indicated by its internal comparison object (of type Compare).

set containers are generally slower than unordered_set containers to access individual elements by their key, but they allow the direct iteration on subsets based on their order.

Sets are typically implemented as binary search trees.