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

We present Tachis, a higher-order separation logic to reason about the expected cost of
probabilistic programs. Inspired by the uses of time credits for reasoning about the running …

Properties such as provable security and correctness for randomized programs are naturally
expressed relationally as approximate equivalences. As a result, a number of relational …

Although randomization has long been used in concurrent programs, formal methods for
reasoning about this mixture of effects have lagged behind. In particular, no existing …

We present ExpIris, a separation logic framework for the (amortized) expected cost analysis
of probabilistic programs. ExpIris is based on Iris, parametric in the language and the cost …