Jean-François Degbomont

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This work describes a data structure, the Implicit Real-Vector Automaton (IRVA), suited for representing symbolically polyhedra, i.e., regions of n-dimensional space defined by finite Boolean combinations of linear inequalities. IRVA can represent exactly arbitrary convex and non-convex polyhedra, including features such as open and closed boundaries,(More)
This work studies automata-based symbolic data structures for representing infinite sets. Such structures are used in particular by verification tools in order to represent the sets of configurations handled during symbolic exploration of infinite state spaces. Our goal is to develop an efficient projection operator for these representations. There are(More)
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