TreeKs: A Functor to Make Numerical Abstract Domains Scalable

https://doi.org/10.1016/j.entcs.2012.09.005Get rights and content
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Abstract

Relational numerical abstract domains do not scale up. To ensure a linear cost of abstract domains, abstract interpretation-based tools analyzing large programs generally split the set of variables into independent smaller sets, sometimes sharing some non-relational information. We present a way to gain precision by keeping fully expressive relations between the subsets of variables, whilst retaining a linear complexity ensuring scalability.

Keywords

Abstract interpretation
abstract numerical domains
weakly relational domains

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