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        This useful, fully STL-compliant stable container designed
        by Joaquín M. López Muñoz is an hybrid between vector and list,
        providing most of the features of vector
        except element
        contiguity.
      
        Extremely convenient as they are, vectors
        have a limitation that many novice C++ programmers frequently stumble upon:
        iterators and references to an element of an vector
        are invalidated when a preceding element is erased or when the vector expands
        and needs to migrate its internal storage to a wider memory region (i.e.
        when the required size exceeds the vector's capacity). We say then that
        vectors are unstable: by
        contrast, stable containers are those for which references and iterators
        to a given element remain valid as long as the element is not erased: examples
        of stable containers within the C++ standard library are list
        and the standard associative containers (set,
        map, etc.).
      
        Sometimes stability is too precious a feature to live without, but one particular
        property of vectors, element
        contiguity, makes it impossible to add stability to this container. So, provided
        we sacrifice element contiguity, how much can a stable design approach the
        behavior of vector (random
        access iterators, amortized constant time end insertion/deletion, minimal
        memory overhead, etc.)? The following image describes the layout of a possible
        data structure upon which to base the design of a stable vector:
      
         
      
Each element is stored in its own separate node. All the nodes are referenced from a contiguous array of pointers, but also every node contains an "up" pointer referring back to the associated array cell. This up pointer is the key element to implementing stability and random accessibility:
        Iterators point to the nodes rather than to the pointer array. This ensures
        stability, as it is only the pointer array that needs to be shifted or relocated
        upon insertion or deletion. Random access operations can be implemented by
        using the pointer array as a convenient intermediate zone. For instance,
        if the iterator it holds a node pointer it.p and
        we want to advance it by n positions, we simply do:
      
it.p = *(it.p->up+n);
That is, we go "up" to the pointer array, add n there and then go "down" to the resulting node.
        General properties. stable_vector
        satisfies all the requirements of a container, a reversible container and
        a sequence and provides all the optional operations present in vector. Like
        vector, iterators are random access. stable_vector
        does not provide element contiguity; in exchange for this absence, the container
        is stable, i.e. references and iterators to an element of a stable_vector remain valid as long as the
        element is not erased, and an iterator that has been assigned the return
        value of end() always remain valid until the destruction of the associated
        stable_vector.
      
        Operation complexity. The big-O complexities
        of stable_vector operations
        match exactly those of vector. In general, insertion/deletion is constant
        time at the end of the sequence and linear elsewhere. Unlike vector, stable_vector does not internally perform
        any value_type destruction, copy/move construction/assignment operations
        other than those exactly corresponding to the insertion of new elements or
        deletion of stored elements, which can sometimes compensate in terms of performance
        for the extra burden of doing more pointer manipulation and an additional
        allocation per element.
      
        Exception safety. (according to Abrahams'
        terminology) As stable_vector
        does not internally copy/move elements around, some operations provide stronger
        exception safety guarantees than in vector:
      
Table 9.1. Exception safety
| operation | 
                  exception safety for  | 
                  exception safety for  | 
|---|---|---|
| insert | 
                  strong unless copy/move construction/assignment of  | strong | 
| erase | 
                  no-throw unless copy/move construction/assignment of  | no-throw | 
        Memory overhead. The C++ standard does not
        specifiy requirements on memory consumption, but virtually any implementation
        of vector has the same behavior
        wih respect to memory usage: the memory allocated by a vector
        v with n elements of type T is
      
mv = c∙e,
        where c is v.capacity()
        and e is sizeof(T). c can
        be as low as n if the user has explicitly reserved the exact capacity required;
        otherwise, the average value c for a growing vector
        oscillates between 1.25∙n and 1.5∙n for typical resizing policies.
        For stable_vector, the memory
        usage is
      
msv = (c + 1)p + (n + 1)(e + p),
where p is the size of a pointer. We have c + 1 and n + 1 rather than c and n because a dummy node is needed at the end of the sequence. If we call f the capacity to size ratio c/n and assume that n is large enough, we have that
msv/mv ≃ (fp + e + p)/fe.
        So, stable_vector uses less
        memory than vector only when
        e > p and the capacity to size ratio exceeds a given threshold:
      
