Add to ORKGInternational audienceWe compare two learning algorithms for generating contextual assumptions in automated assume-guarantee reasoning. The CDNF algorithm implicitly represents contextual assumptions by a conjunction of DNF formulae, while the OBDD learning algorithm uses ordered binary decision diagrams as its representation. Using these learning algorithms, the performance of assume-guarantee reasoning is compared with monolithic interpolation-based Model Checking in parametrized hardware test cases
Abstract The learning-based automated Assume–Guarantee reasoning paradigm has been applied in the la...
This paper shows how empirical human reasoning traces can be formalised and automatically analysed a...
The present document provides a comparison of different knowledge representations and their inferen...
International audienceWe propose a purely implicit solution to the contextual assumption generation ...
Abstract. We propose a purely implicit solution to the contextual as-sumption generation problem in ...
Assume-guarantee reasoning enables a “divide-and-conquer” approach to the verification of large syst...
Software systems are taking on an increasingly important role in society and are being used in criti...
This paper presents a combination between the assume-guarantee paradigm and the testing relation ioc...
Abstract. In this paper, we suggest three optimizations to the L*-based automated Assume-Guarantee r...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Abstract. Compositional reasoning aims to improve scalability of verification tools by reducing the ...
This paper shows how empirical human reasoning traces can be formalised and automatically analysed a...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Finite-state verification techniques are often hampered by the stateexplosion problem. One proposed ...
Abstract The learning-based automated Assume–Guarantee reasoning paradigm has been applied in the la...
This paper shows how empirical human reasoning traces can be formalised and automatically analysed a...
The present document provides a comparison of different knowledge representations and their inferen...
International audienceWe propose a purely implicit solution to the contextual assumption generation ...
Abstract. We propose a purely implicit solution to the contextual as-sumption generation problem in ...
Assume-guarantee reasoning enables a “divide-and-conquer” approach to the verification of large syst...
Software systems are taking on an increasingly important role in society and are being used in criti...
This paper presents a combination between the assume-guarantee paradigm and the testing relation ioc...
Abstract. In this paper, we suggest three optimizations to the L*-based automated Assume-Guarantee r...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Abstract. Compositional reasoning aims to improve scalability of verification tools by reducing the ...
This paper shows how empirical human reasoning traces can be formalised and automatically analysed a...
Finite-state verification techniques are often hampered by the state-explosion problem. One proposed...
Finite-state verification techniques are often hampered by the stateexplosion problem. One proposed ...
Abstract The learning-based automated Assume–Guarantee reasoning paradigm has been applied in the la...
This paper shows how empirical human reasoning traces can be formalised and automatically analysed a...
The present document provides a comparison of different knowledge representations and their inferen...