International audienceWe consider the quantitative problem of obtaining lower-bounds on the probability of termination of a given non-deterministic probabilistic program. Specifically, given a non-termination threshold p ∈ [0, 1], we aim for certificates proving that the program terminates with probability at least 1 − p. The basic idea of our approach is to find a terminating stochastic invariant, i.e. a subset SI of program states such that (i) the probability of the program ever leaving SI is no more than p, and (ii) almost-surely, the program either leaves SI or terminates. While stochastic invariants are already well-known, we provide the first proof that the idea above is not only sound, but also complete for quantitative termination ...
Termination analysis has received considerable attention in Logic Programming for several decades. I...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
We consider the problem of automatically verifying that a parameterized family of probabilistic conc...
We consider the quantitative problem of obtaining lower-bounds on the probability of termination of ...
Termination is one of the basic liveness properties, and we study the termination problem for probab...
We present a new proof rule for proving almost-sure termination of probabilistic programs, including...
In this article, we consider the termination problem of probabilistic programs with real-valued vari...
Probabilistic programs extend classical imperative programs with real-valued random variables and ra...
In this work, we consider the almost-sure termination problem for probabilistic programs that asks w...
We study termination of higher-order probabilistic functional programs with recursion, stochastic co...
AbstractIn this note we show that probabilistic termination of concurrent programs is in many cases ...
In this paper, we consider termination of probabilistic programs with real-valued variables. The que...
International audienceIn this work, we consider the almost-sure termination problem for probabilisti...
An important question for a probabilistic program is whether the probability mass of all its divergi...
We present the first machine learning approach to the termination analysis of probabilistic programs...
Termination analysis has received considerable attention in Logic Programming for several decades. I...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
We consider the problem of automatically verifying that a parameterized family of probabilistic conc...
We consider the quantitative problem of obtaining lower-bounds on the probability of termination of ...
Termination is one of the basic liveness properties, and we study the termination problem for probab...
We present a new proof rule for proving almost-sure termination of probabilistic programs, including...
In this article, we consider the termination problem of probabilistic programs with real-valued vari...
Probabilistic programs extend classical imperative programs with real-valued random variables and ra...
In this work, we consider the almost-sure termination problem for probabilistic programs that asks w...
We study termination of higher-order probabilistic functional programs with recursion, stochastic co...
AbstractIn this note we show that probabilistic termination of concurrent programs is in many cases ...
In this paper, we consider termination of probabilistic programs with real-valued variables. The que...
International audienceIn this work, we consider the almost-sure termination problem for probabilisti...
An important question for a probabilistic program is whether the probability mass of all its divergi...
We present the first machine learning approach to the termination analysis of probabilistic programs...
Termination analysis has received considerable attention in Logic Programming for several decades. I...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
We consider the problem of automatically verifying that a parameterized family of probabilistic conc...