Abstract
Memory requirement estimation is an important issue in the
development of embedded systems, since memory directly influences
performance, cost and power consumption. It is therefore crucial
to have tools that automatically compute accurate estimates of
the memory requirements of programs to better control the
development process and avoid some catastrophic execution
exceptions. Many important memory issues can be expressed as the
problem of maximizing a parametric polynomial defined over a
parametric convex domain. Bernstein expansion is a technique that
has been used to compute upper bounds on polynomials defined over
intervals and parametric ldquoboxesrdquo. In this paper, we
propose an extension of this theory to more general parametric
convex domains and illustrate its applicability to the resolution
of memory issues with several application examples.
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