We present a novel static analysis technique to derive higher moments for program
variables for a large class of probabilistic loops with potentially uncountable state spaces …

Essential tasks for the verification of probabilistic programs include bounding expected
outcomes and proving termination in finite expected runtime. We contribute a simple yet …

Wir studieren die quantitative Analyse probabilistischer Programme. Dabei untersuchen wir
vornehmlich zwei Aspekte: Die Analysetechniken selbst, sowie die komplexitäts-bzw …

We consider the problem of expected cost analysis over nondeterministic probabilistic
programs, which aims at automated methods for analyzing the resource-usage of such …

We present the first machine learning approach to the termination analysis of probabilistic
programs. Ranking supermartingales (RSMs) prove that probabilistic programs halt, in …

We consider imperative programs that involve both randomization and pure
nondeterminism. The central question is how to find a strategy resolving the pure …

Almost-sure termination is an important correctness property for probabilistic programs, and
a number of program logics have been developed for establishing it. However, these logics …

We revisit two well-established verification techniques, k-induction and bounded model
checking (BMC), in the more general setting of fixed point theory over complete lattices. Our …

This paper presents a quantitative program verification infrastructure for discrete
probabilistic programs. Our infrastructure can be viewed as the probabilistic analogue of …

In this work, we consider the almost-sure termination problem for probabilistic programs that
asks whether a given probabilistic program terminates with probability 1. Scalable …