# Checking policies

A checking policy controls how the `interval` class will deal with special cases like: empty intervals, infinite numbers, invalid values.

For example, let's consider `operator+(interval, T)`. The second argument could be an invalid value (for a floating-point number, it is a NaN). What to do in such a case? First, we could say that the second argument can never be an invalid number. Second, we could also say such a situation can arise but is forbidden. Third, we could allow such values and generate an empty interval when encountered. And there is many other possibilities.

It is the reason why such a policy is used: there is a lot of interesting behaviors and it would be sad to arbitrarily select one of these.

## Requirements

The checking class should satisfy the following requirement (in the form of an interface):

    /* requirements for checking policy */
    struct checking
    {
      static T inf();
      static T nan();
      static bool is_nan(const T&);
      static T empty_lower();
      static T empty_upper();
      static bool is_empty(const T&, const T&);
    };

The first function, `inf` is invoked each time the library need to create the infinite bound of an interval. For example, `interval::whole` computes `interval(-checking::inf(), checking::inf())`. If infinite values are allowed and `std::numeric_limits<T>::infinity()` returns a correct value, such a value can be used.

Next comes `nan`. This function is used each time a function need to return a value of type `T` but is unable to compute it. It only happens when one of the arguments of the function is invalid. For example, if you ask what the median value of an empty interval is, `nan` will be used. But please remember: `lower` and `upper` directly return the value stocked in the interval; so, if the interval is empty, `lower` will not answer `by` a call to `checking::nan` (but will return the same value than `checking::empty_lower` could return).

`empty_lower` and `empty_upper` respectively return the lower and upper bound of the empty interval. There is no requirements for `empty_lower` and `empty_upper` to return the same value than `checking::nan`. For example, if the type `T` does not have any invalid value, the `empty_` functions can return the [1;0] interval.

`is_nan` is used to test if a value of type `T` is invalid or not. `is_empty` tests if the interval formed by the two arguments is empty or not. Such tests will generally be at the beginning of each function which involves an argument of type `T`. If one of the inputs is declared invalid, the the function will try to produce an invalid value or an input interval.

## Synopsis

    namespace boost {
      namespace interval_lib {

    template<class T>
    struct checking_base;
    template<class T, class Checking = checking_base<T>, class Exception = exception_create_empty<T> >
    struct checking_no_empty;
    template<class T, class Checking = checking_base<T> >
    struct checking_no_nan;
    template<class T, class Checking = checking_base<T>, class Exception = exception_invalid_number<T> >
    struct checking_catch_nan;

    template<class T> struct exception_create_empty { T operator()(); };
    template<class T> struct exception_invalid_number { void operator()(); };

      } // namespace interval_lib
    } // namespace boost

## Predefined classes

In order to simplify the customization of the policy, some templates are already defined in the library.

First of all, there is `checking_base`. Thanks to the information provided by `std::numeric_limits<T>`, this class is able to generate a base for the policy. If `T` has quiet NaNs (as said by `numeric_limits::has_quiet_NaN`), then the value is used for `nan`, `empty_lower`, `empty_upper`; and a basic test is used for `is_nan` (it is `x!=x`). If `T` does not have quiet NaNs, then `nan` is an `assert(false)`, the empty interval is [1,0], and `is_nan` always return `false`. As for `nan`, `inf` returns `numeric_limits::infinity()` if possible, or is an `assert(false`) otherwise. Finally, `is_empty(T l,T u)` is always defined by `!(l<=u)`.

Next comes `checking_no_empty`. Using it means that each time an empty interval should be produced (by `empty_lower` and `empty_upper`), the function object given by the `Exception` argument of the template is invoked and the value it returns is propagated. So, if `Exception` is appropriately defined (for example it could throw an exception, hence the name of the argument), you can be sure no empty interval will ever be created. So `is_empty` will always return `false` (since there is no need to test for an empty interval). And as explained before, in that case we can also replace `nan` by an `assert(false)`; you will be sure no invalid number will ever be produced. If this template is not used, it implicitly means that all the functions can produce empty intervals and they correctly deal with empty interval arguments.

