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Quantitative Weakest Hyper Pre: Unifying Correctness and Incorrectness Hyperproperties via Predicate Transformers

Authors :
Zhang, Linpeng
Zilberstein, Noam
Kaminski, Benjamin Lucien
Silva, Alexandra
Publication Year :
2024

Abstract

We present a novel \emph{weakest pre calculus} for \emph{reasoning about quantitative hyperproperties} over \emph{nondeterministic and probabilistic} programs. Whereas existing calculi allow reasoning about the expected value that a quantity assumes after program termination from a \emph{single initial state}, we do so for \emph{initial sets of states} or \emph{initial probability distributions}. We thus (i)~obtain a weakest pre calculus for hyper Hoare logic and (ii)~enable reasoning about so-called \emph{hyperquantities} which include expected values but also quantities (e.g. variance) out of scope of previous work. As a byproduct, we obtain a novel strongest post for weighted programs that extends both existing strongest and strongest liberal post calculi. Our framework reveals novel dualities between forward and backward transformers, correctness and incorrectness, as well as nontermination and unreachability.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2404.05097
Document Type :
Working Paper