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DTSTART:20170326T030000
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DTSTART:20171029T020000
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DTSTAMP:20260428T030317Z
UID:58a57fac1ebdd352904873@ist.ac.at
DTSTART:20170510T170000
DTEND:20170510T180000
DESCRIPTION:Speaker: Matteo Sammartino\nhosted by Tom Henzinger\nAbstract: 
 Automata learning\, or regular inference\, is a widely used technique for 
 creating an automaton model from observations. In recent years\, it has be
 en successfully applied to the verification of security protocols\, hardwa
 re\, and software systems. The original algorithm L* works for determinist
 ic finite automata\, and is only capable of learning control-flow models. 
 \n\nIn this talk I will present an extension of L* to learn combined contr
 ol/data-flow models in the form of nominal automata\, which are acceptors 
 of languages over infinite (structured) alphabets. After recalling L*\, I 
 will briefly present the theory of nominal sets. Then I will show how this
  theory enables extending L* to infinite alphabets in a seamless way\, wit
 h almost no modifications to the original code. Finally\, I will give a sh
 ort demo of a tool based on this work\, currently being developed at UCL.
LOCATION:Mondi Seminar Room 3\, Central Building\, ISTA
ORGANIZER:pnovotny@ist.ac.at
SUMMARY:Matteo Sammartino: Learning Nominal Automata
URL:https://talks-calendar.ista.ac.at/events/608
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