Model-based testing (MBT) is a well-known technology, which allows for automatic test case generation, execution and evaluation. To test non-functional properties, a number of test MBT frameworks have been developed to test systems with real-time, continuous behaviour, symbolic data and quantitative system aspects. Notably, a lot of these frameworks are based on Tretmans' classical input/output conformance (ioco) framework. However, a model-based test theory handling probabilistic behaviour does not exist yet. Probability plays a role in many different systems: unreliable communication channels, randomized algorithms and communication protocols, service level agreements pinning down up-time percentages, etc. Therefore, a probabilistic test ...
AbstractIn this paper we extend de Nicola and Hennessy’s testing theory to deal with probabilities. ...
One of the most studied extensions of testing theory to nondeterministic and probabilistic processe...
AbstractWe present a testing preorder for probabilistic processes based on a quantification of the p...
Model-based testing (MBT) is a well-known technology, which allows for automatic test case generatio...
This paper presents a model-based testing framework for probabilistic systems. We provide algorithms...
In the last years, increasingly complex systems are being put in charge of critical tasks. When thes...
This work presents an executable model-based testing framework for probabilistic systems with non-de...
In the last years, increasingly complex systems are being put in charge of critical tasks. When thes...
Abstract. A new model based testing theory built on simulation semantics is presented. At the core o...
We introduce a notion of finite testing, based on statistical hypothesis tests, via a variant of the...
AbstractWe consider the specification and testing of systems where probabilistic information is not ...
International audienceWe propose a theoretical testing framework and a test generation algorithm for...
This paper provides a comprehensive introduction to a framework for formal testing using labelled tr...
AbstractWe develop a general testing scenario for probabilistic processes, giving rise to two theori...
Probability plays an important role in many computer applications. A vast number of algorithms, prot...
AbstractIn this paper we extend de Nicola and Hennessy’s testing theory to deal with probabilities. ...
One of the most studied extensions of testing theory to nondeterministic and probabilistic processe...
AbstractWe present a testing preorder for probabilistic processes based on a quantification of the p...
Model-based testing (MBT) is a well-known technology, which allows for automatic test case generatio...
This paper presents a model-based testing framework for probabilistic systems. We provide algorithms...
In the last years, increasingly complex systems are being put in charge of critical tasks. When thes...
This work presents an executable model-based testing framework for probabilistic systems with non-de...
In the last years, increasingly complex systems are being put in charge of critical tasks. When thes...
Abstract. A new model based testing theory built on simulation semantics is presented. At the core o...
We introduce a notion of finite testing, based on statistical hypothesis tests, via a variant of the...
AbstractWe consider the specification and testing of systems where probabilistic information is not ...
International audienceWe propose a theoretical testing framework and a test generation algorithm for...
This paper provides a comprehensive introduction to a framework for formal testing using labelled tr...
AbstractWe develop a general testing scenario for probabilistic processes, giving rise to two theori...
Probability plays an important role in many computer applications. A vast number of algorithms, prot...
AbstractIn this paper we extend de Nicola and Hennessy’s testing theory to deal with probabilities. ...
One of the most studied extensions of testing theory to nondeterministic and probabilistic processe...
AbstractWe present a testing preorder for probabilistic processes based on a quantification of the p...