As we've seen, when using a standard implementation of an expression like
tt(one + two + three + four), where the objects are vectors having tt(n)
elements, then if we have tt(k) vectors we have to perform a total of tt(k * 2
* n) index evaluations.

Expression templates allow us to avoid many of these evaluations. When using
expression templates these templates may access the vectors, but their
elements are not accessed during addition operations. 

Assuming our expression template is named ET, and we want to add tt(one + two
+ three), then the first tt(+) operator merely creates tt(ET(one, two)). Note
that no addition is actually performed, tt(ET) merely stores (constant)
references to tt(one) (becoming tt(ET's lhs) data member) and tt(two)
(becoming tt(ET's rhs) data member). In general, tt(ET) stores references to
the two arguments that are passed to its constructor.

At the next addition operator another tt(ET) is created. Its constructor
arguments are, respectively, the tt(ET) object that has just been constructed
for tt(one) and tt(two), and the vector tt(three). Again, no addition is
performed by the ET objects.

This algorithm easily generalizes to any number of vectors. Parentheses can
also be used. E.g., tt((one + two) + (three + four)) results in
        verb(    ET(ET(one, two), ET(three, four)))

Presumably, at some point we want to obtain the sum of the vectors. For this
the expression template is provided with a conversion operator, converting the
tt(ET) object to a vector, or maybe an assignment operator doing the same.

The conversion operator looks like this:
        verb(    operator ET::VecType() const
    {                                                        
        VecType retVal;
        retVal.reserve(size());

        for (size_t ix = 0, end = size(); ix != end; ++ix)
            new(&retVal[ix]) value_type((*this)[ix]);
                                                     
        return retVal;
    })

Placement new is used for efficiency reasons: there's no need to
initialize tt(retVal) with default values first. The really interesting part,
however, is hidden behind the tt((*this)[idx]) expression: at this point the
real addition takes place.

    tt(ET's) index operator simply adds the values returned by the
corresponding index expressions of its tt(lhs) and tt(rhs) data members. If a
data member refers to a vector then the corresponding vector element is used,
adding it to the other data member's value. If a data member itself refers to
an ET object, then that nested tt(ET) object's index operator performs the
same addition on its own data members, returning their sum. So, an expression
like tt((*this)[0]) returns tt(first[0] + second[0] + third[0]), and the
computed sum is then stored in tt(retVal[0]) using placement new.

    In this case the required number of index expression evaluations are tt(n
* k) (for the n elements of the k vectors) plus n (for the n elements of
tt(retVal), adding up to tt((k + 1) * n)). 

Since tt((k + 1) * n < 2 * k * n) for tt(k > 1) expression templates evaluate
the requested addition more efficiently than the traditional implementation of
tt(operator+). An additional benefit of using expression templates is that
they do not create additional temporary vector objects when parenthesized
expressions are used.