msv < mv <-> f > (e + p)/(e - p). (provided e > p)
This threshold approaches typical values of f below 1.5 when e > 5p; in a 32-bit architecture, when e > 20 bytes.
        Summary. stable_vector
        is a drop-in replacement for vector
        providing stability of references and iterators, in exchange for missing
        element contiguity and also some performance and memory overhead. When the
        element objects are expensive to move around, the performance overhead can
        turn into a net performance gain for stable_vector
        if many middle insertions or deletions are performed or if resizing is very
        frequent. Similarly, if the elements are large there are situations when
        the memory used by stable_vector
        can actually be less than required by vector.
      
Note: Text and explanations taken from Joaquín's blog
Using sorted vectors instead of tree-based associative containers is a well-known technique in C++ world. Matt Austern's classic article Why You Shouldn't Use set, and What You Should Use Instead (C++ Report 12:4, April 2000) was enlightening:
“Red-black trees aren't the only way to organize data that permits lookup in logarithmic time. One of the basic algorithms of computer science is binary search, which works by successively dividing a range in half. Binary search is log N and it doesn't require any fancy data structures, just a sorted collection of elements. (...) You can use whatever data structure is convenient, so long as it provides STL iterator; usually it's easiest to use a C array, or a vector.”
“Both std::lower_bound and set::find take time proportional to log N, but the constants of proportionality are very different. Using g++ (...) it takes X seconds to perform a million lookups in a sorted vector<double> of a million elements, and almost twice as long (...) using a set. Moreover, the set uses almost three times as much memory (48 million bytes) as the vector (16.8 million).”
“Using a sorted vector instead of a set gives you faster lookup and much faster iteration, but at the cost of slower insertion. Insertion into a set, using set::insert, is proportional to log N, but insertion into a sorted vector, (...) , is proportional to N. Whenever you insert something into a vector, vector::insert has to make room by shifting all of the elements that follow it. On average, if you're equally likely to insert a new element anywhere, you'll be shifting N/2 elements.”
“It may sometimes be convenient to bundle all of this together into a small container adaptor. This class does not satisfy the requirements of a Standard Associative Container, since the complexity of insert is O(N) rather than O(log N), but otherwise it is almost a drop-in replacement for set.”
        Following Matt Austern's indications, Andrei Alexandrescu's Modern
        C++ Design showed AssocVector,
        a std::map drop-in replacement designed in his
        Loki library:
      
“It seems as if we're better off with a sorted vector. The disadvantages of a sorted vector are linear-time insertions and linear-time deletions (...). In exchange, a vector offers about twice the lookup speed and a much smaller working set (...). Loki saves the trouble of maintaining a sorted vector by hand by defining an AssocVector class template. AssocVector is a drop-in replacement for std::map (it supports the same set of member functions), implemented on top of std::vector. AssocVector differs from a map in the behavior of its erase functions (AssocVector::erase invalidates all iterators into the object) and in the complexity guarantees of insert and erase (linear as opposed to constant). ”
        Boost.Container flat_[multi]map/set containers are ordered, vector-like
        container based, associative containers following Austern's and Alexandrescu's
        guidelines. These ordered vector containers have also benefited with the
        addition of move semantics
        to C++11, speeding up insertion and erasure times considerably. Flat associative
        containers have the following attributes:
      
shrink_to_fit is used)
          
        When the standard template library was designed, it contained a singly linked
        list called slist. Unfortunately,
        this container was not standardized and remained as an extension for many
        standard library implementations until C++11 introduced forward_list,
        which is a bit different from the the original SGI slist.
        According to SGI STL
        documentation:
      
        “An slist
        is a singly linked list: a list where each element is linked to the next
        element, but not to the previous element. That is, it is a Sequence that
        supports forward but not backward traversal, and (amortized) constant time
        insertion and removal of elements. Slists, like lists, have the important
        property that insertion and splicing do not invalidate iterators to list
        elements, and that even removal invalidates only the iterators that point
        to the elements that are removed. The ordering of iterators may be changed
        (that is, slist<T>::iterator might have a different predecessor or
        successor after a list operation than it did before), but the iterators themselves
        will not be invalidated or made to point to different elements unless that
        invalidation or mutation is explicit.”
      
