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A Robust Class of Data Languages and an Application to Learning

Benedikt Bollig ; Peter Habermehl ; Martin Leucker ; Benjamin Monmege.

We introduce session automata, an automata model to process data words, i.e., words over an infinite alphabet. Session automata support the notion of fresh data values, which are well suited for modeling protocols in which sessions using fresh values are of major interest, like in security protocols&nbsp;[&hellip;]

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Analyzing Robustness of Angluin's L$^*$ Algorithm in Presence of Noise

Lina Ye ; Igor Khmelnitsky ; Serge Haddad ; Benoît Barbot ; Benedikt Bollig ; Martin Leucker ; Daniel Neider ; Rajarshi Roy.

Angluin's L$^*$ algorithm learns the minimal deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approximatively correct (PAC) version substitutes an equivalence query by numerous random membership queries to get a high level&nbsp;[&hellip;]

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