Modern programmable blockchains have built-in support for smart contracts, ie ‍programs
that are stored on the blockchain and whose state is subject to consensus. After a smart …

We consider the quantitative problem of obtaining lower-bounds on the probability of
termination of a given non-deterministic probabilistic program. Specifically, given a non …

Template-based synthesis, also known as sketching, is a localized approach to program
synthesis in which the programmer provides not only a specification, but also a high-level" …

Formal reasoning about hashing-based probabilistic data structures often requires
reasoning about random variables where when one variable gets larger (such as the …

Probabilistic programs often trade accuracy for efficiency, and thus may, with a small
probability, return an incorrect result. It is important to obtain precise bounds for the …

We study discrete probabilistic programs with potentially unbounded looping behaviors over
an infinite state space. We present, to the best of our knowledge, the first decidability result …

We present an exact Bayesian inference method for inferring posterior distributions encoded
by probabilistic programs featuring possibly unbounded loops. Our method is built on a …

Reinforcement learning has received much attention for learning controllers of deterministic
systems. We consider a learner-verifier framework for stochastic control systems and survey …

We present an exact Bayesian inference method for inferring posterior distributions encoded
by probabilistic programs featuring possibly unbounded looping behaviors. Our method is …

We present a new proof rule for verifying lower bounds on quantities of probabilistic
programs. Our proof rule is not confined to almost-surely terminating programs--as is the …