International audienceBIP is a component-based framework supporting rigorous design of embedded systems. This paper presents SBIP, an extension of BIP that relies on a new stochastic semantics that enables veri cation of large-size systems by using Statistical Model Checking. The approach is illustrated on several industrial case studies
This paper presents a major new release of SBIP, an extensible statistical model checker for Metric ...
International audienceThis paper presents a major new release of SBIP, an extensi-ble statistical mo...
In this thesis, we consider two problems that statistical model checking must cope. The first proble...
International audienceBIP is a component-based framework supporting rigorous design of embedded syst...
BIP is a component-based framework supporting rigorous design of embedded systems. This paper presen...
International audienceIn this paper we survey the main experiments performed using the SBIP framewor...
International audienceThe SBIP framework consists of a stochastic real-time component-based modellin...
This paper presents a major new release of SBIP, an extensible statistical model checker for Metric ...
International audienceThis paper presents a major new release of SBIP, an extensi-ble statistical mo...
In this thesis, we consider two problems that statistical model checking must cope. The first proble...
International audienceBIP is a component-based framework supporting rigorous design of embedded syst...
BIP is a component-based framework supporting rigorous design of embedded systems. This paper presen...
International audienceIn this paper we survey the main experiments performed using the SBIP framewor...
International audienceThe SBIP framework consists of a stochastic real-time component-based modellin...
This paper presents a major new release of SBIP, an extensible statistical model checker for Metric ...
International audienceThis paper presents a major new release of SBIP, an extensi-ble statistical mo...
In this thesis, we consider two problems that statistical model checking must cope. The first proble...