We develop a weakest-precondition-style calculus à la Dijkstra for reasoning about
amortized expected runtimes of randomized algorithms with access to dynamic memory …

We present a novel weakest pre calculus for reasoning about quantitative hyperproperties
over nondeterministic and probabilistic programs. Whereas existing calculi allow reasoning …

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

Cost analysis, also known as resource usage analysis, is the task of finding bounds on the
total cost of a program and is a well-studied problem in static analysis. In this work, we …

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

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 …

Morgan and McIver's weakest pre-expectation framework is one of the most well-established
methods for deductive verification of probabilistic programs. Roughly, the idea is to …

Quantitative separation logic (QSL) is an extension of separation logic (SL) for the
verification of probabilistic pointer programs. In QSL, formulae evaluate to real numbers …

We present a novel strongest-postcondition-style calculus for quantitative reasoning about
non-deterministic programs with loops. Whereas existing quantitative weakest pre allows …