Can you Trust your Data?
Peter Ørbæk April 1995 |
Abstract:
A new program analysis is presented, and two compile time
methods for this analysis are given. The analysis attempts to answer the
question: ``Given some trustworthy and some untrustworthy input, can we trust
the value of a given variable after execution of some code''. The analyses
are based on an abstract interpretation framework and a constraint generation
framework respectively. The analyses are proved safe with respect to an
instrumented semantics. We explicitly deal with a language with pointers and
possible aliasing problems. The constraint based analysis is related directly to the abstract interpretation and therefore indirectly to the
instrumented semantics.
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