        “The main difference between slist
        and list is that list's iterators are bidirectional iterators, while slist's
        iterators are forward iterators. This means that slist
        is less versatile than list; frequently, however, bidirectional iterators
        are unnecessary. You should usually use slist
        unless you actually need the extra functionality of list, because singly
        linked lists are smaller and faster than double linked lists.”
      
        “Important performance note: like every other Sequence,
        slist defines the member
        functions insert and erase. Using these member functions carelessly, however,
        can result in disastrously slow programs. The problem is that insert's first
        argument is an iterator pos, and that it inserts the new element(s) before
        pos. This means that insert must find the iterator just before pos; this
        is a constant-time operation for list, since list has bidirectional iterators,
        but for slist it must find
        that iterator by traversing the list from the beginning up to pos. In other
        words: insert and erase are slow operations anywhere but near the beginning
        of the slist.”
      
“Slist provides the member functions insert_after and erase_after, which are constant time operations: you should always use insert_after and erase_after whenever possible. If you find that insert_after and erase_after aren't adequate for your needs, and that you often need to use insert and erase in the middle of the list, then you should probably use list instead of slist.”
        Boost.Container updates the classic slist container with C++11 features like
        move semantics and placement insertion and implements it a bit differently
        than the standard C++ forward_list.
        forward_list has no size()
        method, so it's been designed to allow (or in practice, encourage) implementations
        without tracking list size with every insertion/erasure, allowing constant-time
        splice_after(iterator, forward_list &,
        iterator,
        iterator)-based
        list merging. On the other hand slist
        offers constant-time size() for those that don't care about linear-time
        splice_after(iterator, slist &,
        iterator,
        iterator)
        size()
        and offers an additional splice_after(iterator, slist &, iterator, iterator, size_type) method that can speed up slist
        merging when the programmer already knows the size. slist
        and forward_list are therefore
        complementary.
      
        static_vector is an hybrid
        between vector and array: like vector,
        it's a sequence container with contiguous storage that can change in size,
        along with the static allocation, low overhead, and fixed capacity of array. static_vector
        is based on Adam Wulkiewicz and Andrew Hundt's high-performance varray
        class.
      
        The number of elements in a static_vector
        may vary dynamically up to a fixed capacity because elements are stored within
        the object itself similarly to an array. However, objects are initialized
        as they are inserted into static_vector
        unlike C arrays or std::array which must construct all elements
        on instantiation. The behavior of static_vector
        enables the use of statically allocated elements in cases with complex object
        lifetime requirements that would otherwise not be trivially possible. Some
        other properties:
      
        static_vector is well suited
        for use in a buffer, the internal implementation of other classes, or use
        cases where there is a fixed limit to the number of elements that must be
        stored. Embedded and realtime applications where allocation either may not
        be available or acceptable are a particular case where static_vector
        can be beneficial.
      
        small_vector is a vector-like
        container optimized for the case when it contains few elements. It contains
        some preallocated elements in-place, which allows it to avoid the use of
        dynamic storage allocation when the actual number of elements is below that
        preallocated threshold. small_vector
        is inspired by LLVM's
        SmallVector container.
        Unlike static_vector, small_vector's capacity can grow beyond
        the initial preallocated capacity.
      
        small_vector<T, N, Allocator> is convertible to small_vector_base<T,
        Allocator>,
        a type that is independent from the preallocated element count, allowing
        client code that does not need to be templated on that N argument. small_vector inherits all vector's member functions so it supports
        all standard features like emplacement, stateful allocators, etc.