18th International Symposium, SAS 2011, Venice, Italy, September 14-16, 2011. ProceedingsThe standard approach to program transformation involves the use of discrete logical reasoning to prove that the transformation does not change the observable semantics of the program. We propose a new approach that, in contrast, uses probabilistic reasoning to justify the application of transformations that may change, within probabilistic accuracy bounds, the result that the program produces. Our new approach produces probabilistic guarantees of the form ℙ(|D| ≥ B) ≤ ε, ε ∈ (0, 1), where D is the difference between the results that the transformed and original programs produce, B is an acceptability bound on the absolute value of D, and ε is the maxi...
Abstraction is a fundamental tool for reasoning about a complex system. Program abstraction has been...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
We present a new foundation for the analysis and transformation of computer programs.Standard approa...
We present a new foundation for the analysis and transformation of computer programs. Standard appro...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
"A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in the ...
Probabilistic modeling and reasoning are central tasks in artificial intelligence and machine learni...
In earlier work, we introduced probability to the B by providing a probabilistic choice substitution...
Probabilistic predicate transformers provide a semantics for imperative programs containing both dem...
Probabilistic programs [6] are sequential programs, written in languages like C, Java, Scala, or ML,...
Probabilistic predicate transformers provide a semantics for imperative programs containing both dem...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
We identify a refinement algebra for reasoning about probabilistic program transformations in a tota...
Abstract. In earlier work, we introduced probability to the B-Method (B) by providing a probabilisti...
Abstraction is a fundamental tool for reasoning about a complex system. Program abstraction has been...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
We present a new foundation for the analysis and transformation of computer programs.Standard approa...
We present a new foundation for the analysis and transformation of computer programs. Standard appro...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
"A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in the ...
Probabilistic modeling and reasoning are central tasks in artificial intelligence and machine learni...
In earlier work, we introduced probability to the B by providing a probabilistic choice substitution...
Probabilistic predicate transformers provide a semantics for imperative programs containing both dem...
Probabilistic programs [6] are sequential programs, written in languages like C, Java, Scala, or ML,...
Probabilistic predicate transformers provide a semantics for imperative programs containing both dem...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
We identify a refinement algebra for reasoning about probabilistic program transformations in a tota...
Abstract. In earlier work, we introduced probability to the B-Method (B) by providing a probabilisti...
Abstraction is a fundamental tool for reasoning about a complex system. Program abstraction has been...
Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calcul...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...