Program logics for bug-finding (such as the recently introduced Incorrectness Logic) have
framed correctness and incorrectness as dual concepts requiring different logical …

Hoare logics are proof systems that allow one to formally establish properties of computer
programs. Traditional Hoare logics prove properties of individual program executions (such …

This paper presents a new language for network programming based on a probabilistic
semantics. We extend the NetKATlanguage with new primitives for expressing probabilistic …

We present Lilac, a separation logic for reasoning about probabilistic programs where
separating conjunction captures probabilistic independence. Inspired by an analogy with …

Programs increasingly rely on randomization in applications such as cryptography and
machine learning. Analyzing randomized programs has been a fruitful research direction …

Hoare logic provides a syntax-oriented method to reason about program correctness and
has been proven effective in the verification of classical and probabilistic programs. Existing …

We present Bluebell, a program logic for reasoning about probabilistic programs where
unary and relational styles of reasoning come together to create new reasoning tools. Unary …

Probabilistic programming provides a convenient lingua franca for writing succinct and
rigorous descriptions of probabilistic models and inference tasks. Several probabilistic …

An oblivious computation is one that is free of direct and indirect information leaks, eg, due
to observable differences in timing and memory access patterns. This paper presents …

Machine learning (ML) is increasingly being applied to a wide array of domains from search
engines to autonomous vehicles. These algorithms, however, are notoriously complex and …