Quantitative Weakest Hyper Pre: Unifying Correctness and Incorrectness Hyperproperties via Predicate Transformers
<|reference_start|>Quantitative Weakest Hyper Pre: Unifying Correctness and Incorrectness Hyperproperties via Predicate Transformers: 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.<|reference_end|>
@article{zhang2024quantitative,
    title={Quantitative Weakest Hyper Pre: Unifying Correctness and Incorrectness
  Hyperproperties via Predicate Transformers},
    author={Linpeng Zhang, Noam Zilberstein, Benjamin Lucien Kaminski, Alexandra
  Silva},
    journal={arXiv preprint arXiv:2404.05097},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.05097},
    primaryClass={cs.LO cs.CR cs.FL cs.PL}
}