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Abstract:
We show that abstract interpretation-based static program analysis can
be made efficient and precise enough to formally verify a class of
properties for a family of large programs with few or no false alarms.
This is achieved by refinement of a general purpose static analyzer
and later adaptation to particular programs of the family by the
end-user through parametrization. This is applied to the proof of
soundness of data manipulation operations at the machine level for
periodic synchronous safety critical embedded software.
The main novelties are the design principle of static analyzers by
refinement and adaptation through parametrization,
the symbolic manipulation of
expressions to improve the precision of abstract transfer functions, the
octagon, ellipsoid, and decision tree
abstract domains, all with sound
handling of rounding errors in floating point computations,
widening strategies
(with thresholds,
delayed) and the automatic
determination of the parameters (parametrized packing).
