specifies additional characteristics of Ada implementations intended
for real-time systems software. To conform to this Annex, an implementation
shall also conform to the Systems Programming Annex.
The metrics are documentation requirements; an implementation
shall document the values of the language-defined metrics for at least
one configuration of hardware or an underlying system supported by the
implementation, and shall document the details of that configuration.
The metrics do not necessarily yield a simple number.
For some, a range is more suitable, for others a formula dependent on
some parameter is appropriate, and for others, it may be more suitable
to break the metric into several cases. Unless specified otherwise, the
metrics in this annex are expressed in processor clock cycles. For metrics
that require documentation of an upper bound, if there is no upper bound,
the implementation shall report that the metric is unbounded.
1 The specification of the metrics makes
a distinction between upper bounds and simple execution times. Where
something is just specified as “the execution time of” a
piece of code, this leaves one the freedom to choose a nonpathological
case. This kind of metric is of the form “there exists a program
such that the value of the metric is V”. Conversely, the meaning
of upper bounds is “there is no program such that the value of
the metric is greater than V”. This kind of metric can only be
partially tested, by finding the value of V for one or more test programs.
2 The metrics do not cover the whole language;
they are limited to features that are specified in Annex
, “Systems Programming
in this Annex. The metrics are intended to provide guidance to potential
users as to whether a particular implementation of such a feature is
going to be adequate for a particular real-time application. As such,
the metrics are aimed at known implementation choices that can result
in significant performance differences.
3 The purpose of the metrics is not necessarily
to provide fine-grained quantitative results or to serve as a comparison
between different implementations on the same or different platforms.
Instead, their goal is rather qualitative; to define a standard set of
approximate values that can be measured and used to estimate the general
suitability of an implementation, or to evaluate the comparative utility
of certain features of an implementation for a particular real-time application.