
[/ Copyright 2011 Daniel James.
 / Distributed under the Boost Software License, Version 1.0. (See accompanying
 / file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) ]

[section:rationale Rationale]

The rationale for the design can be found in the original design
[footnote issue 6.18 of the __issues__ (page 63)], but an issue that
occasionally comes up is the quality of the hash function, so that
demands some more attention.

Many hash functions strive to have little correlation between the input
and output values. They attempt to uniformally distribute the output
values for very similar inputs. This hash function makes no such
attempt. In fact, for integers, the result of the hash function is often
just the input value. So similar but different input values will often
result in similar but different output values.

This means that it is not appropriate as a general hash function. For
example, a hash table may discard bits from the hash function resulting
in likely collisions, or might have poor collision resolution when hash
values are clustered together. In such cases this hash function will
preform poorly.

So why not implement a higher quality hash function? Well, the standard
makes no such guarantee, it just requires that the hashes of two
different values are unlikely to collide. Containers or algorithms
designed to work with the standard hash function will have to be
implemented to work well when the hash function's output is correlated
to its input. Since they are paying that cost a higher quality hash function
would be wasteful.

For other use cases, if you do need a higher quality hash function,
there are several options
available. One is to use a second hash on the output of this hash
function, such as [@http://www.concentric.net/~ttwang/tech/inthash.htm
Thomas Wang's hash function]. This this may not work as
well as a hash algorithm tailored for the input.

For strings that are several fast, high quality hash functions
available (for example [@http://code.google.com/p/smhasher/ MurmurHash3]
and [@http://code.google.com/p/cityhash/ Google's CityHash]),
although they tend to be more machine specific.
These may also be appropriate for hashing a binary representation of
your data - providing that all equal values have an equal
representation, which is not always the case (e.g. for floating point
values).

[endsect]