We introduce a system of monadic affine sized types, which substantially generalise usual sized types, and allows this way to capture probabilistic higher-order programs which terminate almost surely. Going beyond plain, strong normalisation without losing soundness turns out to be a hard task, which cannot be accomplished without a richer, quantitative notion of types, but also without imposing some affinity constraints. The proposed type system is powerful enough to type classic examples of probabilistically terminating programs such as random walks. The way typable programs are proved to be almost surely terminating is based on reducibility, but requires a substantial adaptation of the technique
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
We present the first machine learning approach to the termination analysis of probabilistic programs...
International audienceIn the last two decades, there has been much progress on model checking of bot...
We introduce a system of monadic affine sized types, which substantially generalizes usual sized typ...
International audienceWe introduce a system of monadic affine sized types, which substantially gener...
Probabilistic programs extend classical imperative programs with real-valued random variables and ra...
We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stoch...
International audienceWe consider the quantitative problem of obtaining lower-bounds on the probabil...
We present a new proof rule for proving almost-sure termination of probabilistic programs, including...
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 ...
Termination is one of the basic liveness properties, and we study the termination problem for probab...
In sequential functional languages, sized types enable termination checking of programs with complex...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
We present the first machine learning approach to the termination analysis of probabilistic programs...
International audienceIn the last two decades, there has been much progress on model checking of bot...
We introduce a system of monadic affine sized types, which substantially generalizes usual sized typ...
International audienceWe introduce a system of monadic affine sized types, which substantially gener...
Probabilistic programs extend classical imperative programs with real-valued random variables and ra...
We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stoch...
International audienceWe consider the quantitative problem of obtaining lower-bounds on the probabil...
We present a new proof rule for proving almost-sure termination of probabilistic programs, including...
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 ...
Termination is one of the basic liveness properties, and we study the termination problem for probab...
In sequential functional languages, sized types enable termination checking of programs with complex...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
We show that complexity analysis of probabilistic higher-order functional programs can be carried ou...
We present the first machine learning approach to the termination analysis of probabilistic programs...
International audienceIn the last two decades, there has been much progress on model checking of bot...