Causality-Aided Falsification
Copyright policy )Causality-Aided Falsification
Falsification is drawing attention in quality assurance of heterogeneous systems whose complexities are beyond most verification techniques' scalability. In this paper we introduce the idea of causality aid in falsification: by providing a falsification solver -- that relies on stochastic optimization of a certain cost function -- with suitable causal information expressed by a Bayesian network, search for a falsifying input value can be efficient. Our experiment results show the idea's viability.
In Proceedings FVAV 2017, arXiv:1709.02126
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Logic in Computer Science, Computer Science - Artificial Intelligence, QA75.5-76.95, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Machine Learning (cs.LG), Logic in Computer Science (cs.LO), Artificial Intelligence (cs.AI), Electronic computers. Computer science, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Mathematics
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Logic in Computer Science, Computer Science - Artificial Intelligence, QA75.5-76.95, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Machine Learning (cs.LG), Logic in Computer Science (cs.LO), Artificial Intelligence (cs.AI), Electronic computers. Computer science, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Mathematics
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