Finally there are `checking_no_nan` and `checking_catch_nan`. The first one expresses the functions of the library will never get an invalid number as argument. So `is_nan` will only return `false`. The other one means the arguments can be an invalid number but in that case, `is_nan` will call the function object `Exception` and return `false`. Indeed, this template means invalid numbers should never make their way through to the body of the function. If none of this two templates is used, it implicitly means that all the functions can get invalid number arguments and they will correctly deal with them.

`exception_create_empty` throws `std::runtime_error` with the message `"boost::interval: empty interval created"` and `exception_invalid_number` throws `std::invalid_argument` with the message `"boost::interval: invalid number"`.

## Customizing your own checking policy

In order to define a suitable policy, you need to correctly say what you expect from your interval class. First of all, are you interested in getting empty intervals at the end of a calculus? If you do not want to obtain empty intervals, `empty_lower` and `empty_upper` have to fail when invoked (they can throw an exception, set a flag, etc). However, if no function is able to produce an empty interval, it is no more necessary to do the test, so `is_empty` may always return `false`. In this case, a good compiler will do a lot of optimizations.

You could also be interested in getting empty intervals at the end of the calculus. For example, if you need to transform an array of unsure values (or intervals) in a new array of intervals, you may not want to stop the conversion at the first encountered problem. So `empty_lower` and `empty_upper` need to return suitable values in order to define an empty interval (you can use an upper bound which is not greater or equal than the lower bound for example); and `is_empty` must be able to distinguish empty intervals from the valid intervals.

Another important question is: is it possible that some base numbers (objects of type `T`) are invalid? And if it is possible, are they allowed or not ? If it is not possible, no test is necessary; `is_nan` may always return `false`. In this case too, a good compiler will do a lot of optimizations. If function arguments can hold invalid numbers, two cases must be considered according to whether they are allowed or not. If they are allowed, `is_nan` just has to test if they are invalid or not. If they are forbidden, `is_nan` should fail (exception, assert, etc.) when invoked on an invalid argument and return `false` otherwise. The value returned by `nan` does not have any interest since the interval functions are guaranteed not to produce invalid interval bounds unless the user passes invalid numbers to the constructors. So you can put an assert inside if you do not trust the library. :-)

And finally, you need to decide what to do with `nan` if it has not already been decided at the beginning, and with `inf`. These functions should return a value or start an exceptional behavior (especially if the base type does not have corresponding values).

## Some examples

- If you need a checking policy that allows the library to correctly manipulate data, even if they contain invalid numbers and empty intervals, then `checking_base<T>` is a possibility.
- If you do not want empty intervals to be created and are not sure all the numbers are valid, then `checking_catch_nan<T, checking_no_empty<T> >` can help you. This is the default policy and it is also called `interval_lib::checking_strict`.
- If all the numbers will be valid and if no empty interval is supposed to be created (or if you do not want them to be created), then you can use `checking_no_nan<T, checking_no_empty<T> >`. Please note that if `T` does not have a way to represent invalid numbers, then this policy will behave the same way as `checking_no_empty<T>`.
- If all numerical data are valid but the algorithm can produce and manipulate empty intervals, then `checking_no_nan<T>` should be used.
- Similarly, if invalid data have to be signaled and the algorithm can manipulate empty intervals, the `checking_catch_nan<T>` is a solution.
- If you do not mind having undefined results when an empty interval or an interval number is produced, your best bet is to create your own policy by overloading `checking_base` and modifying `is_nan` et `is_empty` in order for them to always return `false`. It is probably the fastest checking policy available; however, it suffers from its deficient security.

Revised: 2003-01-19
Copyright (c) Guillaume Melquiond, Sylvain Pion, Hervé Brönnimann, 2002.
Polytechnic University.